MICROTAB Version 7

CROSS TABULATION

SOFTWARE

THE STANDARD OF EXCELLENCE IN CROSS TABULATION SOFTWARE

Copyrighted By MICROTAB, INCORPORATED

Copyright Notice

Both the program and this manual are proprietary, copyrighted material. No part of either may be reproduced, transmitted, stored or translated into any other computer or foreign

language without the express written permission of Microtab, Incorporated.

The program and the manual have been copyrighted by Microtab, Incorporated every year from 1982 through 2008. The manual and software are protected by both United States

Copyright Law and International Treaty provisions.

Trademark Acknowledgements

Microtab is a registered trademark of Microtab, Incorporated. MS-DOS, Word, Excel and Windows are registered trademarks of Microsoft Corporation.

IBM is a registered trademark of International Business Machines, Inc. SPSS is a registered trademark of SPSS, Inc.

Microtab, Incorporated 10945 State Bridge Road · Alpharetta, Georgia 30022 USA

(770) 664-9244· Fax (770) 664-9798 e-mail: support@microtab.com

You can also reach us at: http://www.microtab.com

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Table of Contents Introduction............................................................................................................. 6 Additional Capabilities............................................................................................ 8 Overview of The Toolbar...................................................................................... 11 Study New ........................................................................................................... 15 Open .......................................................................................................... 18 Save/Save As/Copy................................................................................... 19 Edit Properties........................................................................................... 20 Edit Specs.................................................................................................. 20 Print Specs................................................................................................. 20 Variables ................................................................................................... 20 Data Add............................................................................................................ 23 Edit ............................................................................................................ 24 Merge ........................................................................................................ 24 Key Verify................................................................................................. 24 Change Respondent ID Number ............................................................... 25 Delete By ID Number..................................................................................... 25 By Condition ....................................................................................... 26 Print ........................................................................................................... 26 Browse ...................................................................................................... 27 Import........................................................................................................ 27 Export........................................................................................................ 30 Columns Condition Checking Skip Patterns ....................................................................................... 35 Punch Presence ................................................................................... 37 Punch Distribution .............................................................................. 38 Punch Overflow .................................................................................. 39 Multiple Punches................................................................................. 40 Column Addition................................................................................. 40 Value Field Addition........................................................................... 41 Against Study Specs............................................................................ 43 Recode Data ..................................................................................................... 43 Punch Distribution .............................................................................. 45 Specific Numeric Values .................................................................... 46 Numeric Ranges .................................................................................. 49 Conditional.......................................................................................... 50 Clean ......................................................................................................... 51 Copy .......................................................................................................... 52 Spread........................................................................................................ 54

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Summary Marginals .................................................................................................. 56 Arrays........................................................................................................ 57 One by Ones.............................................................................................. 59 Record Numbers ....................................................................................... 61 Weighting Sample Balancing...................................................................................... 63 Weighting Files ......................................................................................... 65 Banners Banner & Page Layout .............................................................................. 68 Labeling .................................................................................................... 69 Qualifiers................................................................................................... 70 Header & Footer........................................................................................ 70 Data Format............................................................................................... 71 Stat Parameters.......................................................................................... 72 Print ........................................................................................................... 74 Tables

Overview................................................................................................... 75 Regular ...................................................................................................... 76

General ................................................................................................ 76 Stubs.................................................................................................... 77 Append .......................................................................................... 78 Ranking ......................................................................................... 81 Medians/Means/Stat............................................................................ 82 Value ......................................................................................................... 85 General ................................................................................................ 86 Stubs.................................................................................................... 87 Append .......................................................................................... 88 Medians/Means/Stat............................................................................ 89 Mean Summary ......................................................................................... 90 Add Stubs ............................................................................................ 90 Print Options ....................................................................................... 92 Volume...................................................................................................... 92 Advanced .................................................................................................. 94 Reports Report Manager....................................................................................... 100 Printing Tables ........................................................................................ 103 Chart Charts ..................................................................................................... 106 New ..................................................................................................... 107 Options ................................................................................................... 108 Tools Statistical Testing.................................................................................... 111 Data Manipulation................................................................................... 111 Log Viewer ............................................................................................. 114 Create DOS version files......................................................................... 115

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Tools (continued) Options General .............................................................................................. 116 Reports .............................................................................................. 116 Preview.............................................................................................. 116 Print ................................................................................................... 117 Filter .................................................................................................. 117 Template............................................................................................ 118 Stat .................................................................................................... 119 Help Help Topics ............................................................................................. 120 About Microtab ....................................................................................... 120 Appendix 1 - Data Format Layout & Types ..................................................... 121

Appendix 2 - Filtering (Sub-sample Qualification) .......................................... 123

Appendix 3 - Printer Limitations ...................................................................... 125

Appendix 4 - Statistics ...................................................................................... 126 (Median, Mean, Variance, Standard Deviation, Standard Error)

Appendix 5A Statistics (Warnings and Cautions) ......................................................... 129 (Chi-Square, Z-tests, t-tests)

Appendix 5B - Statistics (Chi-Squares) .............................................................. 134

Appendix 5C - Statistics (Z-tests) ....................................................................... 138

Appendix 6 - Other Statistical Routines............................................................ 142

Appendix 7 - Rank Ordering Stub Lines........................................................... 144

Appendix 8 - Rank Ordering Stub Lines – A Unique Situation........................ 148

Appendix 9 - Importing an Excel File............................................................... 150

Appendix 10 - Importing Other file types........................................................... 153 (SPSS*.SAV files, Triple S *.SSS and *.ASC files)

Appendix 11 - Variable names VS Column numbers......................................... 159

Appendix 12 - Creating *.SAV files with Ci3 .................................................... 161

Appendix 13 - Creating other file types.............................................................. 163

Appendix 14 - Advanced Charting ..................................................................... 164

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INTRODUCTION

Congratulations! and welcome to the world of in-house data processing. You have purchased the STANDARD OF EXCELLENCE in cross tabulation software. Microtab Cross Tabulation software can meet the data processing needs for all of your marketing research studies. By so doing, you save money; you exercise better control over your projects; and you provide a higher level of client service. The tables you can generate using Microtab conform to industry standards for cross tabulation tables in every respect. Though this software is easy to use, the sheer power it offers might make a first-time user feel a bit uneasy. At this point, you have probably read literature on Microtab's many features, and you might think, "To do all of this, the software must be a monster." Though you are eager to have the software work for you, there might be some natural apprehension associated with a new, powerful software suite, similar perhaps to the hiring of a new employee whose credentials are more impressive than anyone you've ever seen before. Certainly, you want to take advantage of that employee's talents immediately, but you might experience anxiety about your first meeting with him or her. The purpose of the following is to briefly explain what Microtab does and reduce any "new employee" anxieties that might push you away from the software. As you will see, Microtab is a logical, easy-to-understand marketing research tool. In survey research, we deal with peoples’ opinions and their reactions to specific products, services, or advertisements. An accepted way of finding out what people think is to use questionnaires. Though information generated is informative, it is relatively useless unless it is easily readable. A stack of questionnaires contains information spread out over hundreds or thousands of pages. No matter how carefully created and how thoroughly answered the questionnaires may be, the data they contain is of little help in a non-compiled state. The primary function of Microtab cross tabulation software is to take this physical data and arrange it into a compressed and more useful form. Microtab takes the information contained in a stack of questionnaires, compresses it, and presents you with easy-to-read tables. The process is often thought of as "data reduction". This process contains three steps: entering questionnaire information into the computer, manipulating the data, and then outputting the data back to you in an understandable form. Perhaps the only reason that Microtab seems overwhelming is that the designers sought to give its users complete control over all three steps of the process. Users decide how to enter the data and how to have the software check the data to insure 100% data integrity. You then can determine how to organize the information and how the completed tables should look. The options offered are numerous, but you will soon grow quite comfortable making the decisions that determine the appearance of your final output.

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As you begin to use the software, remember that all functions relate back to a point in the process of input, checking, reduction/manipulation, and output. As the marketing researchers who designed the software considered what needs a cross tab software package

had to fulfill, they decided ease-of-use was extremely important. For this reason, Microtab is driven by a very clear and logical system, with the idea that choices are much easier to make when you have them listed in front of you. Should you choose not to read the entire manual, we strongly urge you to read page 27 (DATA > IMPORT) and review Appendix 1 for a discussion of the different types of data formats as a starting point.

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ENHANCEMENTS MADE TO MICROTAB Version 7

Enhancements: 1. Importing from Excel (Office 2007) – Office 2007 was enhanced by Microsoft so that a user could have more than 256 columns in an Excel sheet, which would seem to be a boon to market researchers who use Excel for data entry. Unfortunately, Microsoft Corporation still limits developers (who have to use Microsoft’s import dll), to importing only 255 columns from an Excel sheet. Out of necessity, Microtab Version 7 has added the capability to import a CSV file of any length to get around this limitation set by Microsoft. Save the Excel file in CSV format and you can then read the CSV file into Microtab, regardless of length. 2. Value tables – Starting with Version 6, value table row labels (stubs) could be automatically filled-in (by clicking the autofill button) with each unique value being assigned a unique stub. The value is shown as the row label. With Version 7 we have increased the number of rows (stubs) allowed in a value table from 99 to 999. This removes most restrictions when creating a value table showing numeric zip codes. 3. Value tables – Two additional value table stats can be shown on a value table. These two stats are the minimum value found in the field and the maximum value found in a field. The minimum and maximum values found are printed for each banner point, and the values are printed above the mean at the bottom of the table. 4. X and Y codes – The codes/punches X and Y are inherent to the IBM360 column binary format (80 column card image format). Because the use of this format is not the most widely used data format anymore, we have added the ability to NOT use the X and Y codes for selected functions. The shipping default setting is that X and Y will be used for certain functions. However, you can change the default by going to (on the toolbar) Tools>Options>General and clearing the check box in the lower right hand corner of the screen. If the check box is cleared, the use of X and Y codes will not be utilized for conditional recoding, single data column recoding, and spreading data recoding. The use of X and Y codes will likewise not be allowed when importing SPSS, Triple-S, Excel, DBF, and CSV files. The X and Y radio buttons will either be disabled or the codes to be created (mapped) will not display the X and Y codes. Improvements: 1. Statistics – In regular tables the weights that a user assigns (for means, medians) can be positive or negative and can be assigned in ascending order (example: from 1 to 5 going top to bottom) or descending order (example: from +2 to -2 going top to bottom). The various combinations offered for presentation sometimes caused incorrect medians to be calculated. .

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2. Stub (row) label length – With most printers the optimal stub label length is 19 characters per line. This length allows for the generation of a report with 22 banner points on most printers. With the ability to create tables automatically using text files generated by SPSS and Triple-S files, 19 characters are sometimes insufficient. With Version 6, a

user had to specify the length that was desired before the first table was created. Over-riding the warning to specify a stub line length caused the program to assign a default row length for labeling of 15 characters. With Version 7 we added the ability (under <Tools><Options><Reports>) to set the default amount of space available (length) to any number between 15 and 30. This number is set to 19 with the shipping version but it can be modified (under tools) to present a different length. The default set by the user can always be over-ridden for selected banners. 3. Banner point shading – The option of shading of selected banner points made available in Version 6 sometimes created shading that was visible on the preview screen but not on the printed copy. This was caused by the capabilities of different printers handling shading differently. With Version 7 we have added a slide bar under <Tools><Options><Print> so that you can easily control the density of the shading during printing. This is used when printing from Microtab, Word or HTML. 4. Office 2007 – With Office 2007 Microsoft changed the file name extension for Excel files and made other formatting changes for both Excel and Word files. Because Microtab allows tables to be saved in both Word and Excel format, we had to modify our conversion routines. 5. Leasing and Evaluating – With the release of Version 7 of Microtab, a potential user can enjoy affordable lease options starting at less than $100 per station per month. Before committing to a lease OR electing to purchase the software, a new potential user can evaluate Version 7 free-of-charge for 90 days, with free 24/7 technical support included. 6. Stat (excluding the total banner point) – The total banner point cannot be used during stat testing. On one hand, in the "Banner & Page layout" screen, the "Print the TOTAL banner point" checkbox cannot be checked when banner point #1 was specified as a "left point" in statistics. In such case, when a user checks the "Print the TOTAL banner point" checkbox and then clicks "OK", she receives the following message: ""Print the TOTAL banner point" cannot be checked as long as banner point #1 is included as the left banner point in statistical testing. If the TOTAL banner point is required to be printed, please remove the banner point #1 from statistics.". On the other hand, in the "Statistical testing parameters" screen, when the user specifies the banner point #1 as "left point" in statistics, while "Print the TOTAL banner point" was checked, the following message will display when clicking "OK": "Banner point #1 is not allowed in block <block number> when "Print the TOTAL banner point" is checked."

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7. Excel import – improved logic - A recurrent issue with importing from Excel was due to the fact that sometimes the Microtab software wrongly assumed that an input column contained text, while it contained in fact numeric values. This happened because the data type is actually determined by the Microsoft driver that we are using in order to read in Excel files. This driver "reads the first eight rows of data, in order to make an educated guess at the data type of each column". Previously, if a column had no data in the first eight records of the file, it was considered as containing text, even when subsequent rows contained numeric values. As a workaround, Microtab Version 7 will now ignore the driver's decision and instead determine the data type by itself, after scanning the data. Even when the driver reports that a column contains text, as long as Microtab detects that the column contains only numeric values (identified by Microtab as strings that contain only

digits), Microtab assumes that the column has a numeric data type, allowing the user to select it for import. 8. Delete multiple stubs (row labels) – The multiple selection is achieved in the Windows manner, by using CTRL + click and/or SHIFT + click. The enhancement applies to the following types of tables: regular, value, volume and advanced N box.

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9. Display variables – A user can select a subset of variables to be displayed in the 'Browse' window. Note: due to a technical limitation, the maximum number of variables that can be selected is 450.

Overview Of The Toolbar Study

New –initiate a new study Open –access an already created study Save as –copy all files or selected files from the opened study to a new study Edit properties – change the number of cards per questionnaire, the high column or

edit the description Edit specs – edit card column properties Print specs – generate a paper copy of your questionnaire specifications Variables – with the SPSS add-on module, you can import variable names, question

text and the answers to the questions and then click one button to create tables. You can specify for each table whether the stubs should be rank ordered or weighted (for means and statistical testing). Globally, designate whether the last stub (DK) should be ignored (for assigning weights) and if the weights should be reversed from the punch values.

Data

Add – enter new data to the database Edit – change existing data in the database Merge – enter, edit or view data in selected card columns Key verify – confirm data already entered Change respondent ID number – change respondent ID number or re-instate deleted

respondents Delete

By ID number – delete respondents one at a time By condition – delete multiple respondents with one command

Browse – if you have purchased the SPSS Add-on module or have entered variable names from within Microtab, you can display the records (one line each) showing their recorded data or their variable labels.

Print – display or print a respondent’s stored data Import – import data from ASCII string or card format, IBM 360 format, Microtab

format, Excel (xls) and DBF format. With the SPSS add-on module, import data in SPSS format or Triple S format

Export – export data to ASCII string or card format, IBM 360 format, Excel (xls) format, DBF format, or comma delimited format. With the SPSS Add-on module, export data in SPSS format or Triple S format

Columns

Condition checking Skip patterns – Check skip pattern logic Punch presence – examine who does or does not have specific data Punch distribution – show an array with the number of respondents that

gave one, two, three, etc. answers to a long list of choices Punch overflow – list the respondent numbers of those records that have

answers that exceed a user specified number Multiple punches – find records that have multiple punches

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Column addition – check for inaccuracies in ranking type questions

Value field addition - check for inaccuracies in constant sum or percentage type questions

Against study specs – find violations of study specifications Recode

Data – create new variables based on existing single column data Punch distribution – create a number in a user specified (new) variable that

represents the number of answers given Specific numeric values - create new variables based on existing value field

data Numeric ranges – compress value fields into ranges and create new

variables Conditional – create a new variable based on Boolean logic

Clean – remove data based on conditions Copy – copy data to new locations based on conditions Spread – copy multiple punch data into new locations as single punch variables

Summary

Marginals – generate a summary report showing frequency counts of punches in columns. Means are calculated and displayed for each column.

Arrays – generate a summary report of unique value fields and their frequency counts

One By Ones – generate a report showing one unlabelled column cross tabulated against another

Record numbers – listing of respondent/record numbers in various formats Weighting

Weighting files – create files that assign weights based on conditions or fields Sample balancing – create and calculate fields that contain weights for each record

Banners – design appearance, specify labels and qualifiers, and set-up stat testing for

column headings. Spell check is included Tables – Regular, Value, Mean Summary, Volume and Advanced tables: Set row labels,

stat testing and qualifiers for the tables to be cross tabulated. Spell checking is included. Perform independent or dependent t-tests on advanced tables.

Reports – for each report to be printed, specify which tables are to be used for a banner,

their print order, and the weight and filter files that are to be used. From the print screen specify which banners, if any, you wish to interleave.

Charts – after you have imported data and variables from SPSS or Triple S files (or

created tables from scratch and subsequently created variables), this option allows you to create charts in batch mode for inclusion into the written analysis.

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Tools – access raw data statistical testing routines, access data manipulation capabilities and default options. Defaults can be set for the location of the default folder for study data, chart size, screen preview size, margins for reports, default filter conditions, template for table stub screen and statistical bases for testing.)

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Help – access all online help topics; view Microtab version number and view/change the serial number

SPECIAL NOTE To use pre-1996 files from the Silver, Gold and Platinum Editions (DOS versions): All of your recodes and table parameter files created with the Silver, Gold and Platinum Editions of Microtab Cross Tabulation software can be used by the Microtab Editions without modification. The 1997 Professional and 1998 Professional w/Stat data files (SPC) do NOT have to be modified. They can be used without modification in the Microtab Editions. The Silver, Gold, and Platinum data files (SPC), circa 1995, do need to be modified. Again, the data files (SPC files) for the DOS versions of the Professional Editions do NOT have to be modified; they can be used as is without change. To modify the Silver, Gold and Platinum SPC files: 1. Output the SPC data using the Silver, Gold or Platinum software

• Output the data to IBM 360 column binary format (7 on the utility menu and then 1).

• Use any file name you wish as the name for the IBM360 file. 2. Read the data into the Windows Standard or Professional Edition

• Start Microtab. Initialize a new study in a new folder, creating the folder if necessary. Indicate that the new study will have a four-digit respondent ID number.

• Specify the column types and high punches or use the default specifications. • Import the IBM 360 column binary data as initial data. • Copy the other files for the DOS version of Microtab.

The above steps will create the proper SPC file for use with the Microtab Windows Editions. Special Note: Once you have converted the SPC file for use with the Windows Editions, you can only work with that specific SPC file in the Microtab Windows Editions.

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STUDY STUDY > New - Prepare the program to accept data for a study.

Example: Column eight on a questionnaire might correspond to a yes/no question, with a 1 code showing a "Yes" answer and a 2 code indicating a "No". Therefore, your specification would show that only a single code is acceptable for column eight and that the code can only be a one or a two. Enter these specifications for every column in a study. Preparation: During this procedure, you will be telling the computer what your questionnaire "looks like." Therefore, you should have a copy of the questionnaire you are going to tabulate in front of you.

Prompts:

Study Number - When you define a new study, you first have to assign a study number. We recommend that a five-digit study number be assigned. Use the first digit to indicate the year (example: a 6 to indicate 2006), the next two digits to indicate the month (example: the number 05 to indicate May), and the last two digits to indicate which study of the month this one represents (example: 18 for the 18th study that was initialized for this month). The resulting study number would be 60518.

Path – Your entry indicates the folder where the information and data for this study

will be stored. We recommend that you establish a primary folder in the C: directory called Data and sub-folders within the Data folder for every study.

Description – Type a phrase that describes this study. Number of cards – Enter the number of 80 column cards that are required to store

the data for this study. See Appendix 1 for an explanation of the 80 column card format. We use punches (in card column lingo) and codes (SPSS) interchangeably.

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Number of digits in the respondent ID number- Enter the appropriate answer. A seven digit respondent ID number permits you to have up to 10 million questionnaires in a study (actually only 9,999,999 but 10 million sounds better).

Highest column in the last card - Enter the appropriate answer, according to your

questionnaire. Your answer must be in a two-digit format - Ex: If column 38 on card 2 is your highest column, enter "38". If column 43 on card 7 is your highest, enter "43." If column 24 on card 11 is your highest, enter "24".

Click on Create default column specifications – If you check this box the program will create default (M/Y = multiple responses will be allowed with up to 12 codes) column specifications. If you elect not to check this box, you will be prompted to enter specifications for each card column.

Click on create – Your study will be created.

Questionnaire specifications – If you choose to create default column specifications, this step is skipped. If you didn’t check default column specifications, you will now enter the actual specifications for your study. The program uses card columns 1 through 4 (up to 7) to record the respondent ID number. Card column 80 stores the card number. Both 79 and 80 are used in studies over nine cards. You are not prompted to enter specifications for these reserved columns. Read the column numbers vertically, starting with card 1, column 05 (or 06 or 07 or 08). In the below example, the cursor (dark block) is below column 105. The card number is shown in a box above the column specifications. The first line after the column numbers tells you the type of data a column can hold – single answer (S), multiple answer (M), ignore (I) (no data can be entered using the keypad) or data that is part of a value field (V). The second line tells you the highest code (or punch) that is allowed in the column. Valid punches are 1 through 9, 0 and X and Y. When importing data, a ten is converted to a 0; an eleven is converted to an X; and a twelve is converted to a Y. Please contact us if you have any questions.

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For each column, you will enter two pieces of information. First, you will enter one of the following letters, indicating the type of data a particular column will hold:

S - Single punch M - Multiple punch V - Value punch I - Ignore Second, you will enter the highest punch allowed in that column. The following

hierarchy exists among the twelve punches you may enter: 1234567890XY, where the program treats a 2 as a higher punch than 1 and so on, until you reach Y, the highest punch possible. During keypad data entry, the program will not allow you to enter punches that fall outside the criteria you have setup during this stage.

If you specify a column as a value or ignore column, you do not input a high punch.

In effect, for these types of columns, you will only enter one piece of information. Although X and Y codes are not considered as part of a value field, these codes are used in Microtab to indicate a skip pattern or a respondent’s no answer response.

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Special Note: It might be tempting to speed the questionnaire specification process by specing all columns as multiple punch with a high punch of Y. This is what occurs if you “Create default study specifications”. With such specs, all data is accepted. If you spec all columns as value columns, only single punches will be accepted. Doing either of the above defeats the purpose of this process, which is to cut down on errors when you use the keypad for data entry. Setting up criteria for the data in each column ensures you complete keypad data entry with fewer errors. Therefore, we recommend that you do not spec all columns with a high punch of Y or as value field columns if you are performing keypad data entry. It is quite acceptable to do so though if you are importing an electronic data file.

Remember that columns 1 through (4-7) record the respondent ID number only.

Column 80 is used to indicate the card number. In studies over nine cards long, column 79 is also used to hold the card number. For studies over nine cards long, specify column 79 on all cards as an ignore column. You will not be prompted to enter specifications for columns 1 - 4(7) and 80. When you begin, you will automatically start in the first available column of card 1.

STUDY > Open – Switch to an already created study. You can also access Study from the

toolbar and a list of previously opened studies is shown at the bottom of the drop down box. You can open any one of the studies listed by clicking on it.

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STUDY > Save/Save as/Copy – Copy an existing study (all or selected files) to a new study number.

This allows you to establish a study that repeats itself (perhaps a tracking study) and then to use the files created for the initial study as the basis for subsequent studies.

When using this function to copy the files to the new study, you should elect not to copy the spc12345.dat file, as that file holds the data for the first wave (example) of a tracking study. Specify which files not to copy by removing the check in the box next to them.

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All file names are created based on the following convention: the first three characters designate the file type, the next five characters represent the study identifier and the three character extension is either dat or it represents the file number.

STUDY > Edit properties – Here you can change the number of cards a record

(questionnaire) should have allocated. You can increase or reduce the number of cards in a study by expanding or truncating the database using this function. The data in any cards truncated is lost. Back up the data file before doing this, as the truncated data will not be recoverable.

STUDY > Edit specs –To make changes to previously recorded study specifications.

Example: Originally, columns 113 - 150 may have been specified as ignored columns. Now your open-ended information is coded and you need to use those columns to record the data. You have to change the study specs before entering any data into those columns. Likewise, you may also wish to use columns 160 - 170 on a card that was spec’d with a high column of 159. This function is also used to create a new high column. You can change the type of data to be stored in certain columns. However, editing study specs does not affect data already entered into the columns. This means that changing column 105 from a multiple to a single punch column will not remove any of the multiple punches that are already entered. Likewise, changing columns from single punch columns to ignore columns will not remove punches already entered in those columns.

STUDY > Print specs – Use this feature to print your stored questionnaire specifications. All print functions default to Preview. This allows you to see the results on the screen without printing them. You can save a previewed file in Word format, Excel format, as a text file, as a comma delimited file (for import into any other spreadsheet) or as an HTML file.

STUDY > Variables – This option permits you to import variable names, question text

and the text of answers to a question from SPSS and Triple S formatted files. You can create your tables automatically from this screen.

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Establishing new variable names (one at a time), deleting variables one at a time or in groups and even editing of variable names and types is possible from this screen.

If you created tables in Microtab without using variable names from the library, here is where Microtab allows you to create variables from the tables. You can also enter variable names from the table manager routine. Click on the general tab in the table manager and you can enter variable names for either regular or value tables.

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An important word about creating variables from Microtab tables: To set the jargon used: Tables have stubs, and variables have answer codes. When you try to create a variable from a table, Microtab attempts to create one answer code for each stub. Due to the different nature of stubs and answer codes, caution must be used when automatically creating variables based on existing tables. On one side, a stub can be based on a complex qualifier (implemented in the Microtab 2004 Editions). On the other side, a variable name (answer code) can only be based on a single variable/code (column/single punch) combination. Creating an answer code from a stub that comes from a single column/punch combination is straightforward. When the single column/punch condition is NOT met (in a case of a complex stub qualifier), or when more than one code (punch) exists for that stub, that stub is ignored.

Important: When creating variable codes, Microtab does not allow you to define more than one answer code per column/punch combination. Consequently, when converting the stubs of a table, the resulting column/punch combinations must be unique (not used before in that table and not used before in any other variable either). When creating variables from Microtab table files, the codes for the created variables are typically based on the punches of the corresponding stubs. In the particular case when a table contains more than one stub based on the same punch, the conflict is resolved by incrementing the code number with 100. For example, if a table contains three stubs, based on the following column/punch combinations: 105/1, 106/1 and 107/1, the corresponding variable codes now receive the numbers 1, 101 and 201, respectively. A data map can be created within this screen using the print option. The variables>import capability only allows you to import this information into the existing study. You cannot create a new study nor import the data into a study from this screen. To create a new study and simultaneously import the variable names, question text, answers to the questions text and data, you would go to Data – Import and click the Create a new study button during the import process. You can also access the import capabilities in Microtab by clicking on the red down arrow icon. The variables>edit capability is useful if you wish to change a variable name, the question text, and/or the text of the answer (code). Example: You created variables from a group of Microtab tables so that you can send the data to your client in SPSS format. The default variable names assigned by Microtab consist of a table-type identifying letter followed by the reference number. To make the resulting SPSS file easier for your client to use click on a particular variable and then click on edit. In the variable name portion of the screen, type a more descriptive name, such as Q1 or Q5B. Keep in mind that if your client is using a version of SPSS older than version 12, you will need to limit your variable names to 8 characters. Version 12 and newer versions can accept the full 64 characters allotted by Microtab.

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DATA

DATA > Add - Before you can tabulate data, you must, among other tasks, enter data. This routine allows you to enter data using the numeric keypad.

Enter respondent ID number – Every record you enter must have a unique respondent ID number of from 4 to 7 digits in length. Entering a duplicate number will result in a message to that effect and you will be directed to enter a unique respondent ID number.

To enter data for single punch columns, value fields or multiple punch columns that only have a single code/punch, enter the code/punch and the cursor will automatically move to the next column that is not an ignore column. To enter multiple punches into a multiple punch spec’d column, first press the letter ‘M’ and then enter the punches. Press the <Enter> key when all the data for that column has been entered.

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After entering data for every column (or clicking END, pressing <Esc> or entering E to end), you will be asked if you want to save the changes to disk. Reply Yes or No or select Cancel. Yes saves the data and prompts you for another ID number. Replying No abandons the data entered and prompts for a respondent ID number. Cancel returns you to the last column in the record or to the last cursor position in the data entry screen before the letter E was pressed.

DATA > Edit – This option performs the same as the data entry function except that you now are editing existing data. You must enter a valid respondent ID number or record number in order to access data for editing. You would ‘edit’ a respondent’s data in order to access a specific record to inspect data or to correct data that was incorrectly generated (i.e., skip patterns not followed) or to correct data that was inaccurately entered. Position the cursor by pressing the arrow keys. After entering the data, you’ll save the data, abandon the record or return to the last column accessed (Yes, No, Cancel).

DATA > Merge – Enter the columns to which you wish to merge data (or columns you

wish to view). You can enter single column numbers, ranges, or a combination all separated by commas. Individual ranges would be entered in the format (start column)-(end column). Enter a respondent ID number (or record number) and then click Edit Data. After entering the data, you’ll save the data, abandon the record or return to the last column accessed (Yes, No, Cancel).

Example: This function is useful whenever you have to add data to a study after the initial data entry has been completed. Assume that you have to generate top-line data on a study before the open-ended coding is done. When you are setting the specifications for the study, you can reserve space for the open-ends by specifying a number of columns as ignore columns. Manually input just the close-ended data and then generate marginals for top-line information.

Later, after the open-ends are coded, you could Edit Study Specs and change the

ignored column specifications. You could then insert the open-end data using this function.

DATA > Key Verify – To confirm the accuracy of data entry, you can key verify recorded

data. You can verify all of the recorded data for a record or just selected columns.

Example: In any study, data integrity is of utmost importance. Let us assume that you want to insure with almost 100 percent accuracy that the information on the printed questionnaires is entered into the data file without error. Based upon the assumption that incorrect data would not be entered twice, you could have one person initially enter the data and a second user key verify the work.

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Sometimes, you will want to only verify selected columns. If you choose to key verify selected columns, you will be asked to select the columns you wish to verify. Input the columns you wish to check. Enter individual columns separated with

commas or indicate a range of columns to check by separating the columns with a dash, as in the example below. You will not be allowed to select a column that has been specified as an ignore column.

DATA > Change respondent ID number – First, specify the number of individual

records to be changed by entering the number. A drop down grid will appear where you may enter the current record number or respondent number. Use the arrow keys to access the different boxes on the grid. Enter the new respondent ID number(s) and click on change.

Example: After importing data from multiple floppy diskettes and running a condition check, you notice that you have duplicate respondent ID numbers and you wish to change some of them. Select this function and type the number of records you want to change. Enter the record number or current ID number. Then type in a new unique ID number and click on the change button. See above.

Another reason to change a respondent’s ID number would be if you deleted a respondent and you now wish to reinstate the record. The deletion feature assigns deleted respondents a respondent ID number of -1, so reinstating deleted respondents requires only that you assign them valid ID numbers using this function. A valid ID number is any 4 digit number (up to 7 digits) greater than zero.

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DATA > Delete > By ID number – This allows you to delete respondents one at a time. When a respondent is deleted, only the respondent ID number is changed (to a –1);

the data remains but is not accessed for any function. The respondent count at the bottom of the screen will still display the count for all the records, active AND deleted. You can re-instate (or “undelete”) a deleted respondent by changing their respondent ID number back to a positive number.

Example: After entering all the data for a study, you discover that one respondent answered his questionnaire incorrectly and his data is not valid. Using this feature, you can prevent that data from being used in any calculations. This function does not erase respondent information. The computer will always acknowledge that the record exists, but because an invalid ID number (-1) is assigned to the respondent during this deletion process, his data will not be accessed for any calculations.

DATA > Delete > By condition – Using this feature, you can delete a group of respondents by specifying a qualifier (or a condition they all meet).

Example: Perhaps you want to delete all the data collected by one field service. Choose this function, click on the Set/Edit filter button and type in the column and punch identifier for that field service. The capability could also be used to reduce the size of a data base that was created through web interviewing. Perhaps you have collected hundreds of thousands of interviews on the web and now you want to tabulate just those that represent a small sub-sample. You can easily delete those who do not meet your criteria. Again, using the Set/Edit filter feature, specify the condition that must be met for all those people you wish to remove (delete) from the data.

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DATA > Print – You can print one respondent’s recorded data with this function. You only need to know either the respondent number or the record number of the

respondent you wish to print. If you know the respondent number, enter it now. If you know only the record number, press <tab> and then input the record number.

DATA > Browse –View a respondent’s data (in a spreadsheet-like preview) by variable

name (column) and code (punch) or by the alpha response to the questions. Answer code labels for all variables must first be established in order to view the alpha responses. You can select a subset of variables to be displayed in the 'Browse' window. Due to technical limitations, the maximum number of variables that can be selected is 450.

The screen below shows the variable names. Optionally, you can click the radio button at the bottom left of the screen and show the numeric variable equivalents for all the variable names.

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DATA > Import – Import data in ASCII string format, ASCII card image format, IBM 360 column binary format, Microtab format or XLS, CSV or DBF formatted data using this feature. If you have the Add-on module to import SPSS or Triple S files, those import options are also possible. Use the browse button to find the data file you wish to import. You might be asked to select the data’s format type. Indicate if the data should be imported into the current study or be used to create a new study. When importing SPSS or Triple S data using this capability, you recommend that you create a new study as part of the process to take advantage of the effort-saving

wizard that walks you through importing both the variable text and the data in one-step. See Appendix 10 for details.

Microtab format – Select when the data file being imported is a data file that is in Microtab format. The file name starts with the letters SPC and is followed by the 5 digit study number. The file extension is dat. Importing data that is in Microtab format will append the data onto the existing data base or overwrite the existing data. Specify if this is additional data or initial data. The latter choice will overwrite any existing data. After you indicate your choice, the file will be imported. Because the data can be appended (additional data), duplicate respondent ID numbers are accepted.

ASCII format - Specifying that the data is in ASCII format (string or card image) will invoke the import wizard. This will cause a grid to be displayed that enables you to view the data. Column numbers are presented at the top of the screen with the data for the first records being displayed. You can move (interchange) columns before importing the data by clicking on the Move columns button (upper right). With a card image, this permits you to interchange data (example) between columns 5 and 6 with the data in columns 79 and 80 in order to have the card number present at the end of the record, a requirement to import card image data into Microtab. See Appendix 1 for a more detailed explanation of the reserved columns. When you are importing ASCII data into Microtab, you can specify how the ASCII symbols “ - “, and “&” should be treated. The defaults are that a “ - “ will be converted to an “X” code and an “&” will be converted to a “Y”code. IBM360 Column Binary format - Specifying that the data to be imported is in IBM360 column binary format will invoke the import wizard and cause a grid to be displayed that permits you to view the data. IBM360 column binary formatted data is in a card image format. Column numbers are presented at the top of the screen with the data for the first records being displayed. You can move (interchange) columns before importing the data by clicking on the Move columns button (upper right). This permits you to interchange data (example) between columns 5 and 6 with the data in columns 79 and 80, in order to have the card number present at the end of the record, a requirement to import data into Microtab. See Appendix 1 for a more detailed explanation of the reserved columns. In all cases, click on whether the data being imported is initial data or additional data. Click on whether duplicate respondent ID numbers should be ignored (not imported), be assigned new record numbers, or overwrite existing respondent data. Click on Import and the data will be read into the Microtab data base. Special Note: If you are importing additional data in a card image format (ASCII card or IBM 360 column binary format) and you indicate that duplicate respondent ID numbers should overwrite existing respondent data, stored data could be corrupted. This is unlikely but could happen if the additional data being added was keypunched manually and a respondent’s ID number was incorrectly entered. We recommend that you backup your data prior to importing additional records.

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Excel (*.xls), CSV and DBF formats – All Editions of Microtab allow you to import xls, csv and dbf formatted data. For a CSV and DBF file, each field is considered a variable, the name of the variable being the name of the field in the csv or dbf file. For an XLS file, each column containing some data is considered a variable, the name of the variable being the value in the first row of the column. See two alternative ways to import an Excel file in Appendix 9. When importing from Excel, the variable type will always default to quantity, avoiding flags that indicate the imported codes, when converted to Microtab, are dissimilar. With this modification to the Excel import routine, the numeric data is always imported as it is presented in Excel. Office 2007 was enhanced by Microsoft so that a user could have more than 256 columns in an Excel sheet, which would seem to be a boon to market researchers who use Excel for data entry. Unfortunately, Microsoft Corporation still limits developers (who have to use Microsoft’s import dll), to importing only 255 columns from an Excel sheet. Out of necessity, Microtab Version 7 has added the capability to import a CSV file of any length to get around this limitation set by Microsoft. Save the Excel file in CSV format and you can then read the CSV file into Microtab, regardless of length. SPSS and Triple S formats – If you have the SPSS Add-on module, you can import the data, variable names, question text, text of the answers to the questions and the data easily into any release of Microtab (2003 or later). Please see Appendix 10 for technical detail regarding these two formats. Because both formats enable you to import the variable names, question text and text of the answers to the questions in addition to the data, we recommend you do not initialize a new study prior to engaging this function. As part of the import routine you can easily create a new study by clicking the Create a new study button. The size of the study (number of cards) will automatically be determined for you by the program. See Appendices 10 and 11 and Study > Variables. When importing data from SPSS/TripleS/Excel formats, Microtab controls the maximum respondent ID number that can be created as a result of the import. There are two scenarios.

• The user selects a variable as the source for the respondent ID. The data is scanned in order to determine whether each to-be respondent ID fits in the number of Microtab columns allocated for the respondent ID. If not, the user is advised to either allocate more Microtab columns for the ID or to choose another variable as the source for the respondent ID;

• If the user specifies a starting value for automatic generation of the respondent IDs, the program checks whether during the import the number of digits required for the generated respondent IDs exceeds the number of columns allocated for the respondent ID. If so, the user is advised to either decrease the starting value or to allocate more columns for the respondent ID.

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When importing SPSS/Triple S files, if the punches/codes to be created in Microtab are not equal to the original SPSS/Triple S codes, a symbol is shown during import step 2. Also, a log entry is created [for that variable] if the user proceeds without

changes. This will be displayed if the imported variable has at least one code outside the 1-12 range (e.g. 99). If the codes to be imported are (example) 1–20 the first 12 codes go in (example) column 105 as punches 1 – 0, X & Y. The additional codes (13 – 20) will go into column 106 as punches 1 – 8. Another case could be three codes: 1, 2 and 99. The program allocates these as code 1 = punch 1, code 2 = punch 2 and code 99 becomes punch 3. These changes (punches compared to codes) would display a symbol next to the variable name and would be shown in the log as well.

Variable Names > Import – After importing the variable names from SPSS or Triple S formatted files, you can view the names in the library by clicking on the V… icon. A new column (unlabeled codes) has been added to the ‘variables’ screen showing a flag for each variable having at least one code that contains the text [added by Microtab import wizard]. When printing variables you can elect to print only ‘codes without labels’ variables. This is an easy way to correct the codes before they are used to create tables or you can use this to generate a printed list of variables that will require editing in the Microtab table manager module. An improvement was made to the ‘Print variables’ functionality so that you can print selected variables. Use the Ctrl and left-click to highlight one variable (or non-contiguous variables) or use Shift and left-click to highlight a block or variables.

DATA > Export – With all Microtab Editions, you are offered options to export data to Microtab format, ASCII string format, ASCII card image format, comma delimited and IBM 360 column binary format. If you have purchased the SPSS Add-on Module, you will also be able to export to SPSS or Triple S formats.

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IBM 360 column binary/Microtab formats – Both of these options work with X and Y punches and also allow you to qualify or filter which records you would like to export. IBM 360 column binary format (not Microtab format) allows you to export specific cards. You can export specific cards and have the data maintain their original card numbers or be renumbered starting with card one.

Microtab format - Use the browse button to find the folder to hold the exported data and then specify the name for the exported data file. Select Microtab format for the exported file. Exporting data to Microtab format copies the spc file of the active study to a file name you specify. ASCII string/card image formats – Both ASCII export options offer you prompts to change the defaults for exporting X and Y punches. The defaults are set so that an “X” will be converted to a “-“ symbol and “Y” punches will be converted to the “&” symbol. You can easily change these. You can also indicate if you want to qualify (filter) the specific records to be exported.

If you export the data in ASCII card image, you can export specific cards and have the data maintain their original card numbers or be renumbered starting with card one. Comma delimited format - When choosing this format, you must establish a file to define the fields or columns to export. To do this, click the ellipse button next to the file number field.

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After clicking the button, you are presented with a field definition window. Click the New button to create a new file. Type in a description and then enter the number of fields to be converted. The number of fields can vary according to the study and according to your needs. You can export all fields or just specific ones. To specify all fields, you will specify the number of fields and enter the Microtab column numbers. You can enter up to 999 fields. Each field will represent the answer data from the survey that you wish to export. The exported data is usually destined for an Excel spreadsheet and each field you specify will appear in one Excel column. Pressing the tab key will take you to the area where you enter the column numbers. Special Note: If you wish to export data stored in Microtab as multiple punched data into ASCII string, ASCII card image, dbf or comma delimited format, you will first need to spread the data. See Columns > Spread data on page 54.

For each single column answer to be exported, type in the appropriate three-digit column number as both the starting and ending column number. In the instances of fields or answers that span more than one column, such as respondent ID numbers or value fields such as dollar amounts, you enter the starting and ending column numbers. Use the arrow keys to move within the grid. SPSS Add-on Module for the Professional Edition - With this module you can export the variable names you created plus the question and answer text and the data to SPSS and/or Triple S format files.

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Create the variable names from tables by accessing Tables>Regular or Tables>Value. The variable names that are created automatically by Microtab can begin with either the letter V (for value tables) or the letter R (for regular tables) followed by the table’s reference number. This automatic assignment of variable names occurs if you enter your tables and do NOT enter variable names as part of the process; instead just creating variables from the table routine. See figure below.

You can override the program’s assignment of variable names by entering your own (a more descriptive name) variable name during the process of setting up your tables. You can also edit the variable names by accessing Study>Variables or clicking on the V icon. A variable name can be up to 64 characters long. We recommend limiting variable names to eight characters for compatibility with older versions of SPSS. Duplicate variable names are not allowed.

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If you are exporting the data in SPSS or Triple S format, you can change the defaults for exporting X and Y punches. The defaults are that an “X“ will be converted to a “-” symbol and an “Y” will be converted to a “&” symbol. You might want to change multiple coded variables to single code fields by spreading data. As part of the spread data function you can elect not to use the X and Y codes in the spread data. See Columns > Spread data for information on this capability. If you have defined the variables with multiple as the variable type, you will not have to spread the data. The SPSS export module will automatically create the appropriate fields in the exported file.

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COLUMNS COLUMNS > This selection from the toolbar provides you with the most extensive

combination of inspecting, creating, cleaning, and copying routines to be found in any tabulation software. The range of tools provided gives you the ability to ensure the highest data quality. You can check the data’s integrity (condition checking), create new variables (recode), machine clean data, and copy data to new locations. You can spread data so that data in multiple punched columns is stored in new locations as single punch data, which is acceptable as ASCII data.

COLUMNS > Condition checking > Skip patterns – This function allows you to

generate a listing of respondents who do not follow a user defined skip pattern. This capability allows you to confirm data cleanliness in situations where if a person said yes to one question they should have answered the next question. Likewise, if they answered no to the first question, they should not have answered the following question. You can specify each column to be checked separately or you can specify a range of columns. When specifying the columns to be checked, separate individual column numbers with commas. A file is created and stored to perform this checking. Fill in the description area in case you have to go back at a later time to perform the checking again.

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Example: This module works on the premise that if one punch exists in a particular column, then in another column there will have to be a blank or there will have to be a punch.

Suppose column 116 held answers to this question "Have you ever been married?" with a 1 for "Yes" and a 2 for "No". Next, column 117 holds codes/punches for the question "How many years were you married?" Anyone with a code of 116-1 should have a code in column 117, while anyone with a punch of 116-2 should be blank (no codes) 117. This is the simple skip pattern shown above.

The following screen shows how you setup sub samples. We also use the phrase Set/Edit filter to mean the same thing. The same screen is used repeatedly throughout this software to qualify data (for whatever reason). These screens permit choices regarding the relationship between punches in a column and the relationship between columns. These punch relationships can be Any, All, None and Not All. The relationship between the columns can be And or Or or anything you wish. Examples are: (Column A AND Column B) OR Column C; Column A AND (Column B OR Column C); (Column A OR Column B) AND Column C; and so on.

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Example: If you wish to find a record that has ONLY code 5 in column 165 you would say you want column 165 – ANY – 5 AND column 165 – NONE – 1234 67890XY.

By telling the computer what codes can exist where, and under what conditions,

you can check your data and produce a list of respondents that do not follow the skip pattern.

COLUMNS > Condition checking > Punch presence – This test should be thought of as

an extension of the skip pattern check. Checking for skip patterns is a check based on columns being empty while punch presence/absence is a check based on specific codes not being in a column. This check is actually much more specific in what it requires the computer to search for. In a skip pattern check, the computer checks to see if a specified column had any punches in it, regardless of what the punches are. Here, the computer is searching for specific codes (answers) in specific columns.

You can check to see which specific record represents a no answer situation (no codes present in a column) for a question. You can also check to see which record has a code that (example) is higher than that allowed. You must specify a filter to perform this checking.

A Skip pattern checks columns while punch presence checks for specific codes being present or absent. The code/punch presence/absence routine is used more often than any other checking routine. It is not necessary to save the created punch presence/absence file before checking the database. You are required to save a created checking file for all of the other checking routines.

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Example: Suppose column 132 on your questionnaire looked like this: Question 18 - What kinds of pets do you own? 132 - 1 Dog - 2 Cat - 3 Bird - 4 Fish Later in the questionnaire is column 158 which looks like this: Question 26 - Which Acme pet products do you buy regularly? 158 - 1 Acme Dog Biscuits - 2 Acme Kitty Litter - 3 Acme Parakeet Treat - 4 Acme Fish Food

Suppose a dog owner listed himself as someone who bought fish food regularly. You would not want such inconsistencies to appear in your final tables. To test for this, the skip pattern check will not work because someone certainly might or might not have punches in both 132 and 158. Here, you would need to check for a more specific pattern, such as people who did NOT answer 132-2, 3 and 4 but did answer 158-2, 3, or 4. In this case you need to use the code/punch presence/absence check. Notice that now the relationship between punches becomes very important.

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COLUMNS > Condition checking > Punch distribution – Certain conditions can exist in a questionnaire where you might have a long list of perhaps 50 items. The list would span multiple columns. Perhaps the respondent is asked, “Which one have you purchased in the past year?”. Multiple responses are not allowed (Which one)

and you need to check the data to insure no respondents gave more than one answer. Likewise, perhaps you have a question where the respondent was instructed to choose up to three answers. This routine shows the number of respondents that gave one answer, two answers, three answers, etc. A frequency distribution is presented and you can see how many records, if any, have more than one (or X) number of answers.

COLUMNS > Condition checking > Punch overflow – Certain conditions can exist in a

questionnaire where you might have a long list of perhaps 50 items. The list would span multiple columns. Perhaps the respondent is asked, “Which three are your favorites?”. Multiple responses are allowed but you need to check the data to insure no respondents gave more than three (or some other number of) answers. This routine will list the records with the record and respondent numbers of those who exceed a user specified number. You would then access Data > Edit to clean the data.

The report generated when you click on the check button is shown on the next page.

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The punch overflow report differs from the punch distribution report because the punch distribution report shows how many respondents gave each number of answers, whereas the punch overflow report shows individual respondent detail for everyone who exceeds the given number of responses.

COLUMNS > Condition checking > Multiple punches – If a specific column has been specified as a single punch column (example: a yes/no question) and contains multiple punches, this routine enables you to easily find those records that have multiple punches. Enter the individual columns to be checked separated by commas or specify a range of columns to be checked with the highest and lowest column numbers in the range separated by a dash. No spaces are allowed.

Though this function may be used on any column, its true purpose is to check the integrity of single-punch columns. If you spec'd your study correctly and inputted data using the numeric keypad, then you cannot have any multiple-punches in single-punch columns. However, there are circumstances when a multiple-punch error might occur, as in a study that was incorrectly spec'd. If you notice a single-punch column where SIGMA (number of punches) and rejects added together exceed the number of records, you will want to perform this function and get a listing of respondents who have multiple punches in that column. This function is especially useful to check the integrity of data that has been imported from another program.

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COLUMNS > Condition checking > Column addition – If you have a ranking question (1st thru 5th choice), you could use this capability to insure that within the range of columns no record holds data with (example) two first choices. The logic is that 1+2+3+4+5 equals 15 and that when you add the five columns together, the total must add to 15. Exceptions are printed. If you had a 5 point ranking scale with the answers allowed being 1, 2, 3, 4, and 5 (a total of 15), an exception would NOT be printed for the responses 2, 2, 5, 4, 2 as they still add to 15.

Example: Suppose you have a question in which you are ranking four products from first choice (code1) to last choice (code 4). Each product has its own column (108, 109, 110, 111) that will get one of the four codes, either a 1, 2, 3, or 4. Since the product is being ranked, the codes 1-4 can only appear once among the four columns (no two products could be ranked a "3", for instance). Therefore, if you added the punches together in those four columns, the sum must equal 10 (that is, 1 + 2 + 3 + 4 = 10). You would fill in the screen as shown above. It is possible to miss a record if the answers entered were (example) 2,3,2,3 as those numbers add to 10. The computer can only check to see if the total adds to 10. This is the logic behind and the need for the column addition check. Since you are given the ability to base the addition check on a sub-sample, you can use this function to determine if a specified sub-sample adds up to a specific total (such as the total number of people in a household).

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COLUMNS > Condition checking > Value field addition – Similar to column addition, this routine checks that certain value fields, when added together, add to a specified number. You could use this routine to check the resulting stored data for a constant sum chip allocation question.

There are at least two instances where value field addition is a useful check. The first is when value fields are being used to hold percentages. The fields may be checked to see if their sum equals 100 (%). Another instance could be when you are using a "constant sum chip allocation" series of questions. In this case, you might tell the respondent he had 50 opportunities to shop at a grocery store, and you wanted to know how many times he would purchase each of a list of products. Each product would have a value field assigned to it. When the respondent is finished, the value fields would have to add to 50. The method of checking value fields is almost identical to that of regular column addition.

Example: The above screen demonstrates the check for value field addition that would apply for a question such as: Q5. – Please indicate what percentage of your bar soap purchases are allocated to each of the below brands.

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The choices are Brand A, B, C, D, E, F, G, and All Others (The total must add to 100%).

COLUMNS > Condition checking > Against study specs – This routine will check all of your stored data against questionnaire specifications you entered for the study. If you created the study and used Create default study specifications, this checking capability doesn’t apply as all data will pass inspection.

Example: Suppose you have generated top-line data for your client based on a partial shipment of questionnaires from the field. The data was entered into the computer through some method other than manual data entry (numeric keypad), and therefore the punches may not correspond to the study spec's. Before giving your client the data, you might check the data to be sure it is "clean" by using this function to reveal inconsistencies between the inputted data and the specifications listed. Later, when the rest of the data comes in from the field, you might want to check it as well

COLUMNS > Recode > Data – All recode capabilities allow you to create new variables

based on specified conditions. Recoding data enables you to create a new variable based on specific punches being present or absent in specified columns. The recode function allows you to create a column/punch combination that represents an unlimited number of qualifiers. Recodes allow you to create a single punch for a net of open-ended responses that can represent many punches from an unlimited number of columns.

Example: If many records show that an interviewer did not indicate a no answer (punch Y) on the questionnaire (a valid response) and instead left the question empty, you could use this capability to create the no answer punch for anyone who did not have any punches in the column. The below screen shows how to create a no answer punch (141-Y) for anyone who left column 141 blank.

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Example: As an example, imagine you are recording positive and negative reactions to a television commercial. In column 145, 146, 147 and 148, you have punches to record different positive comments. In addition to listing each comment in a stub line, you wish to have a stub that reads, "NET - POSITIVE". In this stub, you want to show the number of respondents with positive comments. A stub on a table can be represented by up to three columns. Here, we wish to have one stub represent four columns. Somehow, the four columns must be “compressed” to show as a stub on the table.

First, you must find an empty column, using marginals to be sure it’s empty. Next

you would run a recode. This would require two steps as four columns are being examined. Both step one and two are shown below. They are part of the same instruction file.

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Finally, you tell the computer to use the column/punch 175-1 to represent the "POSITIVE - NET" stub. By running the recode, you are telling the computer to record one punch in your new column every time it finds an appropriate punch in any of the four columns you have listed. This creates a new variable. The same process could be used to create a stub called "NEGATIVE - NET" using column/punch 175-2. All of the negative comments are recoded to be 175-2. Recodes can get as complex as you wish. You could create a stub that is made up of three codes from four different columns, ten codes from six different columns, etc, etc.

COLUMNS > Recode > Punch distribution – (See also Columns > Condition checking

> Punch distribution). Certain conditions can exist in a questionnaire where you might have a long list of perhaps 50 items. The list could span multiple columns. Perhaps the respondent is asked, “Which have you purchased in the past year?”. Multiple responses are allowed and you need to create a variable so that every respondent that gave one answer (across all specified columns) has the number one recorded in a new variable; those that gave two responses would have a two recorded in this new variable, and so on. This routine creates a numeric in the new variable that represents one answer, two answers, three answers, etc. The numeric created for each record might be used as qualifiers for subsets of the data for further analysis.

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COLUMNS > Recode > Specific numeric values – You can easily create specific

punches based on values stored in a value field. An example would be the use of ‘99’ codes (used by some open-end coding services) to represent answers to an open-ended question. This capability allows you to create new multiple punch data in the record. You would then use this data when setting your table parameters.

These numeric fields are used in regular tables, not value tables, because they do not represent actual values. As a zip code is not interpreted as a value (something you could perform a mathematical function on) but rather is a numeric name for something (in this case, a postal district), 99 codes are numeric names for answers to a question. A two-digit number making up a numeric field means that two columns, not one, are used to represent an answer. Furthermore, a numeric field might have more than two digits, such as a zip code, which has five.

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Example: Assume an open-ended question has been coded with "99 codes." That is, each possible answer has been given a two-digit number (01-99). A single answer, such as a 99 code, that takes more than one column to record is known as a numeric field. A numeric field operates exactly like a value field, but the number recorded is not actually a value, the way 23 years or 10 dollars are considered values. Instead a 99 code is a number that represents an answer, as in the following:

Products purchased during the last two weeks: 01 - Toothpaste 02 - Hand Soap etc, etc, up to... 99 - Dental Floss.

The two-digit code corresponding to the first response has been stored in columns 223-224. The two-digit code corresponding to the second response has been stored in columns 225-226, and so on. The above screen shows how you would convert the 01 in columns 223-224 that represents Toothpaste to be a one punch in column 260; the 02 in columns 223-224 that represents Hand Soap to be a 2 punch in column 260, etc. Similar instructions would be entered for columns 225-226 and all subsequent column pairs allocated to this question. Column 260 would be used in the actual table parameter.

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Example: Suppose you wanted to record zip codes and then use each individual "ZIP

CODE" as a banner point. You could use this feature, as shown above, to convert a certain five-digit zip code, taking up five columns, to one code in one column. Then, this single code/punch and column could be listed in the banner and no further recoding would be necessary.

Using this numeric recode function (as opposed to regular recodes) requires that you have an AND condition between all columns (since the computer looks at the punches in all columns of the field as one number). The only other requirement is that the columns be in consecutive order on one card. Special Note: If you wish to create a table for all zip codes recorded in the data base, an alternative method has been implemented. See the screen shot that follows.

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An auto-fill button has been added to the bottom of the value table stub screen. The button will become available after you have specified the value field source columns for this table. Clicking on this button will populate the table with a stub for each unique value and will use that value as the stub label. Because a value table is currently limited to 999 stubs, you might find it necessary to reduce the size of the value field for zip codes from 5 digits to 3 digits. You might also want to create ranges to represent specific zip code areas. See below for this capability.

COLUMNS > Recode > Numeric ranges – Data stored for certain questions could be

specific in nature, such as zip codes. If you want to group the information for your banners and/or for your tables, you would use this capability. You would specify that any record that falls in the range of 30001 to 30350 should be recoded as a specific code in a designated column. The new variable could then be used for the banner point and/or table.

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Example: For this procedure, we will use as an example zip codes that currently take up five columns. Let's assume those columns are 220 - 224, and now we want to assign the zip codes 10001 through 12999 one column/code, 278-1, which has already been checked and is empty. When we are finished, we want everyone in our study who has a zip code of 10001 through 12999 to be represented by the column/code 278-1; everyone who has a zip code of 13000-14999 to be represented by 278-2, etc. Another situation arises when you need to recode a range of values such as those less than 125 verses those greater than 124 in such a way that you can use the new variables as banner points.

COLUMNS > Recode > Conditional – This routine creates a new variable based on

Boolean logic. Two different variables can be examined (let’s use A and B) and new variables can be created if A>B, A<B or A=B. Also included is the logic ‘not equal to’ and ‘greater then/less than or equal to’.

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The Boolean logic options that are presented are shown below. As with all the instruction screens that are presented in Microtab, multiple instructions can be entered and then executed with one keystroke.

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COLUMNS > Clean –Upon examining the database, you might find that many records contain data they shouldn’t, perhaps due to a programming error in the CATI system used to collect the data. The capability presented here allows you to clean the entire data base as determined by certain conditions and filters. You can clean specific records (by establishing qualifiers) or you can clean given data from every

record in the database. We recommend you back-up your data before engaging this function.

Machine cleaning is useful whenever you have uncommonly dirty data coming from the field or when you are working with mail surveys or self-administered surveys. The feature is much like recoding as far as the instruction file is concerned, but the actual function is the exact opposite from recoding. Here, you are not creating punches but rather removing them. Example: You can clean a continuous series of columns of all punches very easily - as shown above. Here, all data will be removed from column 135 through column 139 (five columns) for any respondents who have a two recorded in column 156.

COLUMNS > Copy – We originally offered the ability to derotate data but removed that

ability when users found it too difficult to understand. With derotation, you interchanged data so that the resulting database was column specific – that is, data in a column pertained to one specific product/advertisement. Using the copy routine, you can copy data to a new location in the database and accomplish the same result. Using the copy routine, the original integrity of the data is not altered.

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Special Note: You might not want to use a column already being used to hold other data. Before you begin the copying process, you will want to be sure you are not accidentally altering data that is already being stored in the destination column. You will want to (usually) begin with empty columns. Use marginals to look at the destination column and make sure it is empty. Do not make the search for empty

columns a difficult one. If you only have ten columns left on the last card of your study and you wish to copy 15 columns, do not spend time trying to squeeze out five extra columns from somewhere else. You have the option of expanding your study and creating new cards.

Copying variables to a new location can be a very powerful feature when the option to base the copy file on a sub-sample is used. As in recoding, you can create a new area of data by using this feature. When you copy variables, you can copy one variable at a time or you can copy multiple consecutive variables (a range of columns) with one instruction. You can quickly and easily separate respondents from each other using this copying function in combination with the qualifier (set filter) routine.

Example: For instance, in a study of potential airline commercials, 150 people are

asked which of three commercials they liked the best. The commercial preference answer is recorded in column 159 as a code 1, 2, or 3. Then, in columns 160 - 175, the respondents answer the same questions about the one commercial that they thought was the best. Then they are asked why they liked it best. Therefore, in columns 160 - 175, you have responses to 3 different commercials. For tabulation purposes you could separate those answers, so you have one set of columns for Commercial A, another for Commercial B, and yet another for Commercial C.

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This can be done by copying the data in columns 160 through 175 based on a sub-sample. You could tell the computer to copy the data in those columns to 16 other empty columns (example 305-320), if a respondent answered "1" in column 159

(your filter column). These 16 new variables now would become the variables dedicated to Commercial A answers. Repeat the same copying procedure two more times, copying data into 16 different empty columns (321-336) for respondents who have a punch of 159-2 (for Commercial B) and into 16 other unique (different) empty columns (337-353) for respondents with a punch of 159-3 (for Commercial C). You have now created 48 new variables (three sets of 16 each), which represent a separation of columns 160 - 175.

COLUMNS > Spread - The necessity to spread data becomes apparent when you want to

make a multiple punched data base available to a system that only works with ASCII (single punch) data. An ASCII file is not able to accurately read data in a column with multiple punches. If a multiple punch is encountered during the conversion, all of that column’s data is ignored for that record and an asterisk is exported to the ASCII database.

Certain situations might arise when you have used an ‘X’ and/or a ‘Y’ code in Microtab. When you export the file for use with another program, you might not want to use the ‘X’ or ‘Y’ code. You can spread the data (even if it’s single response data) and edit the grid so that an ‘X’ code could be spread as a one code in the next column and the ‘Y’ code could be spread as a two code in the column after that.

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X and Y codes – The codes/punches X and Y are inherent to the IBM360 column binary format (80 column card image format). Because the use of this format is not the most widely used data format anymore, we have added the ability to NOT use the X and Y codes for selected functions. The shipping default setting is that X and Y will be used for certain functions. However, you can change the default by going to (on the toolbar) Tools>Options>General and clearing the check box in the lower right hand corner of the screen. If the check box is cleared, the use of X and Y codes will not be utilized for conditional recoding, single data column recoding, and spreading data recoding. The use of X and Y codes will likewise not be allowed when importing SPSS, Triple-S, Excel, DBF, and CSV files. The X and Y radio buttons will either be disabled or the codes to be created (mapped) will not display the X and Y codes.

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Example: Assume you need to spread the data from multiple punched columns into several single coded columns to send data to your client. For instance, if you had column 165 spec'd as multiple punch, with the range of answers being from a 1 punch to a 6 punch, then you could spread that data over six single punch columns. Those six columns could be any empty columns in your study. For convenience sake, it is helpful if you spread the data into six consecutive columns. Using this function, you could copy all the 1 codes in column 165 into the column/punch 171-1, all the 2 codes into 172-2, all the 3 punches into 173-3, etc (assuming columns 171 through 176 were empty). The punches, destination columns and their codes are filled in automatically if you click on AutoFill. Once this process is completed, you can safely convert the data to an ASCII format.

SUMMARY

SUMMARY > The summary routines enable you to view the data for cleaning purposes

and also to generate top-line information for your clients. SUMMARY > Marginals – Marginals are also referred to as ‘hole counts’ and show the

frequencies of codes/punches in columns. Specify the column range to compile, percentaging options, displaying of columns specified as ignored and whether the data should be weighted. All the routines in this section allow filters to be set so the compiled data can be viewed based on a sub-sample of the population. Marginals can be generated without percents or be generated with percents based on the total number of respondents, with percents based on the qualified number of respondents (a sub-sample), or with percents based on the total number of punches (sigma). All marginals are generated with the mean displayed for each column. It is calculated based on the numeric codes.

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Example: You have completed data entry for a study and wish to see what columns might be useful as banner points. By generating marginals, you will see the distribution of the punches residing in each column of the study or in a selected set of columns. By default, when you enter the marginals screen, the first and last columns of your data are already inserted. Clicking on the Generate button will give you a quick display of all the frequencies for your data, as shown below. If you were generating top-line information, you could have percentages printed along with the frequency counts. Another use for this function would be if you

were interested in knowing which columns were void of codes and could be used for recodes or for other purposes.

Marginals can be generated to show a variety of percentaging options and the data can also be weighted. By weighting the data and generating marginals, you can check to be sure that the target weights were achieved. You can generate the marginals for the entire database or you can select just certain columns to view.

SUMMARY > Arrays – While marginals show frequencies for specific codes/punches in

columns, arrays show a distribution of values in a continuing series of columns. Typically, arrays are used to display unique values for a percentage question or perhaps a constant sum chip allocation type of question. Several display options are provided and basic statistics are also presented. Array generation is helpful in determining ranges for value table stubs. Weighting and filtering are also available for arrays.

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Example: A typical value field might be:

How much would you pay for this item in a retail store? DOLLARS CENTS

____ ____ ____ ____ 121 122 123 124

...where columns 121 through 124 would be spec'd as value columns. The actual amount given to the interviewer by the respondent would be recorded and would enable you to generate exact means during report compilation. At some point you will want to look at the frequency of the dollar and cent amounts to determine how to organize your value stubs. This can be done using arrays as shown above.

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The only factor you must consider when generating arrays is how the data was entered into the value fields during data entry. Most situations are fairly straightforward, requiring a valid punch of 1 through 0. However, in some cases the respondent may refuse to answer a question. Perhaps he says he doesn't have an answer. In that case, a "Y" punch should be entered. In another case, you might have assigned two columns to record a percentage without anticipating that a respondent might give an answer of 100 percent. You would be unable to record the number "100" in two columns. Instead, you should enter an "X" in one of the

value columns. This "X" can be entered in either column and can be assigned a value later when you generate the array.

Finally, there is a good possibility that the question you are asking is part of a skip pattern, and a group of respondents might not be asked the question at all. In this case, the value columns making up the field would be left blank for those respondents.

To summarize: 1234567890 = Valid punches Blank = Skipped question (Respondent was not asked) Y = Refused/Don't Know (Respondent was asked) X = User-assigned high value

Special Note: A value field can be up to twelve columns in length. A value field cannot start on one card and end on another.

SUMMARY > One by Ones – One by Ones are rudimentary cross tabs that use one

column for the banner (column headings) and another column for the rows (stubs). The banner and stubs are not labeled other than to show the codes/punches within the chosen column. Percentaging, weighting and filtering options are included.

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Example: In a particular study, column 106 records "Purchase Intent" while column 110 records "Past Product Usage". Using this function as shown above, you could specify that you wanted to produce a One By One table that had each punch in column 106 as a banner point (across the top) and each punch in column 110 as a stub (down the side). In effect, you would be cross tabbing product usage against purchase intent. Using the sub-sample option, you could limit the respondents included in the One By One table to female heads of households who are over thirty-five and have low incomes (a three-column qualifier).

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SUMMARY > Record Numbers – Because it might be necessary to see if all the data

inputted was accepted properly by the program, it is possible to list the recorded data by record number or by respondent ID number. You can also check for respondent numbers outside a specified range, missing respondent ID numbers within a range and duplicate respondent ID numbers.

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Example: You wish to reinstate a deleted respondent but you have forgotten his record number. As previously mentioned, a negative one (-1) is assigned as the respondent ID number for all deleted respondents. With the list generated by this function, you can look for the respondents with a -1 respondent ID number and then use the corresponding record number to reinstate specific records into the database.

In the above example, records 35 through 53 can be reinstated into the database by changing their respondent numbers from negative one (-1) to a positive number. You would assign the deleted record a respondent number greater than zero.

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WEIGHTING WEIGHTING > To assign weights so that data recorded for the current study can be

compared to data generated in a prior study. Weighting is used for increasing or decreasing cell sizes to achieve equality or to match the demographic profile of a previous study or a particular forecasting scenario. Two different weighting schemes are available. You have the option of weighting each respondent's record based on a unique computer generated number recorded in a value field as part of that respondent's data. Or, you can develop weights yourself and have them applied during compilation based on specific columns and punches.

You do not physically change the data in your study when you weight it. Even after establishing a weighting file, a set of marginals would still be the same if, when generated, you indicated the data should not be weighted. A weighted set of marginals would reflect the change. Remember, you are not weighting banner points or stub lines. Instead, you are weighting respondents. You are telling the computer to change how a respondent is tallied, from 1.000 to something greater than (example: 1.243) or less than (example: .7378) 1.000.

WEIGHTING > Sample Balancing – Sample balancing is used to create a unique

number recorded in a value field as part of that respondent's data that represents how that respondent is to be weighted.

Example: - Preparing for data weighting requires you to do two things. First you must determine your target values. Then you must determine if you want the size of your total sample to stay the same, increase or decrease.

Special Note: While a respondent's data can not be weighted twice in one weighting file, the Sample balancing routine utilizes iterations so that as one variable is weighted up (example) and therefore everything else in that record increases, a second pass through the data base could weight the record down (example) based on other criteria. Continuous passes through the data base (iterations) will develop individual weights for each record so as to achieve your requested sample composition.

You can look at a cell in a table and know what respondents you want weighted, but the computer can only look at columns and codes/punches. With this routine, you could say you wanted males to total 170 and the instruction would read (example) column 105 punch 1 target is 170. If you wanted females to equal 140, that instruction would read column 105 punch 2 target 140. Further, if you want the age representation to be equal over/under 24, you would say column (example) 147 punch 1 target 155 and column 147 punch 2 target 155.

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Special Note: Because a respondents’ data cannot be weighted twice, you can achieve desired targets for cells but in the above example you will not necessarily have equal over and under 24 age representation by sex. To achieve that refer to page 65 regarding weighting files.

Special Note: The summation of both independent targets must be the same.

You will be advised if the sum of the targets for the independent categories do not add up to the same number (target total number of respondents). If this happens, go back and correct your work. You will not be able to proceed unless the target totals are the same. Assuming your target totals are the same, you will indicate the starting and the ending column numbers for the field to hold the weight. You can use up to 12 columns (one variable with twelve as it’s width) to hold the weight. The decimal can be from one to seven places from the right. You are asked, “What is the starting column for this value field ? ____.” You must enter a starting column number that can go forward without crossing cards. You can print your instructions to check your work. When you are satisfied that your instructions are accurate, click on Calculate weights and the program will perform the necessary number of iterations. The resulting individual weights will be stored as part of each respondent’s data in the designated value field. To complete the process, you access: WEIGHTING > Weighting files. Open a new file and click on Weight from a value field. Enter the starting and ending column numbers for the value field and then indicate how many places from the right the decimal place appears.

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Special Note: The weighting file number created with WEIGHTING/Weighting files is the number you will specify when you want to weight data. In all instances, in order to weight data, you must create a weighting file.

WEIGHTING > Weighting files – This is where the user indicates whether the weights should be accessed from a value field (see Sample Balancing above) or whether the weights are to be user defined. A weight file must be created whether the weights are calculated by the computer (sample balancing) or if the weights are calculated manually. If the weights are created manually, this procedure is the only routine that will be accessed. We recommend that, when possible, you use Sampling balancing to determine the weighting factors as that is easier. Example > Creating your own weights: This exercise is necessary if you want to create nested weights. In a particular study, you have a sample of 200 people. Ideally, you want 100 males and 100 females. Furthermore, you would like to work in an age factor. Of the 100 males, you want 50 to be under 35 years of age, and 50 to be over 35. You wish to have the same division for the female respondents. In your study, sex is recorded in column 107, and age (over/under 35) is recorded in column 110. By generating a One By One table with column 107 as the banner and column 110 as the stub, you see that your actual data is as follows:

Respondent Actual Females/Under 35 50 Females/35 & over 60 Males/Under 35 55 Males/35 & over 35

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Do not weight the 110 and 90 respondents representing the sex totals nor should you weight the 105 and 95 respondents representing the age totals. Instead, work from the inside-out. Use the recode function to create a unique column and punch for each of your cells. You see that 50 respondents are needed in each of the four inner cells. Therefore, concentrate on dividing the target data by the actual data for the inner cells. You divide 50 by 50, 50 by 55, 50 by 60, and 50 by 35 . This gives us the following information:

Respondents Target/Actual Weight New Variable Females/Under 35 50/50 = 1.000000 171-1 Females/35 & over 50/60 = .833333 171-2 Males/Under 35 50/55 = .909091 171-3 Males/35 & over 50/35 = 1.42857 171-4

To determine what weight to assign, you divide the target number of respondents for a cell by the actual number of respondents in that cell. In all cases, before you begin to calculate the weights, you MUST know what you want your cell target values to be. We suggest that you draw a picture of how your table looks before weighting (your actual values) and then another picture of how you want the table to look after weighting (your target values). Remember that you can see the actual values by running a One by One table.

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Calculating your own weights: When looking at data to be weighted, remember that the individual cells making up the Total cells MUST add correctly if the Totals are to work out. Therefore, you would not look at the Total cells, figure out your targets, and then let the inner cells "work themselves out". Instead, you MUST establish values for the inner cells.

Special Note: When you are developing the weights, remember that a respondent's data can not be weighted twice in one weighting file. Determining Actual/Target Values and Calculating Weights

In the example above, notice that the values for Female/Under 35 are already

correct. Weighting those respondents by 1.0000 will not change anything and technically they do not have to be weighted at all. However, for the sake of example, we will include this 1.0000 weight as a contrast to the other weights. We now know by how much the respondents in each cell must be weighted. That is, we are ready to tell the computer to multiply the above groups of respondents by the weight values we have calculated. We now need to identify the above groups for the computer.

Recoding for a Weight File - (Creating a new variable)

We can look at a cell in a table and know what respondents we want weighted, but

the computer can only look at columns and punches. For instance, we could identify Males/35 & Over for the computer by saying they were all respondents with a punch of 107-2 AND 110-1. Furthermore, we can say that we want to weight any respondent with a 107-2 (males) AND a 110-2 (35+) by a factor of 1.4286.

Special Note: When assigning (calculating) your own weights, you must assign one column and one punch for each weight value assigned. Thus, you have to take someone represented by two columns/punches (male and under 35) and represent them by only one column and one punch in a column. This is done by creating a new variable through recoding. Create the new variables and then fill in the grid that’s presented with the columns/punches and weights.

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You would set the instruction so that those records with a 171-4 code would be weighted to 1.4286

BANNERS BANNERS > Here you designate the column/punches that the computer will use to qualify

respondents to be counted in each banner point or column heading. Also, you detail the desired layout for the final report, the labels to appear over the banner points, the data format and any statistical testing you want performed on the compiled data.

BANNERS > Banner & Page Layout – This allows you to detail the physical appearance

of the tables to be generated, by supplying information on the number of banner points desired, the amount of space required for labeling the banner points (width & height), the stub line (row) labeling length, the print orientation (portrait vs. landscape) and font size.

Copying an existing banner: If this layout is for a second banner (or third or fourth...) but all or most of the information for this file is identical to banner “01”, you may open file "01" and all the information from file 01 will appear on the screen. You would then edit this banner (plus the description) and save it. When prompted, indicate that you want to save the information to a new banner number.

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Special Note: When setting up or copying an existing banner, do not change the stub line length from that used for “banner 01” as this will, perhaps, cause a truncation of the text you have entered for the row labels (stubs).

Special Note: Different printers restrict the available print area regarding left, right, top and bottom margins. Appendix 3 details the number of characters that can be printed on a line according to printer type based on information that has been gathered as of this manual’s date.

BANNERS > Labeling – Depending on the instructions entered during Banner & Page

Layout, this screen shows the labeling area for a banner as well as buttons under each banner point that, when clicked, allow you to easily enter the qualifications for each banner point. Clicking both items in Quick view displays help and information screens that facilitate completing the labeling process. When you click on Quick view, you can view your banner point qualifiers for each banner point entered. This is an easy way to check for column and punch errors. Quick view also guides you through the keyboard shortcuts for your banner annotation.

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To enter a banner label, highlight the area where you want the label to appear and double click. A box will appear marked in the corners with solid blocks. You can expand this block, perhaps to bridge two banner points, by holding down the <Shift> key and using the left or right arrows keys. After the box is the desired

size, press <Enter> and type your label. Press <Enter> when it is complete. Use the arrow keys to move to the next label position. The Quick view of keyboard shortcuts will assist you in this function.

BANNERS > Qualifiers - You qualify respondents that should show under each specific

banner point by using the sub-sample routine detailed in Appendix 2. The qualifications between punches in a column can be and/or/none/not all. The relationship between columns can be an AND or an OR condition. If you previously created variables, you can use variable names instead of columns and punches to designate the qualifiers.

SPECIAL NOTE: If you do not specify a qualifier for a banner point, that banner point

label will be printed but without frequencies and percentages. Additional boxes are presented under the qualifier buttons. These boxes are labeled

‘shade’ and by clicking one of the radio buttons next to Quick View (points OR spaces) you can have specific banner point(s) shaded OR you can have specific space(s) between the banner points shaded. You cannot combine both forms of shading on one banner.

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BANNERS > Header & Footer - This refers to the desired print location for the descriptive header that will appear on every table. It is up to you to decide where you want this information to appear on the tables. If you chose to print a header on each table, you will now be able to complete an area reserved for the information you want to appear in your header. You may input up to four lines, with sixty (60) characters on each line. Ctrl + C acts as a toggle and permits centering of the header information. A typical header includes company name, study name, the project number, and the date. A mock-up of how the table will appear is displayed

on the right side of this screen. The <insert> key acts as a toggle between overtype and insert. The default is insert.

You have the option when entering Table Parameters (stubs) to enter a footnote for a table. Here, you are asked where the footnote should appear. This prompt also offers an easy way to suppress footnote printing without changing every table parameter and erasing the actual footnotes. If you specify Omit them, footnotes will not be printed, even though you might have entered them in the table parameter section. If a particular table is more than one page in length, the question (or the table label) will appear on every page of the table, but the footnote will only appear at the bottom of the last page. As part of this routine, if you want to perform stat testing on the tables, you can indicate where the identifying banner letters should appear – either above a banner point, at the bottom of a banner column (after the frequency count) or in both areas.

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BANNERS > Data Format - Three lines are available to display data for every banner point/stub line (column/row) intersection. This allows you room to display the raw data count along with two percentages. Of course, you might opt to show only the raw data. Indicate if percentages should be displayed as integers or carried to one decimal place. Also, indicate if percentages should be displayed with a percentage sign and then specify if zero cell counts should be shown as a zero, a dash or left blank. If you elect to print vertical percentages, you can also print a horizontal index for each cell. Inversely, if you elect to print horizontal percents, you can then

print a vertical index. You also specify here if you want “100%” to print as part of the Total Respondent stub line.

We added a “switch” in our XP 2004 release that allows you, with one click, to print a sigma count at the bottom of every table. You specify how you want this row to be labeled by entering that information into the box provided. This is an easy way to check your data before sending the tables to your client. To generate the tables without this information, click the box again to turn off the feature.

BANNERS > Stat Parameters – Statistical testing that is conducted during table

production is included with the Professional Edition. The questions regarding stat testing relate to the type of testing you desire and banner point identification only.

You give instructions in the table parameter section regarding starting and ending stubs for testing. The testing that is offered here is independent in nature; i.e., the banner points to be tested must be mutually exclusive for the test results to be accurate (i.e., males vs. females or one age grouping compared to another).

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The total banner point cannot be used during stat testing. On one hand, in the "Banner & Page layout" screen, the "Print the TOTAL banner point" checkbox cannot be checked when banner point #1 was specified as a "left point" in statistics. In such case, when a user checks the "Print the TOTAL banner point" checkbox and then clicks "OK", she receives the following message: ""Print the TOTAL banner point" cannot be checked as long as banner point #1 is included as the left banner point in statistical testing. If the TOTAL banner point is required to be printed, please remove the banner point #1 from statistics.". On the other hand, in the "Statistical testing parameters" screen, when the user specifies the banner point #1 as "left point" in statistics, while "Print the TOTAL banner point" was checked,

the following message will display when clicking "OK": "Banner point #1 is not allowed in block <block number> when "Print the TOTAL banner point" is checked." Please see Appendices 5A, 5B, and 5C for descriptions of the three tests that are offered;

Chi-square testing, t-Tests and Z-Tests

After you have set the pairs to be tested for one of the routines, you can copy the pairs from the Z-Test area to the t-Test area (or vice versa) by clicking the copy button. You cannot copy the Chi-square blocks to either the t-test or Z-test routines or vice versa.

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BANNERS > Print - Produce print-outs of the banner specifications, the banner annotation and the stat testing instructions for checking purposes.

TABLES TABLES – Here you specify the questions and their answers, mean weighting/rank order

instructions as well as other question parameter information necessary for producing tables. The parameters for each kind of table are created by choosing a separate function (tab) from this menu. Thus, one file is created to hold all the Regular tables, another file holds the Value tables, and another holds the Volume tables. Mean summary tables and Advanced tables are also accessed by separate tabs. When you get to the point where you will be generating your report, you can place your tables in the desired printing order and the table numbering will automatically be adjusted for you.

Stub (row) label length – With most printers the optimal stub label length is 19 characters per line. This length allows for the generation of a report with 22 banner points on most printers. With the ability to create tables automatically using text files generated by SPSS and Triple-S files, 19 characters are sometimes insufficient. With Version 6, a user had to specify the length that was desired before the first table was created. Over-riding the warning to specify a stub line length caused the program to assign a default row length for labeling of 15 characters. With Version 7 we added the ability (under <Tools><Options><Reports>) to set the default amount of space available (length per line) to any number between 15 and 30. This number defaults with the shipping version to 19 but it can be modified (under tools) to always present a different length. The default set by the user can always be over-ridden for selected banners.

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Presented at the top of the table screen are tabs that enable you to select either Regular tables, Value tables, Mean Summary tables, Volume tables and Advanced tables. The default screen is regular tables. At the bottom of the screen are buttons that allow you to create a new table, copy an existing table, edit the table, create variables, print the table and delete a table. You can highlight multiple tables to perform all the functions except New, Copy and Edit.

TABLES > Regular: You would use regular tables to produce a report based on

frequency counts stored in either single or multiple punch columns. Punches stored in value columns are reported in either value tables or volume tables. Click on New to start your regular tables.

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TABLES > Regular > General - This is where you enter the question (or table label) that will appear at the top of this table. The question’s printed position on the table (left-justified, centered, etc.) is determined by your banner and page layout. You can also enter a footnote on this screen if so desired. Specify if you want to suppress

stub lines based on frequency or percentages. Click on the stubs <tab> at the top to continue.

An area is provided where you can enter a variable name for this question. This variable name would then be used if you were creating variables (question and answer codes) for use when exporting the question to SPSS or Triple S format. If this field is not filled in and you create an SPSS formatted file the variable name assigned will be the reference number – R01 in this example.

TABLES > Regular > Stubs – The default first stub is labeled Total Respondents. You

can edit the label by double clicking on the stub or you can type a label for the first stub from scratch by removing the check mark in the “Show Total respondent count in the first stub” box.

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You can also change the default stub screen by accessing Tools>Options>Template. You can set the opening stub screen to be whatever you want. The ‘new’ default screen will then be used/displayed whenever you enter the table manager routine. Example: Without using the new default stub screen you can still change how the table will look. If you want the first stub to show those who answered the question, you would remove the check mark for the “Show Total Respondent….” check box. Type the label you wish to have appear and then click on the radio button next to “answered”. A frequency count representing the total number of respondents who are counted in all the stubs, regardless of column or variable, can be computed during the report generation and used for this stub.

TABLES > Regular > Stubs > Append – This is where you add the answers to the question you entered in the “General Screen”. You may enter any number from 1 to 999. Remember that the first stub line is usually labeled "TOTAL RESPONDENTS" and that this stub does not need to be appended. Therefore, if you have 10 actual answers to a question, you should say you want 10 stubs. If you choose to have a stub for NO ANSWERS, NETS, or SUB-NETS, each of these should be counted as one additional stub. You can indicate that all the stubs on the table come from the same column. If the table contains a long list of answers (more than fit in one column), you can still use this function and the column numbers and punches will be filled in by the computer. The program assumes that consecutive columns are utilized.

Each blank entry for a stub has a place for three lines of text (where you enter the answer that the stub represents) and a qualifier button you click to access a window specifying the source column(s) and punch(s) for each stub. (The first stub will have a space for column(s) and punch(s) only if you specified that it should not show a total respondent count).

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If you indicated that all of the stubs came from one column, you will see the column number you inputted already entered in every stub for you. You may begin

entering actual text for each stub. You may use 1, 2, or all 3 lines. Each stub line is as long as you indicated in the Banner and page layout for banner 01, or as you set the length under <Tools><Options><Reports>). You can set the default amount of space available (length) to be any length between 15 and 30.

Special Note: With the 2004 release of Microtab, a new capability was added. When the qualifier radio button is marked and Set/Edit clicked, a new screen opens that allows you to specify up to three columns that can be used to qualify who should be counted in this stub. The relationship between the columns can be an OR condition or an AND condition. Any or all of the punches in a column can be specified, with the relationship between the punches being ANY, ALL, NONE or NOT ALL. The qualifiers are identical to those for recoding data but a new variable is not created.

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Some details of how the screen looks depend on the answers you have given up to

this point. A check box is displayed in the lower part of this screen identified as “Assign weight”. If you check this box, you can assign a weight to that stub. The weight will not appear on this stub page until you check “means” on the next <tab>, “Medians/Means/Stat”. This assigned weight is used to generate a weighted mean/median.

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Special Note: When you click on the Not Answered, Answered, or Sigma radio button, the program can calculate that number based on all the columns and punches specified on the table. This capability is useful if you are reporting the results of an open-ended question that spans several columns and you need to have a stub line that represents those respondents who didn’t answer this question.

If editing is required for your stubs after you have assigned the column number or

the weights, highlight all the stubs that should be edited and then click on the button labeled edit. The below screen will appear and you can easily set a new column number just for these stubs, set a new starting punch for the stubs, elect to automatically fill, in ascending order, the punches assigned to the other stubs, and reverse weights or assign new weight values.

See the screen below for the options available to you for editing multiple stubs all at once.

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TABLES > Regular > Stubs > Ranking - Rank ordering refers to controlling the arrangement of stubs on a particular table according to the frequency of mentions for each stub. If you elect to rank order stubs, you will be asked if you would like

the stubs to be ranked in ascending or descending order. Descending is the usual choice. Once you have clicked on your choice, click Rank Order to specify rank ordering information. Here you can control where your stubs fall within subnets (if they are used) by moving stubs up or down or by indenting them. If you would like certain stubs to remain in their current position (for example if you have a “No Answer” stub), you are able to specify this by clicking the radio button next to “maintain current position”. A red arrow will appear next to that stub. See Appendix 7 for examples of ranking.

TABLES > Regular > Medians/Means/Stat - If you choose to print means, you can

change how the printed mean should be labeled. You can leave it labeled MEAN. This is the default, but you can name it anything you wish ("average", etc). The length of your mean label corresponds to your stub line length, which you indicated in the Banner and page layout for banner 01. If you have a rating question with the ratings going from 1 - (fantastic) to 5 - (terrible), you could weight each of the five responses 1, 2, 3, 4, and 5, respectively, with the most positive rating getting the lowest weight. You can also reverse the weight so the most positive answer gets the highest weight. You can also use negative weighting or a combination of positive and negative weighting.

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Medians can display as a calculated median OR as the weight assigned to the stub where the 50th percentile falls. These capabilities were added in 2005. The assigned

stub weights prior to 2005 had to be in ascending order for the median to be calculated properly. Staring with the 2005 release, the order can be either ascending or descending. The program has a routine in place that now will calculate the medians correctly as long as the weights are in sequence (higher to lower or lower to higher). If the weights assigned are out of sequence (1, 2, 3 5, 4) an error message will be displayed to that effect. See Appendix 4 for additional information on medians, means, standard deviations and standard errors.

When generating a table with a mean, you can keep the assigned weight from printing (Hide stub weights). This is handy if the answers to the question are numerical such as a one to ten (1 – 10) scale. The first stub can be labeled One and you can suppress the ‘= 1’ so that it does not print. This would happen for all stubs with weights on this table if you clicked the box labeled “Hide Stub Weights”.

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If you want to generate mean summary tables or an advanced BR table, you’ll enter the descriptive stub text to explain the mean. You have three lines available to enter

this information. Whether you choose to save the mean for a mean summary table or not, you can check the box next to Print the standard deviation and the standard error. If you did not choose to print means, you will not be given the option to show the standard deviation/error information. You can produce a table that shows the median only. The medians will be generated based on the weights you assign in the individual stub lines, just as means are.

Special Note: If you will be generating means and/or medians, you will have to assign a "weight" to each stub on your table that will be used for the calculations. This type of weight is entirely different from "data weighting" which is covered under sample balancing/weighting. When you indicate you want to print means and/or medians, you specify the "Weight" for each stub.

An important word about creating variables from Microtab Regular tables: To set the jargon used: Tables have stubs, and variables have answer codes. When you try to create a variable from a table, Microtab attempts to create one answer code for each stub. Due to the different nature of stubs and answer codes, caution must be used when automatically creating variables based on existing tables. On one side, a stub can be based on a complex qualifier (implemented in the Microtab 2004 Editions). On the other side, a variable name (answer code) can only be based on a single column/single punch combination. Creating an answer code from a stub that comes from a single column/punch combination is straightforward. When the single column/punch condition is NOT met (in a case of a complex stub qualifier), or when more than one punch exists for that stub, the stub is ignored.

Important: When creating variable codes, Microtab does not allow you to define more than one answer code per column/punch combination. Consequently, when converting the stubs of a table, the resulting column/punch combinations must be unique (not used before in that table and not used before in any other variable either).

When creating variables from Microtab table files, the codes for the created variables are typically based on the punches of the corresponding stubs. In the particular case when a table contains more than one stub based on the same punch, the conflict is resolved by incrementing the code number with 100. For example, if a table contains three stubs, based on the following column/punch combinations: 105/1, 106/1 and 107/1, the corresponding variable codes now receive the numbers 1, 101 and 201, respectively.

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Example: You created variables from a group of Microtab tables so that you can send the data to your client in SPSS format. The default variable names assigned by Microtab consist of a table-type identifying letter followed by the reference number. You can give the question/answer text a variable name by entering that name on the stubs screen. If you elect not to do that, highlight and click on a particular variable in the variable screen and then click on edit. In the variable name portion of the screen, type a more descriptive name, such as Q1 or Q5B.

Keep in mind that if your client is using a version of SPSS older than version 12, you will need to limit your variable names to 8 characters. SPSS Version 12 and newer versions can accept the full 64 characters allotted by Microtab.

TABLES > Value – This routine is used to enter stub information, table numbering,

mean/median instructions and other parameters necessary for generating each value table in the final report. A value table is based on a consecutive series of columns whose punches are read together as one value (known as a "field").

These tables report on numeric values, such as a specific price estimate that respondents might have given. Value columns are also used to hold "99 Codes"; codes that aren't values themselves, but rather punches that extend to two digits rather than one. A 99 code could be used to record one of 99 answers to a single question, and take up to two columns. Since 99 codes are usually recorded in value columns, value tables can be used to report them. If you used a value field to record the number of terminates encountered in the process of completing the interview, you would use a volume table to report a summation of this incidence information, not a value table. Establishing the table parameters for value tables is only slightly different from establishing the parameters for regular tables.

Starting with Version 6, value table row labels (stubs) could be automatically filled-in (by clicking the autofill button) with each unique value being assigned a unique stub. The value is shown as the row label. With Version 7 we have increased the number of rows (stubs) allowed in a value table from 99 to 999. This removes most restrictions when creating a value table showing numeric zip codes.

Special Note: When setting up value tables each record in the database must be accounted for with a row/stub line descriptor and qualifier. The autofill feature will ONLY capture those records that have a value. If there are records that do not contain any value an error message will display during report compilation and the table being generated will not display as expected. A log is generated that will indicate which value table did not display/compute properly. Usually this can be remedied by either adding a row label and qualifier that accounts for those respondents who did not answer. You can also set a filter in the report manager so that only respondents who have an answer in the value field are accessed during compilation. With Version 7 two additional value table stats can be shown on a value table. These two stats are the minimum value found in the field and the maximum value found in a field. The minimum and maximum values found are printed for each banner point, and the values are printed above the mean at the bottom of the table.

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TABLES > Value > General - As in regular tables, you are prompted to enter a six-line

question or table label that will appear at the top of each page. The question label’s printed position on the table (left-justified, centered, etc.) is determined by your Banner and page layout. You also enter a footnote on this screen if so desired. The value field that will be tabulated is specified here as well as the decimal point position in the value field. If a decimal is not to be used in this value field, enter the number zero.

You can also change the default stub screen by accessing Tools>Options>Template. You can set the opening stub screen to be whatever you want. The ‘new’ default screen will then be used/displayed whenever you enter the table manager routine

Special Note: As mentioned previously, a value field cannot start in one card and end in another. Therefore, your starting and ending columns must have the same card number. Also, remember that a value field can only be twelve (12) columns long.

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TABLES > Value > Stubs - To determine what stub descriptions you should enter for a value table, you will need to see a breakdown of the frequencies for each value in your value field. This can be accomplished by producing an array. You will want to print an array that is based on cumulative occurrences for this task. The first stub on your table is automatically labeled Total Respondents. You can change this stub screen by accessing Tools>Options>Template. You can set the opening stub screen to be whatever you want. The ‘new’ default screen will then be used/displayed whenever you enter the table manager routine. You can also edit this label by double clicking on the stub or by removing the check mark in the box next to Show the total respondent count. This allows you to specify that the frequency shown should be those answering or sigma.

An auto-fill button has been added to the bottom of the value table stub screen. The button will become available after you have specified the value field source columns for this table. Clicking on this button will automatically populate the table with a stub for each unique value and will use that value as the stub label. Because a value table is currently limited to 999 stubs, you might find it necessary to reduce the size of the value field (example: for zip codes from 5 digits to 3 digits).

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TABLES > Value > Stubs > Append - You may enter any number from 1 to 999.

Remember that the first stub line is usually labeled "TOTAL RESPONDENTS" and that this stub does not need to be appended. Therefore, if you have 10 actual answers to a question, you should say you want 10 stubs. Each blank entry for a stub has a place for three lines of text (where you enter the answer that the stub represents) and a space for the highest value that should be counted on that stub. The range of values that will be counted in that stub are shown in the box at the bottom of the screen. You can also assign a value to an X punch by clicking the button. An "X" is entered during data entry when you wish to assign your own high value, one that was too large to be recorded in the value field itself. An X punch would NOT BE USED to represent a value that is too small for the value field, such as the value .5 in a value field with no decimals.

Example: Suppose the following question was asked, "What percent of the time do you buy this brand of soap?" You might have assumed that no one would answer 100% and therefore your value field was only two columns long. If someone did answer 100%, you would not have any way of recording it. This is the time to enter that special high value. You would do so by clicking Value assigned for high punch and then assigning the number "100". For every questionnaire that has an X punch, this one number that you assigned would be used when calculating the mean, standard deviation, standard error, and median. In our example, the computer would be able to use 100 in those calculations. Remember that your assigned high value can be up to twelve digits long.

Other buttons are for a Y punch (representing Refused/No Answer) and a blank field (representing No Answer – as in a skip pattern). Special Note: In general, be sure that the length of the value field does not exceed the width of one banner point. If it does, you will need to either reduce the size of the value field (change your expression of the number recorded from units to thousands) or print the mean without any decimal positions shown or both. When the print positions required for the mean exceed the banner point width, the means will be truncated. Special Note: If you do not use the autofill option, value stubs must be individually entered starting with the lowest value and going to the highest value. Always assign the values from lowest to highest, going from the first stub to the last stub. An auto-fill button has been added to the bottom of the value table stub screen. This button will become active after you have specified the value field source columns for this table. Clicking on this button will populate the table with a stub for each unique value and will use that value as the stub label.

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Special Note: For the highest value in your last value stub you should enter the highest number possible for the amount of spaces in your value field (i.e., if the field is three columns long, enter "999").

If you elected to show the total respondent count in the first stub and to label it TOTAL RESPONDENTS, then you will start labeling at the first line of the second stub. You may use 1, 2, or all 3 lines for labeling. Each stub line is as long as you indicated in banner file 01.

TABLES > Value > Medians/Means/Stat - The questions concerning the mean, mean

summary tables, and standard deviation/error are identical to those on the third screen for regular table parameters except that all medians are actual medians. Two additional stats can be shown on a value table. These two stats are the minimum value found in the field and the maximum value found in a field. The minimum and maximum values found are printed for each banner point, and the values are printed above the mean at the bottom of the table.

One situation where means would not be useful in a value table would be for 99

codes. As mentioned, 99 codes are two-digit numbers that can code up to 99 answers. They are not actual values (as price or age in a value field would be). Since 99 codes do not represent values, means are not desirable and may be omitted. We recommend you convert 99 codes to specific column/punch designations. See Columns > Recode > Specific numeric values.

You are asked how many decimal places you want to show in the mean. When the

number of print positions exceeds the banner point space you specified in the report format, the mean will be truncated.

An important word about creating variables from Microtab Value tables:

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Value tables are created from value fields (fields of numeric data). Because there are no specific answer codes other than the unique values for each respondent, answer codes are not created. Instead, the unique value entered for each respondent is the answer code shown in the variable output.

TABLES > Mean Summary Tables – Use this function to enter the mean summary table label, table number, and rank order information necessary to produce each mean summary table. A mean summary table is based on the means created when a regular or a value table is compiled. The information is not stored in a separate file. If the means are incorrect on your regular or value tables, they will also be incorrect on the mean summary table.

TABLES > Mean Summary Tables > Add Stubs - A mean summary table is used to collect the means from many tables and combine them on one table. In this function you create a kind of "shell" table in which the means from different tables are inserted. First, enter a label for your mean summary table. Click Add Stubs and a list of all your parameters will be displayed. The descriptive label, to be shown as a stub label on this mean summary table, is shown at the top of the drop down box. This is the label you entered at the regular or value table Medians/Mean/Stat screen.

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Highlight those table parameters you wish to summarize on this mean summary table and click on okay. If you make a mistake, you can delete a stub from this table. You can also arrange the order in which the stubs will print (by highlighting and then using the Alt and arrow keys). A box can be clicked indicating that the highlighted “stub” should be forced to print on a specific line, regardless of ranking specifications (Don’t, Ascending, Descending) . You are being asked to indicate if you wish to force this specific mean summary stub to print on a specific line of the

mean summary table. You might, for instance, want this mean to appear first if it applies to a control product.

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TABLES > Mean Summary Tables > Print Options – Up to six rows of information can be printed for each mean summary stub. The options are: nothing, sample size, mean, standard deviation, standard error, median and sum of the frequencies. Indicate what you want printed and if you want an identifying label to be printed. You’ll then indicate what type of ranking, if any, that you want.

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TABLES > Volume Tables – This routine is used to enter stub information, rounding instructions and other parameters necessary for generating each volume table required for the final report. Volume tables, also known as incidence tables, can be used to report the total number of contacts made while conducting a study. Typically, a volume table shows the total contacts on the first stub line, then successively the number of terminates at each termination point and then the number of completed interviews. These tables come from value fields, and, if you have entered parameters for value tables, you will be familiar with the concepts involved. Like value tables, you do not enter column/punches for each stub. Rather, you enter a starting and an ending column and label the stubs according to

whatever value is contained in that field. For the first stub, you typically indicate those stubs on the table that it should sum.

In value tables, you enter only one set of starting/ending columns for each table.

Each stub in a value table represents a breakdown of the values recorded in that value field.

In volume tables, you have a different set of starting/ending columns for each stub - one stub that is the sum of other stubs and it records the total contacts, and other sets for the column pairs that record the number of terminates at specified points in the questionnaire. With volume tables, you can add together all your terminate fields and create a stub called Total Terminates. Establishing the table parameters for volume tables is slightly different from the procedure followed when establishing the parameters for regular or value tables.

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TABLES > Advanced Tables – There are both regular and value types of advanced

tables.

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There are three variations for regular advanced tables and two variations for value advanced tables. For both regular and value tables, the first variation allows you to generate multiple tables side by side. As an example: You could be testing four different products and one of the questions asked for each product could be “How likely would you be to purchase this product “ with the answers being recorded from Definitely would buy to Definitely would not buy. This type of Advanced table allows you to set up the table with one set of stubs (the purchase intent scale) and four banner points, each banner point representing the column/punches for a different product. Rank ordering the stubs based on frequency count is not allowed on a table where the stubs are assigned weights for means or medians.

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This is the only table type where a dependent t-Test should be performed. The dependent t-Test focuses on the difference between the dependent (paired) data and reports the probability that the actual mean difference is consistent with zero. This comparison is aided by the reduction in variance achieved by taking the differences. For a dependent t-test to be accurate, only respondents who answered both of the questions being asked should be included in the test. If a respondent answered only one of the questions, they should be excluded. Microtab excludes those respondents (when conducting the test) who did not answer both of the questions. The second variation of advanced table (both regular and value) occurs when you need to overlay tables and create a summation of the corresponding cells. You might have a question that asks “What one thing do you like most about this product?” and a follow-up question that asks “What else do you like about this product?” You might want to generate a table for the first question to determine which attribute is most important. This would be your straight regular table. In addition to printing the second table for the follow-up question, you might wish to see a combined frequency distribution for both questions that reflects the answers to the first question and the second question. Both tables would be setup as regular tables but the advanced table would create a summation of their corresponding cells. You specify which information you wish to copy from the table that will serve as the template for these advanced tables. That screen is below.

The above screen is displayed so you can indicate those attributes present on the template reference you wish to copy to the advanced table.

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Because you are asking the program to physically add tables together, the Total Respondent stub line could reflect the total number of respondents in the study multiplied by the number of tables you are adding together. In the example, you are adding together four tables and the total Respondent stub line would show 1200 respondents rather than the desired 300 respondents. To avoid showing 1200 respondents, check the box labeled ‘Single TOTAL stub (not sum of base tables’ TOTALs). The third variation of an advanced table applies to regular tables only. This table can be thought of as a top-two box summary table. Prior to the 2004 release of Microtab, you would have to generate a regular table to produce a top-two box summary table for a list of attributes. However, the percentages shown on the summary table would be based off the same total respondent count. You could not show or have different total respondent counts (bases) for the attributes being summarized.

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This new type of advanced table reflects the percentages shown on the original table. This table type strips the frequency counts and percentages from the original table when the advanced table is generated. The stat test results computed on the original table can also (optionally) be stripped from the source table and inserted into the summary table.

This type of advanced table can have the stubs rank ordered based on frequency count. You can elect not to rank the table or you can have the program rank the stubs in ascending or descending order. The ranking will be based on the frequencies shown in the first printed column of frequencies (banner point).

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REPORTS

REPORTS > This option combines all the questionnaire information that you entered and

outputs it back to you in an understandable form. REPORTS > Report manager - In this, the final step in the production of a report, you

tell the computer which banner configuration (number), and what table parameter files it should combine to produce the tables you desire. Once you have given the computer this information, it is able to produce the final report using the data you have entered. Only one screen is displayed (until you click print) and what follows will explain the various elements of this main screen.

When you generate tables, you are actually pulling many functions together and tying up some loose ends. This fact is reflected in the kinds of information you can provide in this screen. At the top of the screen is a pull down box that contains a listing of all your banners with descriptions. Click the down arrow and select the banner configuration you wish to print.

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Regular, value, volume, and mean summary tables are produced simultaneously and in any order you wish. You can highlight a specific table (or multiple tables) and then use the arrows on the right side (in the middle) of the screen to move the table(s) to the desired print position. These arrow keys are set to repeat so holding

down the left mouse key while it rest on the up or down arrow icon will continue to reposition the highlighted table(s).

On the left-hand side of the screen, all tables show a check mark. Each check mark indicates that that table will print. If there is a table that you do not want to print, click the check mark located in the check box so the check disappears. Only tables with their boxes checked will print. If you wish to generate a report based on weighted data, you will need to indicate what weighting file the computer should use. Use the weight button on the right side (lower half of screen) to access this. You may also indicate that you wish to produce certain tables that are based on a filter (or sub-sample). You will be asked to enter the columns and punches to qualify that sub-sample. You also have the option of overriding the total respondent count on your tables by changing the base for percentaging.

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In all cases, highlight those tables you wish to apply an instruction to and click on Select. If you want all the tables to be re-based on a sub-sample, have the same changed base for percentaging or to be weighted, you click Assign to all tables. There is a box on the right side (middle) of the screen labeled Show details. Checking this box will display the weight file, sub-sample file and base changing information for each table. This information is shown as part of the grid and also is shown in a window at the top of the screen. You can set the program to always

show the details in the grid by accessing Tools>Options>Reports and checking on Show details.

In addition to indicating that you wish to produce certain tables that are based on a sub-sample, you can also create a global filter. This allows you to initially specify the filters for the individual tables and then generate a first set of tables for your client. If the client then comes back and requests another run of all the tables but wants this run based on (example) respondents that have a college education, you would specify a global filter. A global filter is applied in addition to the specific table filters. You would enter the columns and punches to qualify that sub-sample in the same way you specify any sub-sample qualifications. See the Specify a filter screen on the preceding page as well as Appendix 2 for further information. The screen that you see when entering the Report Manager can show the details (weights, filters and change % bases) or not. You select how you wish to view the screen by going to Tools> Options>Report.

If you elect to show details the screen will display three additional columns of information showing weights, filters and base %’s. You can elect to display a descriptive box at the top of the screen by double clicking on the box labeled show details. This will add the box temporarily to the detailed screen as shown below. By clicking on the show printing details box (above) you’ll display just the additional three columns of information (without the descriptive box).

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Table numbering is automatic and the numbers are assigned sequentially from top to bottom. Only tables that are checked are assigned a table number. If you wish to indicate that a table should be numbered (example) 42B, you highlight that table and right click and then click the button labeled Specify table numbering. After you have entered all the parameters for producing these tables against the indicated banner, click Save and the instructions will be stored. You can copy these instructions to another banner by changing to the new banner and clicking Copy set-up, which is located in the top right corner of the screen.

REPORTS > Printing Tables – You can print all your check marked tables or just the

current (highlighted) table. Indicate if you want to restrict the printing to just one (highlighted) table. The default is that all tables checked marked will be printed. As is common in Microtab, clicking Print first displays your request in a Preview screen so that you do not have to actually generate a hard copy. Radio buttons give you control over the printing of the table of contents. You can elect to print a detailed table of contents, showing reference numbers, column numbers and the question text. Also shown will be the assigned table number, the weight file used, if any, and the filters created for each table.

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You can interleave your tables during printing. By interleave, we mean print table 1 against banner 1, banner 2, banner 3, etc., and then automatically repeat the process for table 2, tables 3, etc. This will be done in batch mode for every checked marked table. You accomplish this by filling in the box at the bottom of the print and preview screen labeled “Additional banners…”. If you want to interleave the tables for banners one and two, select banner one from the previous screen and type the number 2 in the area designated additional banners. Do NOT type in the number 1 again or you will get two copies of banner 1. Separate the banner numbers by commas. When everything is as you wish, click on Preview and the tables will be displayed on the screen.

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In the upper right corner of the displayed table screen is a drop down box showing all the compiled tables. Select the table you wish to view and click. That table will be immediately displayed. If the report meets your requirements, you can send it to the printer, save it as a Word document, save it as an Excel file, save it as a text file, save it as a comma delimited (spreadsheet) file or save it in HTML format.

CHARTS CHARTS – After tables have been generated for a study you might want to generate charts. Charting is included with the Professional Edition.

During the course of writing an analysis for the project you have just tabulated, your client might feel that it would be appropriate to include charts in the analysis. Microtab can automatically generate charts for every table that you produced (or perhaps for only one or two tables). Chart production is done the same way as table production –every table or selected tables. Preparation: You must have variables created before you can create charts. This is easily accomplished. You normally create your tables and generate your reports before there is a need to create charts. Therefore, after your tables have been created you can highlight all of the regular tables <Ctrl> <A> and then click on Create variables at the bottom of the table’s screen. You could repeat this process for value tables. Below is the main table screen and the button for creating variables is at the bottom of the screen between Edit and Print.

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Select or create an instruction file > After you create your variables, click on Charts from the toolbar and you can either create a new Chart instruction file, open an existing instruction file or delete an existing instruction file. See the screen display below.

CHARTS > New – Clicking on New will first ask you to confirm that the file to be created should be referenced as file number 01. Click yes to proceed and the program will display every variable name in the Microtab library. If you used the automatic variable creation feature mentioned above, the variable name by default is the Microtab tables’ reference number. You can change the variable name by accessing Studies>Variables from the toolbar. Highlight the variable name you wish to change and then click on Edit.

To the left of the variable name is a check box. If there is a table (variable) for which you wish to generate a chart, check the box next to the variable name. You can check as many boxes as you wish for each instruction file you create. Two buttons are provided so you can check all tables or uncheck all tables with just one click. One of three different letters is displayed next to the check box: an S for a single variable, an M for a multiple variable and a V for a value variable. It is best to review the table’s question in determining which charts you wish to produce.

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Different charts can be easily produced. You can generate 4 different pie charts – 2D, 2D exploded, 3D, and 3D exploded. You can also generate 4 different column/bar charts – 2D column (vertical), 3D column (vertical), 2D bar (horizontal) and 3D bar (horizontal). If you have more than one table for which you

want to generate the same type of chart, highlight (Ctrl and then left click) those tables (click in their question area) and click on Options. If a table or group of tables require a filter, highlight the group of tables or the single table and then click on the filter button. The routine for filtering is identical to that used throughout Microtab. Without filtering, every chart will be based on the entire data base.

CHART > Options – Clicking this button permits you to select the type of chart that you wish to generate and to set various chart parameters.

Special note: You check mark those variables for which you want to produce a chart. If you have a group of variables that you want to generate (example) 3D Pie Charts, highlight just those charts and then click on Options. The parameters you select will apply to all the highlighted variables, NOT to all the checked variables.

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The default size of the charts can be set under Tools > Options > Reports. The default size can be over-written (temporarily) by changing the values shown on the Chart Options screen (see below). The chart options screen also allows you to select whether you wish to have the legend displayed as part of the chart. You can also elect to show values or percentages and whether you want the X axis to be labeled.

The parameters you set for the charting instruction file will apply to all the variables that you highlighted on the previous screen. You can highlight a different variable (or group of variables) and establish different parameters for those (i.e., Pie charts instead of Bar charts).

There is a button labeled Advanced on the Chart Options screen. An explanation of all of the functions available when clicking this button can be found in Appendix 14. Please read the Special Note below.

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Special Note: Starting in 2005, Microtab permits typing the question text on up to six lines with each line being 80 characters in length. If you use all 80 available characters on a line and/or use all six lines, the question text might interfere with the default legend placement on the graph. A quick adjustment can be done for a question with a long title by moving the Legend downwards. This is accomplished by entering the Advanced Options screen, clicking the Legend tab, then Position in the next row of tabs, and increasing the Position offset.

. After you have established the parameters for all the charts you wish generate, click on save. You can always edit the file you created, adding more charts (or removing certain charts) and changing the chart types. After saving your charts, they can be previewed on the screen. After previewing, you can save all the charts to a Word document (*.doc) or in Rich Text Format (*.rtf). Without previewing, you can save all the carts as jpeg images; one chart per jpeg file name. If you determine that you need one chart for a report that you are writing, you can access this charting routine, highlight the variable you need to chart and select preview. After the chart is displayed on the screen, you can copy it to the clipboard. This chart can then be pasted into a Word document or a PowerPoint presentation. Actually, the chart (*.bmp image) can be pasted into any software that accepts a *.bmp image. You also print or save the charts from the Preview screen. Charts can be saved in Word format or saved in rich text format.

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TOOLS TOOLS > Statistical testing – Certain statistical testing capabilities are made available to

you by accessing Tools. A test selection wizard is available to assist you in selecting the correct statistical test to perform based on data relationships, sample composition and number of variables being tested. Not all tests in the selection wizard are included as part of this software. The tests provided in Microtab are ANOVA, Repeated measures of ANOVA, Independent t-Tests, Dependent t-Tests, Cochran’s Q and McNemar.

Our intent was not to compete with complete statistical offerings from other companies but rather to address the needs that arise as part of table generation. See Appendix 6 for more information.

TOOLS > Data Manipulation - As part of the data reduction process, it is sometimes

necessary to manipulate the data in order to combine data that is in different "formats". An example would be a questionnaire that asks the respondent to indicate how much orange juice is consumed on a weekly basis in their household. Some respondents could say "one half gallon" while others could say "two twelve ounce frozen containers". Other combinations could also be given by the respondents. It is the researcher's task (perhaps) to express all the answers given in ounces of drinkable orange juice and thereby be able to provide an average weekly consumption rate of orange juice for the respondents participating in the study.

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To achieve this objective, the initial values given by the respondents would be separated by "format" and then individually multiplied by a user specified number. The result would be placed into a secondary field. Many respondents could have replied with more than one format. Therefore, on a respondent by respondent basis, these secondary fields would have to be added together with the result placed in a final field. This final field would then be used to produce a cross tabulated table. Before data can be manipulated, it must be converted into single precision (eight decimal positions) format. Likewise, after data has been manipulated and you want to generate tables based on it, you have to convert it back into the cross tab (integer) format.

You can convert from the current study or you can convert from any other study. Usually you will want to convert from the study that is indicated. If you signify that you wish to convert from a different study, you will enter that study number. The data manipulation database stores data in single precision format. This allows one column in the data manipulation database to hold either an entire value field or just a single numeric digit. It is similar to a spreadsheet in this regard. Because of this, data is copied into the data manipulation database using two different routines. The first converts value fields while the second converts data that comes from a single column.

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Converting value fields: Designate the column to hold the converted data by entering a tag. This tag is a descriptive alpha-numeric label that identifies the original location of the source data. The tag can be up to 8 characters long. Then enter the starting and ending column numbers for the cross tab value field, the location of the decimal point in the value field and any qualifiers that might be required. If a decimal appears at the far right of the value field, you would enter a 0 to indicate its location. If no qualifiers are required, you skip that field. If you are using an "X" punch in the value field to represent a high value, you would enter the assigned value in the field provided. If you are not using an "X" punch, skip that field. Enter any qualifiers (filters) that might be required. Convert single column fields: You will be prompted to enter a tag for the destination column number that you want the converted data to be sent to, the cross tab column number, and any punches that should be ignored (not converted). A three (or four) digit number is used when specifying the column number in the cross tab data base. If no punches are to be ignored, skip that field. Special Note: When converting single column fields, "X" punches will be converted to an eleven; "Y" punches will be converted to a twelve; and "0" punches will be converted to a ten. It is primarily because "0"'s are converted to tens that you are offered the option of ignoring certain punches during the conversion process. By ignoring "0" punches during the conversion, blanks will be shown instead. See manipulate data, below, regarding changing blanks to zeros. Converting data back to Microtab (Integer) format: This process is the opposite of that used when converting data to single precision. Special Note: If you send data from the data manipulation data base back to the cross tab data base and data already resides in the destination column, you will NOT be warned. The new data will be ADDED to that which already is in the cross tab data base. When you send data back to a study, it is sent back in record number order. If you elect to send the data back to a study number different than the one it originated from, that study must have the exact same number of records. Make sure that sufficient room is available in the cross tab data base to accept the data you want to send back. It might be necessary for you to expand the cross tab file size (add cards) before converting the data. Actual manipulation - After converting the data, you can manipulate it according to your needs. Various manipulations are available to you. The choices relate to working with multiple columns (add), two columns (subtract, multiply or divide), working with one column and a user input number (add, subtract, multiply, divide or raise to a power) and performing a function on one column (square root, rounding and changing blanks to some number).

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Special Note: You must change blanks to zeros in order to add (or multiply, subtract, etc.) columns together. If you add a fixed value to a column, say a seven, and there is a blank in the column, the result will be a blank. This is because a

blank is interpreted as infinity. Any function that uses a blank as part of the calculation will display a blank as the result.

After the data has been manipulated, it can be sent back to the Microtab database.

TOOLS > Log viewer – The feature automatically creates an audit trail for all data

altering actions performed on the data file for that study. This can be an especially useful tool for tracking studies. You might want to be able to follow the same process of recoding data after each wave’s data is added.

This log can be sorted and filtered by clicking on the ellipse […] at the top of the screen. This allows you to look at (example) just the copy columns files or perhaps just those files created on a specific date.

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TOOLS > Create DOS version files – The DOS versions of Microtab Cross Tabulation

Software limit the user to 99 stubs (row labels) per table. For backward compatibility, a utility to convert table parameters from 999 stubs (Windows only capability back to 99 stubs (DOS versions) has been provided. Any stubs entered in Microtab greater than 99 will be truncated.

TOOLS > Options – Seven tabs are presented that allow you to set defaults for your use

of Microtab.

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TOOLS > Options > General – You can set the program to prompt you for a study number every time the program starts or the program can be instructed to load the last opened study. You can clear the list of recently opened studies (shown on the toolbar under Study) displayed at the bottom of the drop down box. You also set the Default folder for your studies here. It is recommended you create a folder called Data and keep individual folders within Data that are identified by study number. The Default folder for your studies in this example would be Data. You can also indicate your preference for using X and Y codes. The default when shipped is that the software WILL use X and Y codes.

TOOLS > Options > Reports - This tab permits you to specify the underline character

for banner points. The default underline character for the banner point labeling is a dash. You can change that so it is an equal sign, an asterisk, or whatever you want. It is from this tab that you also set your default size for chart sizes. This default can be overwritten while in the charting routine after you have selected a variable(s) to chart by clicking Options. This process will only override these default settings for the chart(s) selected.

You can also check the box next to Show printing details. This will display three additional columns of information in the Report Manager (weighting filtering and base %’s). A descriptive box can also be displayed in the Report Manager by double clicking on the Show details box in Report Manager. You also can set the default stub line length from this screen. The default length is 19 characters but this length can be over-ridden when setting a specific banner.

TOOLS > Options > Preview – All printing is set to default to preview mode, which

displays your intended printout on the screen. Under this tab, you can set the preview to show you a page width display, a whole page display or a percent zoom display. The display selected depends on the monitor and personal tastes. Please see the screen below.

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TOOLS > Options > Print – This tab permits you to set the default top and bottom

margins and to indicate whether or not the printing should be set at 8 lines per vertical inch of paper. At the service bureau we use a top and bottom margin of 0.50 inch and always print at 8 lines per vertical inch. We do not allow you to control the left and right margins when printing as this is controlled by your printer. See Appendix 3 for a discussion of left and right margins.

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TOOLS > Options > Filter – This tab permits you to set the relationship between punches and the relationship between columns for all the filtering routines that are offered in Microtab. The shipping default is as shown below. You can elect to have the filtering conditions set to ‘blank’ if you wish. This will force you to check the desired filters before running any of the routines

TOOLS > Options > Templates – This tab permits you to establish a default stub start screen for regular and value tables. The default template shows the Total Respondent label as the first stub when you access the stub tab for regular and value tables.

The template can be edited to look as follows (or any other setup) and when Apply Template is checked, the below screen will display when you access the stub tab for regular and value tables.

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TOOLS > Options > Stat – When data is weighted through sample balancing or a user

developed weight file and the total size of the sample in increased greatly, stat results can be affected. By selecting the third listed option, the unweighted percentage base, the cell sizes will be determined (during the stat calculations) by their revised weighted percentage multiplied by the unweighted percentage base. This will reflect a true variance as opposed to a (perhaps) miniscule variance.

Special Note: This unique calculation capability was added in 1985 for one of our users who did not want the size of the sample to affect the variance. He weighted the data by a factor of greater than 100. The percentages derived from the weighted data were then used but against the total unweighted sample size to arrive at the cell sizes for calculations. What Microtab does is create the weighted table (and print it), but in the background re-calculate the cell frequencies using the weighted percentages and the unweighted base. These new calculated cell frequencies are what would be tested against the unweighted base. Microtab uses the same formula as documented in the manual. The recalculated cell frequencies are not printed on the table.

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HELP

Help Topics: - The online Help is presented using the Windows convention. Presented

under Help are Contents, Index and Find.

HELP > About Microtab – In this section, the Build number and the Microtab Edition

installed on your computer is displayed as well as our address (physical and web) in addition to our telephone and fax numbers. An area is provided to enter a new serial number. The serial number controls the length of time remaining for use of the Evaluation Edition.

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The serial number also controls which Edition you have installed and the computer that the software will operate on. Microtab is licensed to operate on only one computer and is dedicated to that computer. If you need to install the software on an additional computer, you will have to contact us for a new serial number and pay an additional licensing fee.

APPENDIX 1

DATA FORMAT LAYOUT & TYPES Before you try to use the Microtab cross tabulation software for tabulating the results of a study, it is necessary that you understand data formats and more specifically, how Microtab stores data. Microtab cross tabulation software stores data in card image format. We use the 80 column keypunch card as the card image. Printed on the card are the numbers 1 through 80 (going from left to right) that indicate the column numbers. These numbers are shown between the 0 and 1 punch and repeated between the 8 and 9 punch. Every column contains the numbers 0 through 9 displayed vertically. These are punches. The card also contains an blank area above the 0 punch which can hold an X and a Y punch. The 80 column keypunch card was originally created to control a weaving machine and was later adapted to tabulate census data. A keypunch machine literally punched a hole in a number position in a column.

In survey research (marketing research), a card column can be used represent an answer to a question in a survey. Consecutive columns can be ‘chained’ together to store a number response of more than one digit, such as a dollar amount. The punches in each column indicate the answer to the question, the vote in the election, or the value of a dollar amount. A simple example would be the assignment of a 1 punch to represent a yes answer and a 2 punch to represent an answer of no. A questionnaire might offer a list of 5 choices for the respondent to choose from. The question would be assigned a column number and the choices would be assigned a punch number in that column. Choice A might be punch 1, choice B would be a punch 2.

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You might also have the question “How much would you pay for this product?” To note this on an 80 column punch card, a consecutive series of columns would be assigned to hold the answer. Each individual column would represent a place value in the number;

ones, tens and etc. Each column would hold the punch representing the actual number for that place value given by the respondent. If the respondent answered 250 to the above question then for each of the columns the appropriate number is punched, a 2 in column 15, a 5 in column 16 and a 0 in column 17. Decimals are not used when entering data. Each card contains 80 columns. In most instances the first 4 (up to 7) columns are used to hold the respondent ID number. Column 80 (and sometimes 79) on each card represents the card number. Column 79 is used in studies requiring more than 9 cards. In a lengthy survey, more than one card is often required. Column 80 would be punched a 1 for the first card, 2 for the second card and so on. With a 12 card study, the card number 12 would specified by a punch 1 in column 79 and a 2 punch in column 80. When referring to column numbers in a Microtab database, a 3 or 4 digit number is used. The first number indicates the card number for the study and the second two digits indicate the actual column on the card. For example: the number 125 refers to column 25 on the first card of that study. Likewise, column 1255 refers to column 55 on card 12.

The above illustration represents a punched card. It is punched in column 80 to indicate that this is the first card in a study. Columns 1 through 4 are punched 1, 2, 5, 0 to indicate a respondent number of 1250. Column 20 is punched a 1 to indicate a response to a question. Column 25 is punched at both the 2 and 4 locations. Some questions on surveys might allow for multiple responses. Column binary (card) data can hold multiple punches. Columns 31 through 33 are punched to represent a response of 875.

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Microtab Cross Tabulation software can also accept data that is in ASCII card image format, data that is in ASCII fixed length string format, or data in *.sav files. Triple S formatted data is ASCII data. Microtab software converts all data types into a card image column binary format. With Microtab, you have complete flexibility when it comes to working with data formats. Microtab just stores the data in this card image format.

APPENDIX 2

FILTERING (SUB-SAMPLE QUALIFICATION) To start, view Tools>Options>Filter on page 117. When you ask Microtab to compile data, you might want the data to be based only on people who gave a specific answer to a previous question, while those who did not give the specified answer can be ignored. Any time you want an operation to include certain respondents only, and not the entire database, you are asking the computer to base the operation on a Filter of the database. You can specify whether you want all the respondents to be included in the data or only some of them. If you decide you do not want all respondents, you must tell the computer exactly which respondents should be included. This process is known as “Filtering” (sometimes called "qualifying" the respondents, or "qualifying the sub-sample"). Whatever your reason for wanting to qualify a sub-sample, the procedure is essentially the same. Consider this: One way to qualify respondents would be to look through each questionnaire and see which respondents gave a certain answer to a particular question, then tell the computer what those respondent ID numbers were. However, this would be a tremendous waste of time since the computer can read through the "questionnaires" (actually the data file on the hard disk) many, many times faster than you could. Therefore, you need only tell the computer exactly what to look for, and it will find the respondents for you. Suppose you wanted marginals to include only those respondents under the age of 35. Looking at your questionnaire, you see the following question: Question 14 - What group does your age fall into? 111 - 1 18-25 years - 2 25-34 years - 3 35-44 years - 4 44 years and over When filtering, you can enter up to three columns, but in this case you would only have to enter column 111. You would then press <tab> and click the down arrow. Select Any and press <tab> again. You might want to look at respondents who gave two or more designated answers to a question. In that case, you would want either an AND or an OR condition between the answers. Your choice would be based on whether you only wanted to include those with both answers or whether you wanted to include those with either answer. For this example, enter from the numeric keypad (or click the numbered boxes) for number 1 and 2. Since a person who was entered as either a punch 1 OR 2 in column 111 would qualify, you are done.

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If you are using more than one column to qualify the sub-sample, you will also have to set up an AND/OR condition between columns. You are being asked to, specify the relationship between the two (or three) columns, and you would answer accordingly. If you find the AND/OR concept confusing, think of it this way: the more AND conditions you specify, the less likely it is that a respondent will be included in the sub-sample. You are saying, "To be included, the respondent must be this AND this AND this," creating more and more opportunities for a respondent to be rejected. If a person fails the test of just one condition linked by an AND, he is rejected from the sub-sample. On the other hand, the more OR conditions you include, the more likely it is that a respondent will be included in the sub-sample. Now you are saying, "To be included, the respondent can be this OR this OR this," creating more and more opportunities for a respondent to be accepted. If a person passes the test of just one condition linked by an OR, he is included. Summary - To select records, you can specify up to three related columns for examination, (with either an AND condition or an OR condition between columns) and as many punches within each column as desired (with all the punches being either absent NONE or present ALL of present some ANY) and the relationship between the punches in each of these columns being either an AND condition or an OR condition. (Based solely on the length of this last sentence, you should be aware that this is an extremely powerful routine. It is important that you really think about what you want to do before giving the computer instructions.) The same column can be spec'd twice - once to look for specific punches being present ALL or ANY and again, to look for punches being absent NONE or NOT ALL. The extent of qualifying that can be accomplished is limited only by your imagination.

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If you tell the computer to check for punches 1, 2, 3 or 4 in a column and you say to check for any punch being present (OR), the computer will look for an OR condition between punches in this column. If you tell the computer to check for every punch being present (AND), the computer will look for an AND condition between punches in this column.

APPENDIX 3

PRINTER LIMITATIONS

Different printers restrict the user as far as printable area on a piece of paper. Microtab defaults to a fixed printable area with a left and right margin of .28 inches. This converts to 183 allowable (and printable) characters per line, using the Lucida Console 7 point True Type font. Most laser jet type office printers will work within these parameters but some desk jet and bubble jet printers will not. Below is a list of those printers that restrict the printable area to being less than 183 allowable characters per line. This listing is not exhaustive but indicative of printing problems you might face. To determine the printable line length for your printer, access your word processor and set the page orientation to landscape and the left and right margins to zero. When you try to exit page setup, you’ll be advised that the margins are outside the allowable print area. Click Fix to set them at their minimum. After you are returned to the document, change the font type and size to Lucida Console 7 point and type the numbers:

12345678901234567890 repeatedly until no more will fit on the line. That is the number of characters per line that your printer will support. Repeat the process while setting the page orientation to portrait mode. Repeat the process for landscape and portrait again but change the font type and size to Courier New 9 point. Make note of the four numbers as displayed below. You will have to make allowances for any printer limitations you might discover. If your printer only allows 170 characters to print on a line in landscape mode and you are using Lucida Console 7 point, make sure that 13 spaces are ‘left over’ when setting up your banner.

Printer Fonts Portrait Landscape

Large 102 133 Canon Bubble Jet BJ 250 Small 130 170 Large 108 138 Canon Bubble Jet BJ-230 Small 139 177 Large 104 137 HP DeskJet 840C Series Small 140 183 Large 109 141 Epson Compatible 24 Pin Small 139 180 Large 106 140 HP LaserJet 6P Small 133 175

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The top and bottom margins are controllable by the user within the Microtab program. See TOOLS > OPTIONS > PRINT. At our service bureau, we always print at a forced 8 lines per vertical inch and have the top and bottom margins set at .50 inch.

APPENDIX 4

TABLE STATISTICS (MEAN, VARIANCE, STANDARD DEVIATION, STANDARD ERROR

and CALCULATED MEDIANS)

Following are a couple of examples for sample means, variance, standard deviation and standard error. We'll consider two samples. Sample 1 has five values 10, 8, 7, 3 and 1. SAMPLE MEAN. Merely add all of the values and divide by the sample or cell size. Sample 1: Mean = (10 + 8 + 7 + 3 + 1) / 5 = 5.8 Sample 2 is a frequency distribution : Rating Frequency 5 123 4 57 3 86 2 14 1 40 For frequency distributions, it's easier to multiply each value times its frequency - this is the same as adding the value the correct number of times. Sample 2: Mean = (5 x 123 + 4 x 57 + 3 x 86 + 2 x 14 + 1 x 40) / 320 = 1169 / 320 = 3.653 (Note that 320 is merely the sum of the frequencies.) SAMPLE VARIANCE. This is nastier. What you need to do is subtract the mean from each sample value, square this difference, add them all up and divide the sum by the sample size minus one. Sample 1: S2 = [ (10-5.8)2 + (8-5.8)2 + (7-5.8)2 + (3-5.8)2 + (1-5.8)2 ] / 4 S2 = 54.8 / 4 = 13.7 Again, for frequency distributions, we can multiply instead of adding a large number of times. Sample 2: S2 = [ 123 x (5-3.653)2 + 57 x (4-3.653)2 + 86 x (3-3.653)2 + 14 x (2-3.653)2 + 40 x (1-3.653)2 ] / 319

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S2 = 586.496875 / 319 = 1.839

STANDARD DEVIATION. For either case, just take the square root of the variance. Sample 1: The square root of 13.7 = 3.701 Sample 2: The square root of 1.839 = 1.356 STANDARD ERROR. In either case, again, take the standard deviation and divide it by the square root of the sample size. Sample 1: Divide 3.3701 by (square root of 5) = 1.655 Sample 2: Divide 1.356 by (square root of 320) = 0.76 FORMULA USED FOR CALCULATING INTERVAL MEDIANS OR MEDIANS ON GROUPED DATA An interval median is a calculated median based on assigned values rather than on actual values. This is the median calculated for Regular tables (unless you checked ‘Print non-calculated medians’). The non-calculated median routine prints the weight assigned to the stub where the 50th percentile falls. The median for Value tables is the actual (true) median. The formula used for calculating the median for regular tables (with the stub weights assigned being in ascending order from top to bottom) is below. N = Total Number of Respondents IM = Interval Median LB = Lower Boundary of the interval containing the median. This value is found by adding .01 to the value of the stub before the stub containing

the median (see example on the next page). RP = Cumulative number of respondents falling below the stub containing the median. RI = Respondents in the stub containing the median. CI = Class interval (value difference between the two intervals).

RIRP-(N/2)*CI+LB=IM

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Example:

Respondent Stub Weights Count Cumulative Total = 250 1 33 33 2 45 78 3 85 163* 4 50 5 37 * Interval containing the median

N = 250 LB = 2 + .01 = 2.01 RP = 78 RI = 85 CI = 1 The equation becomes:

8578-(250/2)*1+2.01=IM

2.56=2.5629=IM

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APPENDIX 5A

TABLE STATISTICS Before reading this section, please review Tools>Options>Stat on page 119. While Microtab is an extremely effective cross tabulation software program, we make no claim to being a statistical software program. However, we did include some basic statistical testing processes that can be selected when generating tables. On compiled tables, only independent versions of these tests are offered in Microtab. The three tests that can be performed on already compiled tables are:

t-tests (testing independent means for significance), Z-tests (testing pairs of independent stubs for significance), and, Chi-Square tests (testing blocks of independent stubs for significance).

Statistically Speaking: The following is mentioned because we are trying to protect you from yourself. A few things must be understood. On compiled tables only independent testing should be done. Those are the formulas that are in place. As an example, you can accurately compare (specified in the banner) males against females or 18-34 year olds against 35-49 year olds. It would be wrong to compare males against 18-34 year olds because there are most likely males in the study who are 18-34 and you would be comparing some 18-34 year olds against themselves. In an independent test the composition of the two banner points being tested must be mutually exclusive (in other words, independent). Statistically Speaking: The qualifying table parameters for Z-tests and Chi-Square tests are also specific. A legitimate table to be tested is a table without multiple mentions (a respondent should only be ‘shown’ once on the table). This means you should not use the test we provide on any multiple response table. This also means that any table with nets/subnets or a rating/ranking question with detailed counts PLUS a top two or bottom two box (example) stub row should not be tested. Statistically Speaking: Z-tests are used on nominal dichotomous data. That is, answers are actually (or recoded to be) one of two, and only two, categories. Thus the answers might be “yes or no (not yes)”, “red or not red”, “Coca Cola or not Coca Cola” and so on. Then the user has to decide whether or not she/he wants to include the non-response category(ies) into the “not” side of the above. And, if so, which to include — no answer at all, “Gee I don’t know”, DK, etc. The base, however, should only be those in one of the two categories.

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Statistically Speaking: Chi-square tests can be used on the above (and will give exactly the same conclusion as the Z-test) or on nominal multichotomous data, compared between two or more mututally exclusive groups (i.e., gender, income category, educational category) as banner points. Again, to avoid the “huh” response, these data are where respondents pick one, and only one, from several possible answers: which brand do you use most often (can only use one the most), what is your occupational category (can only have one), in which state do you currently live (only one), and so on. Now, once more, the user needs to decide what to do with the respondents who don’t give

a “legal” answer. If they are included in an “all other” category, they are included in the base. Otherwise they aren’t. The program will allow you to test anything you want but the above statements should be taken seriously! Again, the above is mentioned because we are trying to protect you from yourself. The parameters for statistical testing are specified in two different areas of the program:

1. when the banner is established (or edited) to indicate which banner points are to be tested, and

2. when entering or editing table parameters to indicate the range of stubs to be tested.

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Information must be entered in both of the above areas of the program before the program is able to run any of the stat testing routines. Specific statistical testing capabilities are detailed in the following pages.

CHI-SQUARE TESTS

Conducting a Chi-Square test – A chi-square test addresses the question of whether or not a statistically significant relationship exists between two or more banner points and two or more stubs. In other words, a chi-square test is used to examine whether or not a relationship exists between the banner points and the stubs chosen for testing. A chi-square test is neither one-tailed nor two-tailed. You cross tabulate data in order to view relationships between variables. The question that arises is whether the observed relationships are the result of sampling error (random results) or if the relationships are, in fact, statistically significant (real). A chi-square test will help you answer this question. You can perform the chi-square test on as few as two banner points (columns) and/or two stubs (rows). Interpretation: Your chi-square test will provide you with information automatically inserted onto your table. This information will include the chi-square value, the degrees of freedom, and the confidence. A larger chi-square value will lead you to conclude the following: • a relationship does exist in your data, and • the frequency distribution (%) of the stub variables is not the same for all banner points. Banner Prompts: Check the Chi-Square box and then indicate the number of tests that you want to have performed for this banner. A grid of two columns will be displayed. The number of rows presented will equal the number of Chi-Squares you indicated you wanted to perform. Using the banner graphic displayed at the top of the screen, enter the banner point numbers that correspond to the block (starting and ending banner point) you want tested for each Chi-Square. For the first block, enter the left and right banner point numbers that define the block you want to test. Use the arrow keys to navigate through the grid.

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See Appendix 5B for additional information on Chi-square tests.

T-TESTS Conducting t-tests - The t-test for independent means addresses the question of whether or not the means of two independent banner points are statistically different. Dependent t-tests can only be performed using our advanced tables routine. For both dependent and independent t-tests, the t-tests can be either one-tailed or two-tailed. If you are looking only for a difference (any difference) in the numbers, you would specify a two-tailed test. If you feel that the first (or second) banner point should have a number that is higher than the other banner point, you would want a one-tailed test. For the t-test to be meaningful, each banner point (column) should have a respondent count (frequency) greater than 30.

Interpretation: When your generate tables, the t-test results will be footnoted on your table. You can select two confidence levels to test. The confidences that can be selected for a one-tailed test are 99%, 98%, 95%, 90%, 85%, 84.1% (one standard deviation) and 80%. The confidences that can be selected for a two-tailed test are 99%, 98%, 95%, 90%, 85%, 80%, and 68.3% (one standard deviation). Two-tailed test: Where significant differences are footnoted, you can state, for a two-tailed test, that you are N% confident that your means are statistically different. For example, if you have a footnote that shows <D VS H> and you are testing at the 95% confidence level, you can conclude that at the 95% confidence level your means are statistically different. The letters within the brackets (representing the banner points) are presented in descending alphabetic order as the test is only looking to see if a difference exists. The order does not indicate that (example) D is larger than H.

One-tailed test: If you are conducting a one-tailed t-test, the higher mean of a pair will generate a positive t-value. The letters within the brackets (representing the banner points) are presented with the higher (mean) banner point appearing first. The order will indicate that (example) D is larger than H. You can state that you are N% confident that the mean of the banner point on the left is statistically greater than that of the banner point on the right. With a one-tailed test, a negative t-value means that the mean of the banner point on the right is statistically greater than that of the banner point on the left. This would be shown as <H VS D>. When a confidence value of 95% (for example) is selected, you can be sure of the existence of a statistical relationship at all levels of confidence at or below 95%. Given the example of a 95% confidence level, you could conclude that at the 90% confidence level (and for all levels below that) your means are statistically different.

Banner Prompts: Check the t-test box and then indicate the number of banner point pairs that you want to have tested on this banner.

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A grid of two columns will be displayed. The number of rows presented will equal the number of pairs you indicated you wanted to test. Using the banner graphic displayed at the top of the screen, enter the banner point numbers that you want for each t-Test calculation. Use the arrow keys to navigate through the grid.

Z-TESTS

Conducting Z-tests - The Z-test for two independent proportions addresses the question of whether the proportions of a particular response (a single stub) are equal for two independent banner points. A dependent Z-test is not possible. There is no such test as a dependent Z-test. Z-tests can be either one-tailed or two-tailed. If you are looking only for an unspecified difference in the proportions, you would specify a two-tailed test. If you feel that the first (or second) banner point proportion should have a number that is higher that the other banner point, you would specify a one-tailed test. For the Z-test to be meaningful, your proportions should be neither too small nor too large. Even though it is proportions which are of interest, the usual rule is that the frequencies being tested and their complements all must have a minimum respondent count in each cell of at least five.

Interpretation: After you have performed your Z-test, the program will annotate (next to the frequencies which are shown on the table) those proportions which are statistically different. At the bottom of the table (like a footnote), Microtab will insert a legend to indicate that an upper case letter indicates a significant difference at the XX% confidence level, and, if two levels are being tested, an additional line that says “lower case letter indicates a significant difference at the YY% level”. For each upper case letter (and lower case letter if a lower level is tested) inserted in the table, you can conclude that at the N% level of confidence your proportions are statistically different. For example, if a letter (upper or lower case) prints on the table, it means that the corresponding banner point is significantly different at the 95% confidence level and you can conclude that those proportions tested are statistically different. When the program prints a letter representing a confidence level of 95% (for example), you can be sure of the existence of a statistical relationship at all levels of confidence at or below 95%. Given the example above of a 95% confidence level, you could conclude that at the 90% confidence level (and for all levels below that), there is a statistical difference between the two proportions. Special Note: In both cases (one-tail and two tail testing), the letter(s) will always print next to the higher proportion (frequency count).

Banner Prompts: Check the Z-test box and then indicate the number of independent banner point pairs that you want to have tested on this banner. A grid of two columns will be displayed. The number of rows presented will equal the number of Z-tests you indicated you wanted to perform. Using the banner graphic displayed at the top of the screen, enter the banner point numbers that you want for each Z-test calculation. Use the arrow keys to navigate through the grid.

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See Appendix 5C for additional information on Z-tests.

APPENDIX 5B

DETERMINING SIGNIFICANCE CHI-SQUARE

In order to determine the significance level when performing a chi-square test, a chi-square look-up table is used. Determine the matrix for testing A chi-square test is based upon a matrix of answers (defined by a range of 2 or more stubs against 2 or more banner points). Microtab is designed to allow users the utmost freedom in determining the dimensions of the test matrix on their table. For this reason, we would like to provide the following suggestions regarding testing:

1. A chi-square test should only be used on tables where respondents can select only one of the answer choices (single punch).

2. A chi-square test is ideally calculated on a range of banner points that are mutually exclusive (independent).

3. “No answer” stubs that represent respondents who chose not to answer the question (such as no opinion/none of the above) may or may not be included in the test at the client’s discretion. However “No answer” stubs that represent respondents who were not asked the question (i.e. due to skip patterns) are typically not included in the matrix for testing.

The below examples show two different possibilities for matrix selection: Example 1: Musical Preferences

BP 1 BP 2 BP 3 Stub Total Male Female 1 – Total Respondents 1115 561 554 2 – Classical 28 8 20 3 – Country 390 210 180 4 – Gospel 127 72 55 5 – Oldies 20 10 10 6 – Pop 165 75 90 7 – Rock 270 125 145 8 – No answer/no opinion 115 61 54 The proper banner point range for the chi-square test would be banner points 2-3. Banner point 1 would not be included since the total is not mutually exclusive from the male and female banner points. The proper stub range for the chi-square test would be stubs 2-7 or stubs 2-8 depending on the client’s preference.

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Example 2: Reservation Method Preferences BP 1 BP 2 BP 3

Stub Total Small Firms Large firms 1 – Total Respondents 610 290 320 2 – No answer/don’t

make own reservations 28 8 20

3 – Base = Those who make own reservations 582 282 300

4 – Travel agency 127 72 55 5 – Call to airline 20 10 10 6 – On-line direct to

airline site 165 75 90 7 – On-line through

travel search engine 270 125 145

The proper banner point range for the chi-square test would again be banner points 2-3. The proper stub range for the chi-square test would be stubs 4-7. Stub 2 would not be included since these respondents were not asked the question and stub 3 would not be included since it is not mutually exclusive from the other stubs. Special note with regards to nets: The chi-square test is intended for use on tables with mutually exclusive stubs. However, we recognize the practical need for users to include net stubs within some of their single-response questions. Microtab uses the number of individual respondents in the chi-square stub calculations rather than using the number of responses shown on the table. Therefore, nets can be included in the range for statistical testing. Be aware, however, that wherever a net is included, all the respondents in that net are automatically included in the testing, so you must specify stubs for testing which includes the individual responses under that net. For this same reason, unless your selected matrix includes all possible responses on the table, be sure that your selection of stubs does not cross the “Those Answering” stub. Including the “Those Answering” stub in the matrix automatically includes all the respondents answering the table in the bases, so your stub selection would need to include all those respondents as well. Determine the degrees of freedom To find the significance level, you first have to calculate the degrees of freedom. This is accomplished by counting the number of banner points (columns) in the chi-square and the number of stubs (rows) in the chi-square. Subtract one from each number and then multiply them together. The result is the degrees of freedom.

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Example: Your chi-square spans 5 banner points and 7 stubs. Multiply 4 times 6 and you'll get 24 degrees of freedom. Refer to the Chi-Square table and track down the left-most column until you are on that row where the degrees of freedom equals or just exceeds your calculated number. In our example, you can find the exact row. Trace the row to the right until the value listed on the table is bigger than the calculated chi-square. Back-up one column and read the column heading. The percentage at the top of the column is the significance. In our example, still with 24 degrees of freedom, assume we had a calculated chi-square of 39.73. As we trace across the row, we find that the value of 42.9798 in column five is the first value that exceeds the 39.73. Back up one column to the value 39.3641 and at the top of that column, we find the percent 97.5. You can then say that a relationship exists between the banner points and the stubs chosen for testing and that the relationship is statistically significant at the 97.5% confidence level. The chi-square look-up table is after the next page. It is included for informational purposes only. The table matrix is included as part of the Microtab software and the program automatically performs the look-up for you. The formula used for the chi-square test is:

f)f-f(

=e

eo2

2 ∑χ

For k different banner points and m different stubs, fo is the observed frequency at the intersection of each stub and each banner point. The expected frequency for each intersection, fe, is determined by:

where: T = Sum of all the stubs (respondents not responses) within the matrix selected by the user Rm = Total in each stub Ck = Total of all the stub values (respondents not responses) selected by the user under that banner point

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TCxR=f km

e

Chi-Square Look-up Table

Degrees of Freedom 90% 95% 97.5% 99% 99.5% 1 2.70554 3.84146 5.02389 6.63490 7.87944 2 4.60517 5.99147 7.37776 9.21034 10.5966 3 6.25139 7.81473 9.34840 11.3449 12.8381 4 7.77944 9.48773 11.1433 13.2767 14.8602 5 9.23635 11.0705 12.8325 15.0863 16.7496 6 10.6446 12.5916 14.4494 16.8119 18.5476 7 12.0170 14.0671 16.0128 18.4753 20.2777 8 13.3616 15.5073 17.5346 20.0902 21.9550 9 14.6837 16.9190 19.0228 21.6660 23.5893 10 15.9871 18.3070 20.4831 23.2093 25.1882 11 17.2750 19.6751 21.9200 24.7250 26.7569 12 18.5494 21.0261 23.3367 26.2170 28.2995 13 19.8119 22.3621 24.7356 27.6883 29.8194 14 21.0642 23.6848 26.1190 29.1413 31.3193 15 22.3072 24.9958 27.4884 30.5779 32.8013 16 23.5418 26.2962 28.8454 31.9999 34.2672 17 24.7690 27.5871 30.1910 33.4087 35.7185 18 25.9894 28.8693 31.5264 34.8053 37.1564 19 27.2036 30.1435 32.8523 36.1908 38.5822 20 28.4120 31.4104 34.1696 37.5662 39.9968 21 29.6151 32.6705 35.4789 38.9321 41.4010 22 30.8133 33.9244 36.7807 40.2894 42.7956 23 32.0069 35.1725 38.0757 41.6384 44.1813 24 33.1963 36.4151 39.3641 42.9798 45.5585 25 34.3816 37.6525 40.6465 44.3141 46.9278 26 35.5631 38.8852 41.9232 45.6417 48.2899 27 36.7412 40.1133 43.1944 46.9630 49.6449 28 37.9159 41.3372 44.4607 48.2782 50.9933 29 39.0875 42.5569 45.7222 49.5879 52.3356 30 40.2560 43.7729 46.9792 50.8922 53.6720 40 51.8050 55.7585 59.3417 63.6907 66.7659 50 63.1671 67.5048 71.4202 76.1539 79.4900 60 74.3970 79.0819 83.2976 88.3794 91.9517 70 85.5271 90.5312 95.0231 100.425 104.215 80 96.5782 101.879 106.629 112.329 116.321 90 107.565 113.145 118.136 124.116 128.299

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100 118.498 124.342 129.561 135.807 140.169

APPENDIX 5C

DETERMINING SIGNIFICANCE Z-TEST

In order to determine the significance level when performing a Z-test, a Z-test look-up table is used. This table is the same as the t-test look-up table. Determine the range of stubs for testing A Z-test is used to determine if there is a significant difference between two independent banner points and two independent stubs. The only time a Z-Test can be properly used (statistically accurate) is when you have (example) males vs. females in the banner and a yes/no question. In this specific case, those who did not answer yes or no would be removed from the base and would not be included in the range of stubs to be tested. Microtab is designed to allow users the utmost freedom in determining the pairs to be tested on their table. For this reason, we would like to provide the following suggestions regarding testing:

1. A Z-test should only be used on tables where respondents can select only one of the answer choices (single punch).

2. A Z-test should only be used on a pair of banner points that are mutually exclusive (independent).

3. While excluded from traditional Z-tests, “No answer” stubs that represent respondents who chose not to answer the question (such as no opinion/none of the above) may or may not be included in the test at the client’s discretion. However “No answer” stubs that represent respondents who were not asked the question (i.e. due to skip patterns) should not be included in the matrix for testing.

The below examples show two different possibilities for stub selection: Example 1: Store shopped at most often

BP 1 BP 2 BP 3 Stub Total Male Female 1 – Total Respondents 1115 561 554 2 – Store A 28 8 20 3 – Store B 390 210 180 4 – Store C 127 72 55 5 – Store D 20 10 10 6 – Store E 165 75 90 7 – Store F 270 125 145 8 – No answer/no opinion 115 61 54

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The proper banner point pairs for the Z-test would be banner points 2-3. Banner point 1 would not be included since the total is not mutually exclusive from the male and female

banner points. The proper stub range for the Z-test would be stubs 2-7. However, the test could be performed on stubs 2-8 depending on the client’s preference. Example 2: Reservation Method Used for Most Recent Trip

BP 1 BP 2 BP 3 Stub Total Small Firms Large firms 1 – Total Respondents 610 290 320 2 – No answer/don’t

make own reservations 28 8 20

3 – Base = Those who make own reservations 582 282 300

4 – Travel agency 127 72 55 5 – Call to airline 20 10 10 6 – On-line direct to

airline site 165 75 90 7 – On-line through

travel search engine 270 125 145

The proper banner point pair for the Z-test would again be banner points 2-3. The proper stub range for the Z-test would be stubs 4-7. Stub 2 would not be included since these respondents were not asked the question and stub 3 would not be included since it is not mutually exclusive from the other stubs. Special note with regards to nets: The Z-test is intended for use on tables with mutually exclusive stubs. However, we recognize the practical need for users to include net stubs within some of their single-response questions. Microtab uses the number of individual respondents in the calculations rather than using the number of responses printed on the table. Be aware, however, that wherever a net is included, all the respondents in that net are automatically included in the base for testing, so you would typically also specify stubs for testing which include the individual responses under that net. For this same reason, unless your selected range of stubs includes all possible responses on the table, be sure that your selection of stubs does not cross the “Those Answering” stub. Including the “Those Answering” stub in the range of stubs to be tested automatically includes all the respondents answering the table in the bases. Next, you have to determine if you want the test to be one-tailed or two-tailed. ONE-TAILED TEST: If you want to determine if the proportion of the men who answered a question a certain way is higher (or lower) than the proportion of women, then you should perform a one-tailed test. With a one-tailed test, you are testing for direction. You feel that one segment of your sample is higher proportionally than another segment.

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TWO-TAILED TEST: If you are looking for an unspecified (in direction) difference in the proportions, you would want to perform a two-tailed test. By unspecified, we mean (as an example) that you might want to see if the proportion of the men who answered a question a certain way is different than the proportion of women. You don't care which is higher (or lower); you just want to see if there is a difference in the proportions. The one-tailed Z-test values for specified confidence levels are: Confidence Value 99% 2.326 98% 2.054 95% 1.645 90% 1.282 85% 1.036 84.1% 1.000 - One Standard Deviation 80% 0.842 The two-tailed Z-test values for specified confidence levels are: Confidence Value 99% 2.576 98% 2.326 95% 1.960 90% 1.645 85% 1.440 80% 1.282 68.3% 1.000 - One Standard Deviation

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The same formula is used for both a one-tailed Z-test and a two-tailed Z-test. Only the look-up table is different.

The formula used for the Z-test is:

)

n1+

n1p)(-p(1

nx-

nx

=z

21

2

2

1

1

where the proportion (p) is determined by:

)n+n()x+x(=p

21

21

Other variable definitions are: x1 and x2 = the respective stub count under the first and second banner point, and, n1 and n2 = the respective total banner point counts.

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APPENDIX 6

OTHER STATISTICAL ROUTINES

Other statistical routines are sometimes required when analyzing data and we have included a select few as part of the Microtab software. In addition to the independent t-Tests, Z-Tests and Chi-Squares which are performed on compiled data, we offer ANOVA, Repeated measures ANOVA, Independent t-Tests, Dependent t-Tests, Cochran Q and McNemar tests. We have attempted to describe the situations when each type of test should be used. The t-Tests, Z-Tests and Chi-Squares performed on compiled data (on your tables) should be used only if the samples being compared are independent (you cannot have the same respondent in both groups). ANOVA Use ANOVA to compare the means and standard deviations across several groups. For example, you could have the average amount spent for a meal at 10 different restaurant locations. While a t-Test would tell you if there was a significant difference between 2 specific locations, an ANOVA would tell you if there were enough differences for you to say that the average amount spent varies significantly by restaurant location. Repeated Measures ANOVA Use Repeated Measures ANOVA to test means when all members of a random sample have been measured under a number of different conditions. For example, assume you asked respondents about their likelihood to purchase a product both before and after showing a test commercial. Each occasion the likelihood to purchase was asked represents a measurement of the same characteristic (likelihood to purchase) under a different condition (pre and post commercial). A standard ANOVA in this case is not appropriate because the data violate the ANOVA assumption of independence. Dependent t-Test

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The dependent t-Test focuses on the difference between the dependent (paired) data and reports the probability that the actual mean difference is consistent with zero. This comparison is aided by the reduction in variance achieved by taking the differences. For a dependent t-test to be accurate, only respondents who answered both of the questions being asked should be included in the test. If a respondent answered only one of the questions, they should be excluded.

McNemar Test

The McNemar test is a test on a 2x2 classification table when you want to test the difference between paired proportions, e.g. in studies in which respondents serve as their own control, or in studies with "before and after" design. In the McNemar test dialog box, two discrete dichotomous variables with the classification data must be identified. Answer choices are numeric, usually yes/no. The answer choices cannot contain more than 2 different choices. For example, in a certain study a test is performed both before treatment and after treatment in 20 patients. The results of the test are coded 1 and 2. The test will answer the question “Is there a significant change in the test result before and after treatment?).

Dependent Z-Test

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It seemed to us that if you can perform an Independent Z-Test you should be able to perform a Dependent Z-Test. We were wrong. According to statisticians, there is no such thing as a Dependent Z-Test. The test that is usually used for testing for differences in proportions on already compiled tables is called The Bowker Extension of the McNemar Test to a Test of Symmetry in a Square Contingency Table.

APPENDIX 7

RANK ORDERING STUB LINES

Rank ordering stub lines is accomplished easily. A few very simple rules govern the process. First, enter all the stubs for the table (in approximate order) and, if appropriate, with each net followed by its sub-nets and its answers. When entering net and sub-net stubs, remember to include all punches needed to qualify a particular stub for that net or sub-net. Setting up a recode file will be necessary if any stub comes from more than one column. Second, decide if you want the stubs to be ranked in ascending or descending order. Make your selection and click rank order. You will now need to indicate specific rank ordering information. This is accomplished by positioning the stub within the net or sub-net to which it is assigned. If you do not have nets and/or sub/nets, see below for a pictorial of how the ranking screen could look.

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Move stubs up or down by highlighting the stub and clicking the arrow keys shown at the bottom of the screen. In the above example, indentation is not necessary. If you have a stub that you want to print last, highlight that stub and using the arrow keys, position it at the

bottom of the list. Click the red arrow radio button to indicate you want that stub to maintain its current position. Below shows how to indent stubs for a table that has nets only (no sub-nets).

The following example shows how to indent stubs for a table that has nets and sub-nets. All ranking and assignment to specific nets and sub-nets is accomplished by indenting the stubs. In order for a stub set to be ranked as part of a net, it must be indented under the net. If you have a particular stub that you do not want rank ordered (such as a No Answer stub), highlight the stub and click the red radio button on the bottom of the screen so it will maintain its current position. If there is a stub that you wish to print last within a sub-net, highlight that stub and using the arrow keys, position it as the last stub under that sub-net and click the red arrow button.

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When ranking sub-nets, indent the sub-net stub line by using the arrows at the bottom of the screen so it appears under the regular net. This will enable the sub-net frequency count to be separated from the regular net frequency count.

Special Note: If you would like the stubs to print indented under nets and sub-nets on the tables, you must physically indent (using the space bar) each stub on the main stub screen (where you enter the column number and punch). Example 1- Answers only – no nets: Straight Answer Straight Answer Straight Answer Straight Answer Straight Answer Straight Answer

Example 2 – Answers and nets: Specified Net Net Answer Net Answer Net Answer Net Answer Specified Net Net Answer Net Answer Net Answer

Example 3 – Answers & nets/sub-nets: Specified Net Specified Sub-Net Sub-Net Answer Sub-Net Answer Sub-Net Answer Sub-Net Answer Specified Sub-Net Sub-Net Answer Sub-Net Answer Sub-Net Answer Specified Net Net Answer Net Answer

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Net Answer

Occasionally, you might have a situation where you will have a Net that has both Net Answers and Sub-Nets within it. Usually, to make the grouping of responses easier to follow, you will want all of the Net Answers to print first within the Net and for the Sub-Nets (with their corresponding Sub-Net Answers) to follow these Net Answers. To accomplish this, you would use a combination of indenting responses and marking some with the red arrows. In the below example, an * indicates that a red arrow has been used to force that stub to be printed in its current position.

Example 4 – Answers & nets/sub-nets: Specified Net * Net Answer * Net Answer Specified Sub-Net Sub-Net Answer Sub-Net Answer Specified Sub-Net Sub-Net Answer Sub-Net Answer Specified Net Net Answer Net Answer

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APPENDIX 8

RANK ORDERING STUB LINES – A UNIQUE SITUATION

You might need to group a subset of stubs and sub-nets, rank-order them within the group, and also place the entire group in a desired (fixed) position. To accomplish this:

1. Identify (or prepare) a column that is not empty (contains at least a punch) for every respondent.

2. In the Table Parameters screen edit the stubs of the desired table, and append a stub

with certain characteristics:

a . The column number is the column identified (or prepared) at step 1

b. The punch is indicated as "NOT ANSWERED" and the checkbox "don't print if frequency count is zero" is CHECKED;

c. It could be helpful to also give this stub a suggestive label like "GHOST SUBNET").

3. Open the Rank order screen, select the new stub (which should be located at the end of the tree) and maneuver it in the tree until it becomes the parent of the stubs and sub-nets that need to be rank-ordered separately. See the following page.

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Finally, place this entire subnet in the desired position, mark the “GHOST SUBNET” as fixed, and all its children as “movable”.

Now, when printing the table, all the stubs and sub-nets placed within the GHOST SUBNET will print at the end of the NET INGREDIENTS / CONTENT net, but they will still be rank-ordered, as desired.

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APPENDIX 9

HOW TO IMPORT AN EXCEL FILE

An Excel and/or DBF file’s data can be imported into a Microtab data base in different ways. Alternative 1 - How to prepare an Excel file for Microtab use One way to read Excel data into Microtab is to save it as formatted text, space delimited from Excel, and then read it into Microtab as ASCII string data. In order for the data to translate properly, certain conditions must be met:

• The respondent number must be zero filled in the first 4-7 spaces of every row • The last column of data must be filled for every respondent • There should not be any special characters or text fields in the file

Preparing the respondent number:

If a respondent number does not already exist: • Right-click on the heading for column A, then select Insert. • Go to block A1 and type in 1001. (Note: if the number of rows in your database

is more than 9999, start with 10001. If more than 99999, start with 100001, etc.)

• Go to block A2 and type in =1+A1. • Copy the formula in block A2 and then paste it in blocks A3 through A?, where

? represents your last row of data.

If a respondent number already exists: • That number must be zero filled. So, if the first respondent number is 1, the

screen should show 0001. To accomplish this, right-click on the heading for column A, then select Format cells.

• Within the number tab, select Custom. • Within the Type: box, type 0000. (Note: if the highest respondent number you

have is 9999 or less, type 0000. If the highest respondent number you have is 10000 to 99999, type 00000, etc.)

Make sure the columns containing the data contains no leading spaces. To do this: • Left-click on the block above the row label 1 and left of the column label A.

This will highlight the entire spreadsheet. • Select Format from the toolbar at the top of the screen.

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• Select Column, then AutoFit selection

Preparing the last column of Excel data:

If the last column of data has been answered by every respondent: • Ensure that the data is right justified by left-clicking on the letter designating

that column, then selecting the icon for right justify from the toolbar:

If the last column of data has not been answered by every respondent, create a new last column: • Go to the first row of the first available column after your last column of data,

type the number 0, and then press enter. • Right-click on the cell containing the 0, and select Copy. • By dragging the mouse, Paste the 0 into all other rows containing data.

Saving the data

• Choose File from the toolbar and select Save As. • Within the Save as Type box, scroll down and select Formatted Text (Space

delimited) (*.prn) • Select your location, type a file name and click on the Save button.

Alternative 2 – How to prepare an Excel or DBF file for Microtab use The wizard for importing from SPSS and Triple S was extended in order to also support the import from DBF and XLS. Basically, the same steps are required to import from the new sources, with the notable exception of allowing the user to choose the type of the imported variable. This can be done for *.xls files, in the first step of the wizard, by selecting a variable in the list and choosing the variable type (among Single / Multiple / Quantity) from its popup (context) menu – displayed by a right-click. Step by step example: a) Data > Import, the ”Import data” screen is displayed b) Browse for the Excel (*.xls) or *.dbf file c) Select “Create a new study based on the imported data” and then press “Continue”. d) The “Define a new study” screen is displayed, fill in the fields, [check “create default

specs”] and press “Create”.

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Special Note: the controls for specifying the properties of the new study (number of cards, digits for respondent ID and high column number) are disabled. This is because the program automatically adjusts the number of cards required, depending on the number and content of the XLS/DBF variables that are selected for import during the wizard. However, it is true that the number of digits for respondent ID should still be able to be set by the user. Please provide us with feedback in this regard.

e) The “Import data and variables” screen is displayed. The displayed variables are

identified by the program after scanning the imported file.

For a DBF file, each field is considered a variable, the name of the variable being the name of the column. For an XLS file, each column containing some data is considered a variable, the name of the variable being the value in the first row.

The “compatible variables” list has now, in addition to the existing ”type” column (which refers to the original type of the variable, depending on the type of data source), a new column called “Microtab type”. By default, the Microtab type is assumed to be Single (except for the DBF “floating point” types, assumed to be Quantity). The Microtab type of an imported variable can be specified by the user, by right-clicking on the variable and selected the desired type (the options are Single / Multiple / Quantity). For the coded variables (Single / Multiple) the program automatically scans the input file for codes, in order to obtain the list of answer codes of the new Microtab variable. From this point on, the wizard continues exactly as when importing SPSS or Triple S data. See Appendix 10 which follows this section. In it’s current implementation, the Quantity variables are mapped by default into 10 Microtab columns (6 digits + 4 decimals). Maybe this could be refined, if users indicate a desire.

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APPENDIX 10

IMPORTING SPSS *.SAV FILES AND TRIPLE S *.SSS AND *.ASC FILES This appendix includes sections detailing a description of the functionality, examples using sample data files, and our recommendation for the easiest import process. Description: The Add-on module for the Professional Edition of Microtab (2003 and later) versions allows you to import from (and export to) an SPSS or Triple S file:

A. variable definitions and respondent data B. variable definitions only C. respondent data only

Note: An SPSS file (*.SAV) contains both the variable definitions and the respondent data. A Triple S study is comprised of two files with the same name but a different extension: the *.SSS file contains the variable definitions and the *.ASC file contains the respondent data. Variable definitions include: - the name of the variable (ex: “Q1”) - the label of the variable (question text) (ex: “Would you recommend to a friend?”) - the type of the variable (ex: “SINGLE”) - for coded variables, the possible answer codes and their text labels (ex: “1 – Yes” and

“2 – No”) - for uncoded (quantity) variables, the size of the field and the number of decimals (ex: 5

digits, 2 decimals)

For The Easiest Import of SPSS and Triple S Data and Text Files Part 1 – This section outlines a step-by-step process for importing SPSS files. For a more detailed description of the module’s capabilities, see Part 2. We feel that the easiest method for you to use to import *.sav (SPSS) or *.sss and their *.asc (Triple S) files is as follows:

1. While a different study is active in Microtab, click on the red arrow (Import) and then use the browse button to locate the file you wish to import. For SPSS files that will be the *.sav file. For Triple S files that will be the *.sss file. After highlighting and clicking on the file name, you will be returned to the Import data – Step 1 screen. Make sure the radio button next to Create a new study based on the imported data is on and then click on Continue.

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2. You will see a screen titled Define a new study. Enter a unique five digit or five character study identifier. Click on path and after opening the folder where your

study files are stored, click on New folder and give this folder a unique identifier (perhaps the same name as the study identifier) and then click on OK.

3. Returning to the Define a new study screen, enter a description for the study.

Make sure create default column specifications is marked and then click on create.

4. You will then see a screen titled Import variables and data – Step 2. A listing of

all the text questions is displayed. All of the questions are checked for import. If there are any questions you do not wish to import, uncheck them. Click the radio button labeled Allocate new ids starting with the number …. Make sure the button labeled Allocate columns and punches is on. For your information, incompatible variables (if any) are listed at the bottom of the screen. Click on Continue.

5. The next screen (Step 3) shows all the variables to be imported. You can review

and edit their content if you wish. Click Finish and the variables are imported into the Microtab library.

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6. The next screen Imports the data which is either a part of the SPSS *.sav file or in a separate *.asc file with the same leading name as the Triple S *.sss file. The defaults are set to initial data and that duplicate respondent ID numbers should be assigned new record numbers. Click Import and then click on OK. At this point you have imported the data and created a Microtab library of the variable names. Should you wish to use the table creation wizard to convert variables to tables, continue to step 7 below.

7. Click on the V… icon or from the menu bar select Study and then Variables. A

listing of all the variables in the library is displayed. You can select one variable by highlighting it or select all the variables by pressing the letter A while holding down the <Ctrl> key. After highlighting those variables for which you want tables, click on Create tables and you will be shown an Options screen.

8. At the Options screen, you can convert the question text to all upper case and/or

convert the answer text to all upper case. All the tables to be created are checked indicating that you want the program to create stubs weights for means (based on punch values) and will set flags for generating means, standard deviations, standard errors, t-tests and Z-tests for all stubs. Uncheck those tables for which you don’t wish weights to be assigned and stat testing to be performed. These tables will still be created. When everything is as you want, click on OK and all your tables will be instantly created.

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The above is the easiest way to import SPSS and Triple S data and text files. Please contact us if you experience any difficulties.

Part 2 – Detailed description of SPSS and Triple S import functions. A. Both variable definitions and respondent data can be imported from an external file in a single operation. This can be done via Data > Import, and selecting “Create a new study based on imported data”. A step-by-step detailed instruction page for this process is given in Part 1 of this appendix. The SPSS/Triple S import wizard follows the standard pattern for importing data, with a combination of two additional steps: 1) From all the variables found in the imported file, the user selects the ones to be

imported (this time it’s about their content and their specification) into Microtab. Also, the user must instruct the program on the method to be used for allocating respondent IDs to the imported records, before clicking on <Continue>;

2) At this point, the program creates equivalent Microtab variables, making the necessary

conversions and – optionally – allocating columns and punches for the new variables. Still, these are only “proposals” for the new variables – the user is free to modify the definitions of the variables before clicking on “Finish”. However, the new Microtab variables must be compatible to their corresponding external variables in order to be able to import data. Clicking on <Finish> will add the new Microtab variables to the dictionary and then proceed with the standard data import procedure.

B. Variable definitions can be imported via Study > Variables > Import. When Microtab imports variable definitions from an external file, one Microtab variable is created based on each external variable selected to be imported. The import wizard consists of two steps: 1) From all the variables found in the imported file, the user selects the ones to be

imported into Microtab and clicks on <Continue>; 2) At this point, the program creates equivalent Microtab variables, making the necessary

conversions and – optionally – allocating columns and punches for the new variables. Still, these are only “proposals” for the new variables – the user is free to modify the definitions of the variables before clicking on “Finish” to add the variables to the dictionary.

C. Respondent data is imported into Microtab based on variable mappings. If only respondent data is imported, the variables in the external file must be mapped to existing Microtab variables. Respondent data can be imported via Data > Import, selecting “Import data into the current study”. The import wizard follows the standard pattern for importing data, with two additional steps:

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1) From all the variables found in the imported file, the user selects the ones to be imported (this time it’s about their content, not their specification) into Microtab. Also, the user must instruct the program on the method to be used for allocating respondent IDs to the imported records, before clicking on <Continue>. The available options are:

- use the content of a variable; this is useful when the respondent id was saved as a variable, like in the sample file “TEST SPSS.SAV”, or;

- generate a sequence of respondent ids. 2) At this point, the program searches (in the dictionary of the currently open study) for

compatible Microtab variables. For each external variable, the user has to choose – from the list of existing compatible variables – the Microtab variable that indicates the destination (columns/punches) for the imported data. By default, the program will look for a Microtab variable with the same name. If it finds one, the program will select it as the default destination. Still, the user is free to select another variable from the list of compatible variables, and also to change the default code mapping (in case of a coded variable). Of course, if a variable selected to be imported has no compatible Microtab variable in the current study, its content cannot be imported. After all variables are correctly mapped, clicking on “Finish” will continue the standard data import procedure.

Part 3 - Examples Using the attached sample files (“3sSample12.sss”, “3sSample12.asc” and “test spss.sav”), the following scenarios can be tested: 1) Import variable definitions and respondent data from SPSS into a new Microtab

study: - Start the standard data import procedure (Data > Import > Browse) and choose “test

spss.sav”; - Choose “Create a new study based on the imported data” and click on <Continue>. - Fill in the study number and path. The number of cards required to hold the data will

automatically be determined and displayed by the program. Ensure that “create default specs” is selected and then click on “Create”.

- The “import variables” wizard should appear; Click on “Continue”. - Click <Finish>. - The standard data import should continue; click on <Import>. - At this point, both the variable definitions (76) and the respondent data (9 records) are

imported. A new screen (Data > Browse) displays the content of the study data in a “variable” format (as an alternative to the classic “input listing”).

2) Import variable definitions and respondent data from Triple S into a new

Microtab study: - Start the standard data import procedure (Data > Import > Browse) and choose

“3sSample12.sss”; “3sSample12.asc” must be placed in the same directory. - Choose “Create a new study based on the imported data” and click on <Continue>; - Fill in the study number and path. Ensure that “create default specs” is selected and

then click on “Create”. - The “import variables” wizard should appear. Choose “Allocate new Ids, starting

with 1” and click on “Continue”. - Click <Finish>. - The standard data import should continue. Click on <Import>. - At this point, both the variable definitions (7) and the respondent data (3 records) are

imported.

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3) Import only variable definitions from SPSS into a Microtab study: - Open a study that doesn’t have yet the variables contained in “test spss.sav” (or create

a new one). - Select Study > Variables > Import and choose “test spss.sav”. - The “import variables” wizard should appear. - Click on “Continue”. - Click <Finish>. 4) Import only variable definitions from Triple S into a Microtab study: - Open a study that doesn’t have yet the variables contained in “3sSample12.sss” (or

create a new one). - Study > Variables > Import and choose “3sSample12.sss”. - The “import variables” wizard should appear; choose “Allocate new Ids, starting with

1” and click on “Continue”. - Click <Finish>. 5) Import only respondent data from SPSS into a Microtab study: - Open a study that has stored the definitions of the variables contained in “test

spss.sav”. - Start the standard data import procedure (Data > Import > Browse) and choose “test

spss.sav”. - Click on <Continue>. - The “import variables” wizard should appear; Click on “Continue”. - Click <Finish>. - The standard data import should continue. Click on <Import>. - At this point, the respondent data (9 records) are imported. 6) Import only respondent data from TRIPLE S into a Microtab study: - Open a study that has stored the definitions of the variables contained in

“3sSample12.sss”. - Start the standard data import procedure (Data > Import > Browse) and choose

“3sSample12.sss”. - Click on <Continue>. - The “import variables” wizard should appear. Click on “Continue”. - Click <Finish>. - The standard data import should continue. Click on <Import>. - At this point, the respondent data (3 records) are imported.

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APPENDIX 11

VARIABLE NAMES VERSUS COLUMN NUMBERS Since 1982 every offering of Microtab Cross Tabulation Software has used columns and punches to address the locations of specific cell counts (example: male/female). Starting with the 2003 release of Microtab, you can use variable names instead of column numbers. Rather than specifying that the data you wish to report is located in column 109 punch 1 you can specify that the desired data is in (example) variable ‘tbs’ with a location of ‘one’. The column numbers will still be displayed but by using the data map that can be printed from Study > variables you can confirm your work. To access the variable names, click on the V underlined by the ellipse […] that is to the right of the blank space allocated for column numbers.

You do not have to use variable names. You can still use columns and punches.

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Every sub-sample qualifier, regardless of the Microtab program/routine, permits you to use variable names. Additional availability (other than sub-sample qualification) of variable use (programs/routines) are shown below.

Columns > Column Addition

Columns > Value Field Addition

Columns > Recode Data

Columns > Recode Specific Numeric Values

Columns > Recode Numeric Ranges

Columns > Clean Data

Columns > Copy Data

Columns > Spread Data

Summary > Marginals

Summary > Arrays

Summary > One By Ones

Weighting > Weighting Files

Weighting > Sample Balancing

Banner > Banner Qualifiers

Tables > Regular Tables

Tables > Advanced Tables > Add Tables

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Report > Filter Tables

APPENDIX 12

CREATING *.SAV FILES WITH Ci3

Sawtooth Technologies, Inc. has commands in their Ci3 software that permits a user to output data, variable names, and the text for the questions and their answers in SPSS *.sav format. Sawtooth Technologies, Inc. has provided the below instructions that should be used to create a *.sav file from their Ci3 software. For further clarification, contact Sawtooth Technologies, Inc. at 847-239-7300. LOCATE (LOC) The Locate command must be used in all questions for which the user would like to export value labels. There is only one type of question that requires the use of Locate, and that’s the Select question (single or multiple choice), for all others, like Numeric etc., it’s optional.

Description: The LOC instruction is used to indicate answer text positions for highlighting and other purposes. The LOC instruction MUST be used in questions:

• that have a SELECT (SEL) instruction (which permits selection from a list), and • in those with a NUMERIC (NUM) instruction (which accepts a numeric answer) or

KEY instruction (which accepts a single keystroke) if there is to be:

highlighting (with the HIGHLIGHT (HLA) instruction), deleting (with the DELETE (DLA) instruction), saving of answer text (with the SAVE instruction), or exporting of answer choice labels to a file for use with other software programs using the Export labels option of Utilities.

The LOC instruction must precede the question-type instruction.

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For questions with SELECT (SEL) instructions, LOC’s final argument (NATURAL or REVERSE) must be NATURAL. In questions with SELECT (SEL) instructions, numbers are usually not used to identify answer choices. Ci3 issues an error in Test mode Don’t save data if text placement arguments and LOCATE (LOC) instruction arguments disagree.

See also:

DELETE (DLA), which deletes the text of answer choices and requires a LOC instruction,

HIGHLIGHT (HLA), which highlights the text of answer choices and which

requires a LOC instruction, KEY, a question-type instruction which accepts single-keystroke answers and

requires a LOC instruction if the DELETE (DLA), HIGHLIGHT (HLA), or SAVE instructions are written with it,

NUMERIC (NUM), a question-type instruction that accepts a numeric answer and

requires a LOC instruction if the DELETE (DLA), HIGHLIGHT (HLA), or SAVE instructions are written with it,

SAVE, which saves text associated with answers and requires a LOC instruction,

and

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SELECT (SEL), a question-type instruction that permits the selection of answer choices from a list and which requires a LOC instruction.

APPENDIX 13

CREATING TRIPLE S FILES FROM CfMC SURVENT AND WEB SURVENT AND

CREATING *.SAV FILES FROM ACS’s QUERYWEB AND WINQUERY

Computers for Marketing Corp. (CfMC) has a utility that permits the user to output data, variable names, and the text for the questions and their answers in Triple S *.sss format. It requires version 76 or higher and it is found in the REFORMAT utility. Contact CfMC at 415-777-0470 or by e-mail at support@cfmc.com. The Analytical Group has available a standalone module that permits a user to output data, variable names, and the text for the questions and their answers in SPSS *.sav format. Contact The Analytical Group, Inc. at 480-483-2700. You will also be able to work directly with files created by SPSS (*.sav files). Other software companies also say they can export files in Triple S format. Two we are aware of are Quanquest (a part of SPSS) and Pulse Train Ltd. (561-842-4000).

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APPENDIX 14

ADVANCED CHARTING CAPABILITIES CHART > Options > Advanced Options - allows you to edit any and all of the details of your chart regarding layout.

Click on the Advanced Options button to access all of the options listed below. Chart - Series – allows you to add, delete, title, clone, and change a different series of charts Chart – Axis – Scales – the scales can be made visible or they can be inverted by clicking on those buttons

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Chart – Axis – Title – Style – you can choose a title for your axis, angle it up to 360 degrees, size it, and make it visible or not. See screen shot on next page.

Chart – Axis – Title – Text – the font on the axis title text can be changed by clicking the font tab. The font style, color, size and script can be modified. By clicking the gradient tab, the gradient editor appears. The axis title text can be made visible with the option of selecting default backgrounds, colors, and options to balance the title color. The shadow tab when accessed brings up the shadow editor. This allows you to shadow your axis title text. You can color, size, and make smooth. See below.

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Chart – Axis – Label – The style tab allows for labels to be visible, multi-lined, round first, label on axis, and alternate row of labels if wanted. The format tab allows you to choose your value format. The text tab allows the usual editing of the font style, size, color and script. The gradient, shadow, and outline tabs are also available.

Chart – Axis – Ticks – accessing the axis tab allows the border editor to appear. Here you can make visible a border for the axis, the border can be colored, sized, and styled by clicking the tabs for those options. There is a tab labeled grid. A border editor appears when the grid tab is viewed. The grid lines can be styled, colored, and sized. Clicking the tab labeled centered, centers the grid lines. There is also an option of having ticks. Again, a border editor appears and allows you to make visible tick marks, which can also be colored, sized and styled. You can have inner ticks as well. The same procedure is followed with the border editor. There is a tab labeled len. This tab allows you to size the length of the tick marks. Chart – Axis – Minor - accessing the tick mark tab brings up border editor. Here you have access to minor ticks when the visible tab is checked, which can be colored, sized, styled. The minor ticks can also be lengthened. A grid tab is also available, when accessed border editor comes up. The grid can be made visible along with color, style, and width size. There is an option also to count the grid lines you would like. Chart – Axis – Position – the axis can be positioned (left, right) to a specified percentage. There is a start tab that lets you position from the start of the axis. The end tab allows you to position from the end of the axis. Chart – Titles – Style – the title, sub-title, sub-foot, & foot can be made visible by checking the visible tab. You can also align them right, center, or left on the chart.

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Chart – Titles – Position - you can custom position the title where you want it. Click the custom button. There are also tabs for left and top movements. Chart – Titles – Format – you can frame the title by clicking frame tab. The border editor appears. Here you can make the border visible, add color, size it, and add a style to it. Choosing the pattern tab, the pattern color editor appears. This allows you to select a designed pattern background of the title. You can color it as well. If you want other images from a different file just click browse. The frame can also be beveled. You can also size it. To round the frame, just click or make it transparent.

Chart – Titles – Text - the font on the title text can be changed by clicking the font tab. The style, color, size and script can be modified. By clicking the gradient tab the gradient editor appears. The title can be made visible with the option of selecting default backgrounds, colors, and options to balance the title color. The outline tab allows for the title to be outlined. The border editor comes up and you can make visible the outline, color, and size it. The shadow tab when accessed brings up the shadow editor. This allows you to shadow your title. You can color, size, and make smooth. Charts – Titles – Gradient - clicking the visible button allows for the title appearance to be on a slope or incline. You can choose a default background. You can choose the color you want by clicking the color tab. A color palette is available for choosing your color. If you do not want a middle color click the no middle tab. There is a swap tab that enables you to exchange the colors. The options tab enables you to balance the colors. Charts – Titles – Shadow – This tab allows you to shadow the title.

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Chart – Legends – Style - the legend can be made visible or invisible. You can invert the legend. Also, you can color the letters. The option of choosing a legend and text style is

available. There is a tab for dividing lines, click this and the border editor appears. The option of the lines can be made visible, with color, style, and sized.

Chart – Legend – Position – the legend can be positioned either left, right, top, or bottom. The chart can be resized along with margins. The position of the legend can be offset by percentages. Chart – Legend – Symbols – the symbols can be made visible or not. The width of the symbols can be sized. They can also be positioned to the left or right on the legend. A tab labeled width units can be clicked to access pixels or percentages. The continuous tab allows for no spacing between the symbols. The squared tab allows for the symbols to be square shaped. If you want a border, just check the default border tab. However, you can uncheck the tab and then access the border tab. At this point, border editor appears and you can make the border visible, change its color, size, and style. Chart – Legend – Title – there is an option tab where you can create a title text for the legend. The text can be aligned and made visible. Chart – Legend – Title – Format - the format tab allows for the title text background to have color (click the color tab). Accessing the framed tab brings up the border editor which allows you to put a border to surround the title. You may also choose the style, color, and width of the border. You may select a pattern by clicking the pattern tab. Color is also available. The title also has the option of being beveled - just click the beveled tab. The option to size the bevel portion of the title is available - just click size. To round the frame, click the round frame tab. If you click the transparent tab, the label will be clear. You are able to shadow the title as well using the transparency tab. It appears as if the image can be seen through or light transmitted. The transparency can be sized as well.

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Chart – Legend – Title – Text - the font on the legend title can be changed by clicking the font tab. The style, color, size and script can be modified. By clicking the gradient tab the gradient editor appears. The title can be made visible with the option of selecting default backgrounds, colors, and options to balance the title color. The outline tab allows for the title to be outlined. The border editor comes up and you can make visible the outline, color, and size it. The shadow tab when accessed brings up the shadow editor. This allows you to shadow your title. You can color, size, and make smooth. Chart – Legend – Title – Gradient - clicking the visible button allows for the title appearance to be on a slope or incline. You can choose a default background. You can choose the color you want by accessing the color tab. A color palette is available for choosing your color. If you do not want a middle color click the no middle tab. There is a swap tab that enables the colors to exchange around. The options tab enables you to balance the colors.

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Chart – Legend – Title – Shadow - this makes the title appear to have a mirrored image or reflection. You can add color by clicking the color tab and choosing from the color palette if preferred. You can also size the image either vertically or horizontally. There’s a transparency tab if you prefer this option. The smooth tab gives the title an even consistency.

Chart – Legend – Format – this tab allows you to color (access color tab) the entire background of the legend. Accessing the framed tab bring up the border editor which allows for a border to surround the legend. You may also choose style, color, & width of the border. You may select a pattern by clicking the pattern tab. Color is also available. The legend also has the option of being beveled. Click the beveled tab. The option to size the bevel portion of the legend is available just click size. You can round the frame by clicking the round frame tab. If you click the transparent tab makes the label clear. You are able to shadow the legend as well using the transparency tab. It appears as if the image can be seen through or light transmitted. The transparency can be sized as well.

Chart – Legend – Text – you can change the font for the legend text by clicking the font tab. The style, color, size and script can be modified. By clicking the gradient tab the gradient editor appears. The legend text can be made visible with the option of selecting default backgrounds, colors, and options to balance the title color. The outline tab allows for the legend text to be outlined. The border editor comes up and you can make visible the outline, color, and size. The shadow tab when accessed brings up the shadow editor. This allows you to shadow your legend text. You can color, size, and make smooth. See the following page for the options.

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Chart – Legend – Gradient - clicking the visible button allows for the legend appearance to be on a slope or incline. You can choose a default background. You can choose the color you want by clicking the color tab. A color palette is available for choosing your color. If you do not want a middle color click the no middle tab. There is a swap tab that enables the colors to exchange around. The options tab enables you to balance the colors. Chart – Legend – Shadow - this makes the legend appear to have a mirrored image or reflection. To add color, click the color tab and choose from the color palette. You can also size the image either vertically or horizontally. There’s a transparency tab if you prefer this option. The smooth tab gives the legend an even consistency. Chart - Panel - a background tab is available to allow one to color the entire background of the chart. There is also a default tab, when accessed just gives a default background. There is a back image tab that allows for you to choose an image from another file location by browsing. Chart – Panel - Borders – the whole chart panel is bordered. The panel can be beveled with inner or outer borders by raising, lowering, or having none. The bevels can be sized and separated. Accessing the border tab, border editor appears, this allows for the entire border of the chart panel to have a border visible with the options of coloring, sizing, and styling it. Chart – Walls – Walls can be made visible by checking the visible walls button. You can choose the tabs left, right, bottom, or back. You also have options of choosing color, a border, patterns, or making the walls gradient. There are various other functions noted for creating a wall. They include 3-D, transparency, auto hide, and sizing.

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Chart – 3D – the option tab allows one to select 3 Dimensions by clicking the tab. You can also give it a certain percentage appearance. Accessing the orthogonal tab, it appears as though there are right angles. The angles can also be sized. There is an option also, zoom test. A zoom tab allows you to zoom in on the whole chart. The chart can be horizontally and vertically offset. Chart – 3D – View – this allows for the chart to have different 3D views.

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Series – Format – Format - Style – Change the style of the bar graphs to different shapes by clicking the drop down arrow. Border – clicking this tab will bring up border editor. In this particular box, you can choose if you want a border around the bars or not. Click the visible bar if you do. Remove the check if you do not. You can also choose a border style by clicking the down arrow box under style. There are options allowing you to change the color of the border and the width size as well. Color – clicking the color each tab allows for the graphs to be different colors. Removing the check mark from the tab allows the graphs to be the same color that is noted. You can also click the color pallet to choose a different color for background of graph. Choosing the pattern option allows you to switch to different patterns of the bar. You can change background color as well by clicking the pattern color editor. Accessing the gradient editor default tab allows changes to different gradient patterns as well. The color tab allows changing of colors. If a middle color is not needed just click the no middle bar. The direction tab allows you to change the direction of the color format. The option tab allows you to balance the colors on the chart.

Clicking the tick lines tab brings up the border editor again. Clicking the visible tab allows lines to be inside the graphs. You can choose the options of styles, colors, and width sizes as well. There is also an option to dark bar the 3-D sides as well. Just click the tab. To remove, unclick.

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Series – Format - Size – This tab allows you to be able to change the width and depth size of your graph. Series – Stack – Allows multiple bar stacked Series – General – click the tab show in legend if you want the legend to appear on the chart or not. Format - Changes the decimal location of the values or percentages. The horizontal axis tab allows for the legend to be printed at the top, bottom or top & bottom of graph bars. Vertical axis allows for the scale to be rearranged either on the left, right, or left & right. If you want the option of date times, click the date time tab. Sort tab the graph bars can be sorted in ascending or descending order according to the percentage.

Series – Marks – Style - check the visible and all series visible box, you are able to see the labels on the graph. Clicking the style tab allows you to choose different labels for the bar graphs. (i.e. percentages, values, labels, labels & percentages, etc.) Clicking the draw every tab allows one to put a label on every 1,2 3, etc. bar graph. The angle tab allows you to angle the labels to certain degrees. Series – Marks – Arrows – clicking the border tab, you are able to make the lines from the labels pointing to the graphs visible or invisible by clicking the visible tab. There are also the options of style, color and width to choose. The pointer tab allows for a pointer to be visible at the end of the line from the labels. You can choose a style and select the height & width of the pointer by clicking those tabs. The tab Arrowhead allows you to put an arrow as your pointer as well as size it.

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Series – Marks – Symbol – Format - allows for little symbols (squares) to be added to the label. Clicking the framed tab bring up the border editor which allows for a border to surround the symbols. You may also choose style, color, & width of the border. You may select a pattern by clicking the pattern tab. Color is also available. The symbols also have

the option of being beveled. The option to size the symbol is available just click size. The frame can be rounded by clicking the round frame tab. Check the transparent tab to make the label clear. You are able to shadow the symbol as well using the transparency tab. It appears as if the image can be seen through or light transmitted. Series – Marks – Symbol – Gradient – clicking the visible button allows the symbols to appear on a slope or incline. You can choose a default background. You can choose the color you want by clicking the color tab. A color palette is available for choosing your color. If you do not want a middle color click the no middle tab. There is a swap that enables the colors to be exchanged. The options tab enables you to balance the colors.

Series – Marks – Symbol – Shadow – This makes the symbols appear to have a mirrored image or reflection. A color can be added by clicking the color tab. You can also size the image either vertically or horizontally. There’s a transparency tab if you prefer this option. The smooth tab gives the symbol an even consistency. Series – Marks – Format – gives the background of the labels color by clicking the color tab. Clicking the frame tab allows for the border editor to appear. This allows for the labels to be framed with a border if wanted, and the option of choosing a style, color, and sizing the frame. The pattern tab allows for a particular diagram or design to be chosen for the background of the label. You may also choose a color. The image tab is available also. You can click clear if you want to clear the selected pattern and browse if you want to select from another file. Click bevel tab to make the label appear to be at an angle or incline. You can size the label as well. The round frame tab allows the frame to be rounded. The transparent tab removes the frame from the label if checked. The transparency tab sizes the reflective image of the label.

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Series – Marks – Text – this allows for the font to be changed on the label by clicking the font tab. Here you can change the font, font style, size, color and script. The gradient tab

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allows the gradient editor to appear as well. The text can be visible with the same gradient defaults, colors, and options. To do this, click the outline gradient tab. The outline tab brings up the border editor. The text again can be visible with color, style, and size. When the shadow tab is clicked a shadow editor appears. Here again, color, size, transparency and smoothness can be accessed. The spacing on the text can be changed also. Just decide how many spaces you will increase or decrease the text. Series – Marks – Gradient – making the gradient tab visible, you can choose whatever default, color, options, and the direction you want for the label. Series – Marks – Shadow – you can shadow your label with color, size, smoothness, and making transparent if wanted. Themes – you can preview different background themes for charts and also the colors for the chart background. You will also be able to preview the chart in 3-D. Just click the 3-D button. An example is shown below.