Table of Contents · NESUG&2012&PROCEEDINGS! Coders'&Corner& ClaudineLougee,’ Dualenic,LLC , ChristopherBattiston,’ HospitalforSickChildren , Coders

NESUG 2012 PROCEEDINGS

Programming: Beyond the Basics Robert Schechter, PharmaNet/i3 Parag Shiralkar, eClinical Solutions This section will present abstract submissions that address a broad spectrum of advanced SASR topics, including ODS, Macro, PROC Report, SQL, JMP, and sophisticated, efficient DATA step and PROC step programming. Other objectives of this section include presentation of new features available as a part of SAS 9.2 and SAS 9.3 versions and innovative problem solving techniques using SAS applications. Topics include, but are not limited to, the use of SAS components to address advanced analytical, reporting, data mining, and data management applications. The objective of these tutorial-‐style presentations is to provide a deeper, practical understanding of key SAS features and behaviors that can make the attendee a more efficient, valuable SAS programmer. Interesting Technical Mini-‐Bytes of Base SAS®—From DATA Step to Macros

Airaha Chelvakkanthan Manickam, Cognizant Technology Solutions

BB1

Loading Metadata to the IRS Compliance Data Warehouse (CDW) Website: From Spreadsheet to Database Using SAS® Macros and PROC SQL

Robin Rappaport, Internal Revenue Service -‐ Research, Analysis, and Statistics Jeff Butler, Internal Revenue Service -‐ Research, Analysis, and Statistics

BB2

Using Axes Options to Stretch the Limits of SAS/GRAPH® Template Language

Perry Watts, Stakana Analytics

BB4

Automatically Generating SAS® Code from Client Specifications

Stanley Legum, Westat

BB5


An Efficient Method to Create a Large and Comprehensive Codebook

Wen Song, ICF International Kamya Khanna, ICF International Baibai Chen, ICF International

BB6

Some _FILE_ Magic

Mike Zdeb, U@Albany School of Public Health

BB7

Data Validation and Transformation in ETL Processing with Help of Perl Regular Expressions in SAS®

Val Volovik, Alliant, LLC

BB8

Dynamic Data Processing Using Data-‐Driven Formats and Informats

Jedediah Teres, MDRC

BB9

SAS® and R Working Together

Matthew Cohen, Wharton School

BB10

There’s an App for That: It’s Called SAS® ODS! Mobile Data Entry and Reporting via SAS ODS

Michael Drutar, SAS Institute Inc.

BB11

Using PROC TABULATE and ODS Style Options to Make Really Great Tables

Wendi Wright, CTB McGraw-‐Hill

BB12

A Paperless Report Generation and Distribution System

George Sharrard, GPS Corp

BB13


Use the Full Power of SAS® in Your Function-‐Style Macros

Mike Rhoads, Westat

BB14

Adding Control to Your Data Using SAS® System and Dataset Options

David Franklin, TheProgrammersCabin.com

BB15

Publishing SAS® Metadata Using Macros, PROC SQL and Dictionary Tables

John Fahey, Reproductive Care Program of Nova Scotia Barry Campbell, Reproductive Care Program of Nova Scotia

BB16

An Introduction to Perl Regular Expressions in SAS® 9

Selvaratnam Sridharma, U.S. Census Bureau

BB17

Rounding Up the Stragglers: Dynamically Detecting and Processing All Existing Data Sets

Adam Miller, Management Science Associates, Inc.

BB18


Coders' Corner Claudine Lougee, Dualenic, LLC Christopher Battiston, Hospital for Sick Children Coders' Corner includes brief presentations to give presenters an opportunity to show off their "magic" skills or "trick" code in a fast paced or demo-‐like environment. The presentations, which are only 10 minutes in length, allow for a snapshot of the topic giving novices to experts a flavor for different aspects of SAS®. Topics can range from ODS output to PROC SQL to SAS/Graph to Enterprise Guide or any programming skills related to using SAS. This section gives plenty of opportunity for any user to walk away with practical, useful information that can be applied immediately. Kick It Old School—Creating Reports with the DATA _NULL_ Step

Sai Ma, PharmaNet/i3 Suwen Li, Everest Clinical Research Services Inc. Minlan Li, Everest Clinical Research Services Inc.

CC1

Not Dividing by Zero: Last of the Low-‐Hanging Efficiency Fruit

Bruce Gilsen, Federal Reserve Board

CC2

With a Trace: Making Procedural Output and ODS Output Objects Work For You

Louise Hadden, Abt Associates Inc.

CC3

Penetrating the Matrix

Justin Smith, U.S. Census Bureau William Zupko, U.S. Census Bureau

CC4

Exploring the PROC SQL _METHOD Option

Kirk Paul Lafler, Software Intelligence Corporation

CC6

Checking Out Your Dates with SAS®

Christopher Bost, MDRC

CC7

Mike Zdeb

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Writing Flexible SAS® Codes: Exploring the Value of Global Macro Variables, Conditional Statements, and %SYSFUNC

Victoria Porterfield, Rutgers University

CC8

Accessing SAS® Code via Visual Basic for Applications

Jennifer Davies, Z, Inc

CC9

A Practical Application of PROC GPLOT and PROC GCHART and Annotate to Clinical Trial Data

Tulin Shekar, Merck & Co., Inc.

CC10

Checking for Duplicates


CC11

Using PROC FCMP to Solve Rolling Regression Rapidly

Chao Huang, Oklahoma State University Liang Xie

CC12

Using SAS® to E-‐Mail Reports and Results to Users

Stuart Summers, Alliant, LLC

CC13

Using PROC SQL and the SAS® Macro Facility to Blind Formatted Dates on a Group of Datasets within a Single Directory

Diana Ventura, Harvard University

CC14

Store and Manage Routinely Extracted Observations: A Practical Application

Si Gao, State University of New York -‐ Albany Xin Li, State University of New York -‐ Albany

CC16


Create User-‐Defined Formats: Using SAS® Code to Write Code

Yonghong Shang, Westat

CC17

Correcting for Natural Time Lag Bias among Non-‐Participants in Pre-‐Post Intervention Evaluation Studies

Gandhi Bhattarai, UnitedHealth Group

CC18

The SAS® System Generates Code for You While Using File IMPORT and EXPORT Procedures

Anjan Matlapudi, Amerihealth

CC20

Careful Use of Input Delimiters

Howard Schreier, Howles Informatics

CC23

Managing SAS® Dates with Irregular Granularity

Howard Schreier, Howles Informatics

CC24

You Have SASMAIL!

Rajbir Chadha, Cognizant Technology Solutions

CC25

Multitasking with Nested Formats

Jonathan Kerman, Johns Hopkins Bloomberg School of Public Health

CC26

A Macro to Squeeze SAS® Data and Create a SAS Transport File

Hany Aboutaleb, Biogen Idec

CC27

Mimicking the DATA Step Dash and Double Dash in PROC SQL

Arlene Amodeo, Law School Admission Council

CC28


Using SAS® to Control the Postprocessing of MS Documents

Nat Wooding, J. Sargeant Reynolds Community College

CC29

Yes, No, Maybe So: Tips and Tricks for Using 0/1 Binary Variables

Laurie Hamilton, Healthcare Management Solutions LLC

CC30

%ASSERT Your Way to Sleep-‐Filled Nights: A One-‐Line Macro for Data Validation

Quentin McMullen, Siemens Healthcare

CC31

Calculating Questionnaire Scores Made Easy in SAS®

Qin Lin, ACI, LLC

CC32

Analyze and Manage Your Output with PROC MEANS

Si Gao, State University of New York -‐ Albany Xin Li, State University of New York -‐ Albany

CC33

Fun with PROC SQL

Darryl Putnam, CACI, Inc.

CC34

Summing Data with the SUM Function in SAS®

Anjan Matlapudi, AmeriHealth Daniel Knapp, AmeriHealth

CC35

Sorting a Large Data Set When Space is Limited

Selvaratnam Sridharma, U.S. Census Bureau

CC36

Bring Excel Files with Multiple Sheets to SAS®

Mindy Wang, Marriott International

CC37


Seek and Ye Shall FINDC: A Powerful Function for Qualitative Data Validation

Xiaoke Yang, State University of New York -‐ Albany Peter Landi, New York State Office of Mental Health

CC38

Using PROC TCALIS to Investigate Equality of Covariance Matrices across Two Groups

Chen Li, Educational Testing Service Steven Holtzman, Educational Testing Service

CC39

Combining Continuous Events and Calculating Duration in Kaplan-‐Meier Analysis Using a Single DATA Step

Hui Song, PRA International Inc. George Laskaris, PRA International Inc.

CC40


Programming: Foundations and Fundamentals Jonas V. Bilenas, Barclays UK RBB Stan Legum, Westat

This section includes presentations that focus on a wide range of beginning and intermediate SAS® topics. The papers focus on data step and macro programming. Data step examples include the most useful SAS functions; interfacing with Microsoft Office products, particularly Excel; creating reports; and accessing data from different sources, In addition there are presentations on Enterprise Guide and the use of key PROCs. The presentations should provide beginning and intermediate users with a richer knowledge of SAS programming and increase their productivity in using SAS.

Long-‐to-‐Wide: PROC TRANSPOSE vs Arrays vs PROC SUMMARY

Mike Zdeb, U@Albany School of Public Health

FF1

Let SAS/SHARE® Deliver Formatted Data to Microsoft Office

Hsiwei Yu, Custom Software Systems Tao Dong, Pragmatics

FF2

A Survey of Some of the Most Useful SAS® Functions

Ron Cody

FF3

Loop-‐Do-‐Loop Around Arrays


FF4

Creating a Data Dictionary for an Oracle Database Using SAS® 9.3

Christopher Battiston, Hospital for Sick Children

FF6

Rediscovering the DATA _NULL_ for Creating a Report, and Putting That Text File into RTF in a Single DATA Step


FF7


Imputing Endpoints after Collapsing Longitudinal Data across Related Events

James Joseph, INC Research

FF8

How to Monitor Production and Development Processing Using the SAS® Logging Facility

Curtis Reid, U.S. Bureau of Labor Statistics

FF9

Integrating SAS® and Excel: An Overview and Comparison of Three Methods for Using SAS to Create and Access Data in Excel

Nathan Clausen, U.S. Bureau of Labor Statistics Edmond Cheng, U.S. Bureau of Labor Statistics

FF10

You Want ME to use SAS® Enterprise Guide®??

Vince DelGobbo, SAS Institute Inc.

FF11

Mike Zdeb

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Finance and Insurance Mark Keintz, Wharton Research Data Services Barbara Moss, The Hartford Finance and insurance-‐related applications and research constitute the second largest customer segment of SAS users. This year's section demonstrates the use of SAS in such areas as financial impacts on Medicare providers using simulation analysis, creating finite mixture models, identification of leading and lagging indicators, finding voided claims records, and rolling regressions. Presentations include examples of "classic" SAS modules such as SQL and LIFETEST through more recent tools such as Finite-‐Mixture modeling, text analysis, and PROC FCMP. Remove Voided Claims for Insurance Data

Qiling Shi, NCI Information Systems, Inc.

FI2

Leading and Lagging Indicators in SAS®

David Corliss, Magnify – a division of Marketing Associates

FI3

Modeling Loss Given Default by Finite Mixture Model

Chao Huang, Oklahoma State University Liang Xie

FI4

Becoming the Smartest Guys in the Room: An Analysis of the Enron Emails Using an Integration of Text Analytics and Case Management

John York, SAS Institute Inc.

FI6

Financial Impact Analysis of the New RUG-‐IV on Post-‐Acute Medicare Providers Using Monte Carlo Simulation

John Gao, PointRight Cheryl Caswells, PointRight Barry Fogel, PointRight

FI7

Rolling Regressions with PROC FCMP and PROC REG

Mark Keintz, Wharton Research Data Services

FI8


Graphics and Reporting Perry Watts, Stakana Analytics Darcy Tamburri, NECA Transforming descriptive data from SAS into informative, attractive tabular and graphics output is a requirement for today’s business analyst. The Graphics and Reporting section will present various uses of SAS tools to effectively create professional looking graphs and reports. Presentations include the use of SAS Graph procedures, specifically GEOCODE, GCHART, GPLOT, G3D, GREPLAY and GMAP as well as the Graph Template Language and Statistical Graphics procedures. The use of multiple ODS output destinations, ODS Graphics and PROC REPORT will also be demonstrated. Behind the Scenes with SAS®: Using Custom Graphics in SAS Output

Louise Hadden, Abt Associates Inc.

GR1

Analyzing the Safewalk® Program with SAS®: Saving Shelter Dogs One Walk at a Time

Louise Hadden, Abt Associates Inc. Terri Bright, Massachusetts Society for the Prevention of Cruelty to Animals

GR2

ODS DOCUMENT Step by Step


GR3

Destination Known: Programmatically Controlling Your Output in SAS® Enterprise Guide®

Aaron Hill, MDRC

GR4

Graphics for Univariate Data: Pie is Delicious But Not Nutritious

Peter Flom, Peter Flom Consulting

GR6


Scatter Plot Smoothing Using PROC LOESS and Restricted Cubic Splines

Jonas Bilenas, Barclays UK E RBB

GR7

He Who Graphs SAS® Graphs Best

Lisa Aronson Friedman, Johns Hopkins Bloomberg School of Public Health

GR8

A Map is Just a Graph Without Axes

Nat Wooding, J. Sargeant Reynolds Community College

GR9

Virginia’s Best: How to Annotate County Names and Values on a State Map

Anastasiya Osborne, Farm Service Agency, USDA

GR10

Off the Beaten Path: Create Unusual Graphs with ODS Graphics

Prashant Hebbar, SAS Institute Inc.

GR12


Hands-‐On Workshops Dalia Kahane, Westat Anastasiya Osborne, Farm Service Agency, USDA Hands-‐On Workshops allow attendees to reinforce their understanding of presentation content by following the instructor through exercises and examples on a workshop computer. Workshop topics include presentations on Exporting SAS data to Excel, ODS, SQL, SAS graphics, SAS macros, data manipulation methods, and more. The target audience is attendees at both the beginning and intermediate levels. A Tutorial on the SAS® Macro Language

John Cohen, Advanced Data Concepts, LLC

HW1

Quick Results with Output Delivery System (ODS)


HW2

PROC SQL for DATA Step Die-‐Hards

Christianna Williams, self-‐employed

HW3

Using SAS® ODS Graphics

Chuck Kincaid, Experis Business Analytics

HW4

Quick Results with PROC SQL


HW5

An Introduction to Creating Multi-‐Sheet Microsoft Excel Workbooks the Easy Way with SAS®

Vince DelGobbo, SAS Institute Inc.

HW6

SAS® Enterprise Guide®: Finally, a Programmer’s Tool

Marje Fecht, Prowerk Consulting Rupinder Dhillon, Dhillon Consulting

HW7

Mike Zdeb

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Mike Zdeb

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Large Data Sets Sara Hickson, Harvard Medical School Sandeep Kottam, Independent Consultant Some programming practices that cause no real problems when working with smaller data sets can generate significant obstacles when working with large data sets. These may include, but are not limited to: ·∙ Excessive I/O ·∙ Extensive and high-‐maintenance scripts ·∙ Network access and throughput constraints ·∙ Inefficient retrieval of subsets ·∙ Sparse data

The NESUG 2012 section on Large Data Sets will include papers that describe methods to minimize problems that occur when processing large amounts of data. Presentations may offer solutions that range from those that are very simple to advanced, involving techniques such as macros, data organization and custom indexing.

Using FORMATs Where SQL Won’t Do

James Zeitler, Harvard Business School

LD1

Top Ten SAS® Performance Tuning Techniques


LD2

Standardized Production Processes for One Routine Government Publication—Using SAS® 9.2 to Produce Mortality Tables for the National Center for Health Statistics’ Annual Report, “Health, United States”

Mary Ann Bush, Centers for Disease Control and Prevention, National Center For Health Statistics Sheila Franco, Centers for Disease Control and Prevention, National Center For Health Statistics Li-‐Hui Chen, Centers for Disease Control and Prevention, National Center For Health Statistics Shilpa Bengeri, NOVA Research

LD3


Using SAS® Enterprise Guide® to Handle Backend Data Preparation for the Health Indicators Warehouse

Li-‐Hui Chen, Centers for Disease Control and Prevention, National Center For Health Statistics Mary Ann Bush, Centers for Disease Control and Prevention, National Center For Health Statistics Kate Brett, Centers for Disease Control and Prevention, National Center For Health Statistics

LD4

Tips for Using SAS® to Manipulate Large-‐scale Data in Databases

Shih-‐Ching Wu, Virginia Tech Transportation Institute Shane McLaughlin, Virginia Tech Transportation Institute

LD5

Condensed and Sparse Indexes for Sorted SAS® Datasets

Mark Keintz, Wharton Research Data Services

LD6


Management, Administration and Support Mary Anne Rutkowski, Merck Sharp and Dohme Corp. Kathy Harkins, Merck Sharp and Dohme Corp. The Management, Administration & Support section covers a wide range of topics focused on best practices for increasing productivity from employees, processes, projects, and products related to the use of SAS® Software. In the current professional environment, employees must sustain high productivity and efficiency while managers must adapt to managing in an ever-‐ changing environment. Today’s evolving business models must respond to increased globalization, standardization, accountability, out-‐sourcing, telecommuting, and electronic collaboration. To cope with the current environment, SAS® users must continue to develop and expand their skills and grow professionally. Topics in the Management, Administration & Support section can cover various areas such as optimizing operations in an evolving business environment with quality assurance, effective utilization of SAS for administration and management of data, management techniques, SAS infrastructure maintenance and other administrative facilities. SAS® UNIX-‐Space Analyzer—A Handy Tool for UNIX SAS Administrators

Airaha Chelvakkanthan Manickam, Cognizant Technology Solutions

MA1

Better Safe than Sorry: A SAS® Macro to Selectively Back Up Files

Jia Wang, Data and Analytic Solutions, Inc. Zhengyi Fang, Social & Scientific Systems, Inc.

MA2

Step by Step Approach to Port CDISC SAS® Data Integration Repositories on Cross Platforms Using %OMAPORT Macro

Salman Ali, SAS Professional Services

MA3

Creating an Interactive SAS® Textbook in the iPad with iBooks Author

William Zupko, U.S. Census Bureau

MA4


Quality Assurance: Best Practices in Clinical SAS® Programming

Parag Shiralkar, eClinical Solutions, a Division of Eliassen Group

MA5

Process Simplification—The Simple Way! X

Minal Vyas, Hoffmann-‐La-‐Roche

MA6

PROC CPM and PROC GANTT: The Next Step in Multi-‐Project Management

Stephen Sloan, Accenture Lindsey Puryear, SAS Institute

MA7

Here Comes Your File! File-‐Watcher Tool with Automated SAS® Program Trigger

Rajbir Chadha, Cognizant Technology Solutions

MA8

The Disk Detective

Darryl Putnam, CACI, INC

MA9

Determining What SAS® Version and Components Are Available

David Chapman, Chapman Analytics, LLC

MA10

Running SAS® on the Grid

Margaret Crevar, SAS Institute Inc.

MA11

Mike Zdeb

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Pharma, Healthcare and Life Sciences John Cohen, Advanced Data Concepts LLC Emmy Pahmer, PharmaNet/i3 This section will encompass the use of SAS® in all life science domains including pharmaceutical research, health care delivery, and health insurance reimbursement. The focus will be on programming for auditing, analyzing and reporting, and system/application development, rather than on statistics. Papers will cover topics such as applying SAS to the challenges of the pharmaceutical industry, understanding issues related to regulatory compliance, and exploring emerging industry standards like CDISC, SDTM, and ADaM. Data may be clinical, post-‐marketing or related to commercial sales and marketing. Also covered are health-‐care provider metrics to address quality-‐of-‐care issues, outcomes, pay for performance, provider efficiencies, profitability, and health economics.

Generating Estimates for U.S. Healthcare Costs and Use

Paul Gorrell, IMPAQ International, LLC

PH1

Pharma Sales Reporting Using SAS® Enterprise Guide® 4.3—A Step-‐by-‐Step Practical Approach

Airaha Chelvakkanthan Manickam, Cognizant Technology Solutions Ramya Purushothaman, Cognizant Technology Solutions

PH2

Prove QC Quality—Create SAS® Datasets from RTF Files

Honghua Chen, OCKHAM

PH3

Patient Profiles “On the Cheap”: Quickly Capitalizing on PROC SQL and PROC REPORT to Efficiently and Cost Effectively Create Patient Profiles for Sponsor Source Data Verification, Audit, and Other Types of Clinical Data Verifications and Reviews

Mark Rothe, Roche

PH4

Length of Intensive Care Unit Stay Computed from the VA Corporate Data Warehouse

Adeline Wilcox, Department of Veterans Affairs

PH6


Data Rolls Up-‐Hill: Reverse Waterfall Provider Analysis Using SAS®

John Busch, Community Care Behavioral Health

PH8

Programming to Stay Afloat in Data Waves

Gayle Springer, Johns Hopkins Bloomberg School of Public Health Lorie Benning, Johns Hopkins Bloomberg School of Public Health

PH9

Applying Business Analytics to Optimize Clinical Research Operations

David Handelsman, SAS Institute Inc.

PH10

Harnessing the Power of SAS® ISO 8601 Informats, Formats, and the CALL IS8601_CONVERT Routine

Kim Wilson, SAS Institute Inc.

PH11


Posters Louise Hadden, Abt Associates Inc. Nish Herat, Independent SAS Consultant

The Posters section entertains a rich and varied collection of papers filled with comprehensive idea-‐generating solutions and highly specialized papers that can easily be expanded to your world. Through the "Meet the Poster Presenter" session Monday morning you will have access to paper authors and their work in a less formal, personable setting. Tackle large, complex databases with Hash, get to truly dynamic programming with SAS/SCL, see what SAS can do with the persistent problem of visualizing vast quantities of data, or how the US Geological Survey's internet available data can be used to populate maps with earthquake data. In addition, wise programming techniques, tips from SAS Tip of the Day, and easy ways to get useful rows of zeroes in your data are all on offer. And of course, if you prefer clicks to semicolons, Enterprise Guide and the overlooked Graph'n'Go will be represented so everyone can enjoy the views from the hotel atrium and learn something unexpected.

A SAS® Tip-‐of-‐the-‐Day Web Page on an Intranet

Bruce Gilsen, Federal Reserve Board

PO1

A Breeze through SAS® Options to Enter a Zero-‐Filled Row

Kajal Tahiliani, ICON Clinical Research

PO3

Decision-‐Making Using the Analytic Hierarchy Process (AHP) and SAS/IML®

Melvin Alexander, Social Security Administration

PO4

Working with a Large Pharmacy Database: Hash and Conquer

David Izrael, Abt Associates

PO5


A Visual Approach to Monitoring Case Report Form Submission During Clinical Trials

Rebecca Horney, Dept. of Veterans Affairs Cooperative Studies Program Coordinating Center Karen Jones, Dept. of Veterans Affairs Cooperative Studies Program Coordinating Center Annette Wiseman, Dept. of Veterans Affairs Cooperative Studies Program Coordinating Center

PO6

Using SAS/OR® for Automated Test Assembly from IRT-‐Based Item Banks

Yung-‐chen Hsu, GED Testing Service, LLC Tsung-‐hsun Tsai, Research League, LLC

PO7

Simple Statistical Programming: Preventing Errors When Creating Output Datasets Containing Statistical Test Results for McNemar’s Test

Stephen Bosch, Howard M. Proskin & Associates

PO8

Practical Application of SAS® Capabilities for Pharma Goaling and Performance Review

Ramya Purushothaman, Cognizant Technology Solutions

PO9

Wake Up Your Data with Graph’n’Go

Christopher Battiston, Hospital for Sick Children

PO10

Avoiding the “Ooh Nasty”


PO11


A SAS® Program to Construct Simultaneous Confidence Intervals of Relative Risk for Multiple Adverse Events

Xiaoli Lu, Dept. of Veterans Affairs Cooperative Studies Program Coordinating Center

PO12

Plotting Earthquake Events Using the SAS® PROC GMAP and Data from the USGS


PO13

Using SAS® GTL with 9.3 Updates to Visualize Data When There is Too Much of it to Visualize

Perry Watts, Stakana Analytics Nate Derby, Stakana Analytics

PO14

Using SAS® SCL to Create Flexible Programs... A Super-‐Sized Macro

Ellen Michaliszyn, College of American Pathologists

PO15


Statistics, Modeling and Analysis George J. Hurley, The Hershey Company Peter Flom, Peter Flom Consulting, LLC

The Statistics, Modeling and Analysis section includes abstract submissions that cover the use of SAS® in applied statistical, analytical, epidemiological, and survey methods across a variety of industries, such as consumer packaged goods, health care and pharmaceuticals, government, marketing, and a variety of academic fields. Papers can illustrate business or research problems. Most papers illustrate approaches to satisfying a research or business need, including an analytic or statistical method for addressing the need and demonstrating a SAS and/or JMP implementation of that method.

K-‐Nearest Neighbor Classification and Regression in SAS®

Liang Xie, Travelers Insurance

SA1

Creating and Displaying an Econometric Model Automatically

William Zupko, U.S. Census Bureau Justin Smith, U.S. Census Bureau

SA3

SAS® for Six Sigma—An Introduction

Dan Bretheim, Towers Watson

SA4

An Animated Guide: Regression Trees in JMP® and Enterprise Miner ™

Russ Lavery, Contractor

SA5

Elongated Intersected Clusters and Radial Coordinates Transformation Using SAS®

Alexander Suprun, CIBC

SA6

Target Trained Transformations for Predictive Modeling

Talbot Katz, Cisco Systems, Inc.

SA7


Using SAS® to Test, Probe and Display Interaction Effects in Regression

Timothy Gravelle, PriceMetrix Inc.

SA8

Efficiently Screening Predictor Variables for Logistic Models

Steven Raimi, Magnify – a division of Marketing Associates, LLC Bruce Lund, Magnify – a division of Marketing Associates, LLC

SA9

Developing an Analytics Center of Excellence (Or the Care and Feeding of Magical Creatures)

Chuck Kincaid, Experis Business Analytics

SA10

Introduction to Statistics with Wavelets in SAS®

David Corliss, Magnify – a division of Marketing Associates

SA11

Implementing and Interpreting Canonical Correspondence Analysis in SAS®

Laxman Hegde, Frostburg State University

SA12

Applying Customer Attitudinal Segmentation to Improve Marketing Campaigns

Wenhong Wang, Deluxe Corporation Mark Antiel, Deluxe Corporation

SA13

Profiling Consumer Price Index Formulas

Joshua Klick, U.S. Bureau of Labor Statistics

SA14

A Macro-‐Driven Approach for Systematically Testing Variables Against a Base Regression Model

Jennifer Alessandro, Management Science Associates, Inc. Bryan Harmon, Management Science Associates, Inc.

SA15


Generalized Additive Models in Marketing Mix Modeling Revisited

Patralekha Bhattacharya, Jigyasa Analytics

SA16

A Model for Extreme Stacking of Data at Endpoints of a Distribution

Robert Gallop, West Chester University

SA17

What?? SAS/AF® & SCL Can Enhance Rapid Prototyping of Modern Web Development Efforts?

Joe Whitehurst, High Impact Technologies Richard Devenezia, High Impact Technologies Art Tabachneck, myQNA

SA18

Look Out: After SAS/STAT® 9.3 Comes SAS/STAT 12.1!

Maura Stokes, SAS Institute Inc.

SA19

Introducing the FMM Procedure for Finite Mixture Models

Maura Stokes, SAS Institute Inc.

SA21

Building a Predictive Model for 30-‐Day Inpatient Readmission Using PROC PHREG

Klaus Lemke, Johns Hopkins Bloomberg School of Public Health

SA22