Getting Started with IBM SPSS Stats 20Presented by: Rosey Zackula

Center for Biostatistical CollaborationOffice of ResearchTuesday, October 23, 2012

THE RESEARCH PROCESS

(1) Turn idea(s) into research question(s)

(2) Review the literature

(3) Design study and develop method(s)

(4) Write proposal

(5) Address

funding issues

(6) Obtain approval

(7) Collect data

(8) Analyze and interpret data

(9) Evaluate

implications

(10) Report and disseminate

findings

http://www.rdinfo.org.uk/flowchart/Flowchart.html

COURSE OBJECTIVES

I. Become familiar with the SPSS systemII. Establish methods for reporting resultsIII. Explore steps for analyzing a datasetIV. Demonstrate the analysis process*V. Hands on exercise*

* All examples are from Windish and Diener-West, 2005

I. WHAT IS IBM SPSS STATS 20?

• Comprehensive system for analyzing all types of data

• Suite of software tools• Primary purpose

• Generate tabulated reports• Produce charts• Plot distributions and trends• Conduct descriptive statistics• Perform complex statistical analyses

IBM SPSS System

• 16+ Analysis Tools– Statistics Base– Advanced Statistics– Bootstrapping– Categories– Complex Samples– Conjoint– Custom Tables– Data Preparation– Decision Trees

• Cont’d– Direct Marketing– Exact Tests– Forecasting– Missing Values– Neural networks– Regression– AmosAND– SamplePower

Manuals for SPSS

SPSS Help and Support

• Help features in SPSS• SPSS Manuals

– S:\SPSS Manuals\SPSS 20• IBM Corp. Web site

– http://www.ibm.com/support• USENET discussion group

– comp.soft-sys-stat.spss • Center for Biostatistical Collaboration

II. ESTABLISH METHODS FOR REPORTING RESULTS

• What style is required?– Check target journal for manuscript– Example JGIM

• Modify SPSS output– Edit > Options

• Output labeling• Adjust fonts/formats

– Table and Charts• Copy special formats (for copying into manuscript:

Word, Excel, etc.)

III. STEPS TO ANALYZE DATA

Step 1: Set up

Step 2: Inspect

Step 3: Clean

Step 4: Describe

Step 5: Analyze

Step 1: Set up data

• Enter manually• Import

– Database• Excel, Access, REDCap, Text

– Read text• Copy and paste (not advised)

Data considerations

• SPSS Types– Numeric, comma, dot, scientific notation, date, dollar,

custom currency, string, restricted numeric (non-negative integer with leading zeros, i.e. 000001)

• Values– Example: categorical variables

• 0 = No; 1 = Yes

• Measures– Nominal, Ordinal, Scale (data that can be multiplied

with meaningful results)

Step 2: Inspect data

• Role– Input, Target, Both, None, Partition, Split

• Defining variable properties– Data attributes– Custom tables

• Multiple response: define variable sets (surveys)• Utilities

– Variable information– Data file comments– Define/use variables sets

Step 3: Clean data

• Data preparation– Validation

• Identify missing information, unusual cases, etc.– Restructure data

• Transform (recoding)– Visual Binning– Create new variables

• Compute, recode, replace missing values– Remember to define any new variable properties and

attributes

Step 4: Describe data

Summarizing categorical data– Tables

• Dichotomous: proportions• Nominal: relative frequencies (percent of total)• Ordered: median (interquartile range)

– Graphs• Bar and pie charts

– Percentages vs. Counts

Step 4: Describe data (cont’d)

Summarizing continuous (scale) data– Tables

• Parametric or normal distribution: Mean (standard deviation)

– Test of normality» Kolmogorov-Smirnov “vodka test”

• Nonparametric test: 1-Sample K-S» K-S Lilliefors (by group)

• Explore: Plots• Nonparametric: Median (interquartile range)

– Graphs• Histograms, line charts, scatter plots

Step 5: Analyze the data

• What is the study design?• What is(are) the research question(s)?

– Hypothesis to be tested• What is the outcome?

– What shape/type of distribution?• Are any groups being compared?• What are the variables of interest?

– What shape/type of distribution?– Predictors or confounders?

IV. DEMONSTRATION

• Study design: randomized clinical trial to evaluate 1-month curriculum

• Compare performance of two unpaired groups (intervention and control)

• Outcome: composite number of maneuvers performed correctly

• Hypothesis 1 – Ho: Participants and controls do not differ in

mean number of correct maneuvers

V. YOUR TURN

• Open SPSS– File > Open Database > New Query…

• Database Wizard: Excel Files > Next• Browse…

– S:\Everyone\Intro_IBM SPSS_Oct 23– Intro IBM SPSS_Test data_Windish article.xlsx– Retrieve all Fields > Next > Next– GENDER: Recode to Numeric

» Minimize string widths > Finish

Your turn (cont’d)

• Establish output options per author instructions from target journal– Edit > Options

• Define Variables– Data > Define Variable Properties– Variable View

• Type, Width, Decimals, Labels, Values, etc.

• Choose hypothesis to test– See article Windish and Diener-West, 2005 Hypothesis

2, 3 or 4 (data are not the same; therefore, results may differ)

THE GRANDMA CLAUSE

You do not really understand something unless you can explain it to your grandmother. 

Albert Einstein

Statistical Results

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Reference

• A Clinician-Educator’s Roadmap to Choosing and Interpreting Statistical Tests. Windish and Diener-West, 2005– http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1924630/

– Important downloads from the article:• Table 1: Questions to Consider When Selecting

the Appropriate Statistical Test• Appendix A: Diagrammatic Approach to Choosing

Summary Measures, Statistical Tests and Methods• Appendix B: Glossary of terms