MWSUG 2015 Conference Proceedings

Omaha, Nebraska
October 18-20, 2015

Advanced Analytics Beyond the Basics BI / Customer Intelligence Career Development Data Visualization and Graphics

Pharmaceutical Applications Posters Rapid Fire SAS 101 Tools of the Trade

Advanced Analytics

AA-01. Can you STOP the guesswork in your marketing budget Allocation??? Marketing Mixed Modeling using SAS® can help!!!
Delali Agbenyegah, Alliance Data Systems, Columbus, OH

AA-02. A Property & Casualty Insurance Predictive Modeling Process in SAS
Mei Najim, Sedgwick Claim Management Services, Chicago, IL

AA-03. Fitting and Evaluating Logistic Regression Models
Bruce Lund, Magnify Analytic Solutions, a Division of Marketing Associates, LLC, Detroit, MI

AA-04. Advanced Techniques for Fitting Mixed Models Using SAS/STAT® Software
Jill Tao, SAS Institute Inc., Cary, NC
Kathleen Kiernan, SAS Institute Inc., Cary, NC
Phil Gibbs, SAS Institute Inc., Cary, NC

AA-05. Need Help Finding Something? Why Not Ask Your (Virtual) Community! A Collaborative Filtering Based Recommendation Engine in SAS®
Ben Elbert, Alliance Data, Columbus, OH

AA-06. Base SAS Sentiment Analysis Using Catchprases
Mike Tangedal, Capella University

AA-07. Slice and Dice your customers easily by using SAS® Clustering Procedures
Yanping Shen, Alliance Data Systems, Columbus, OH

AA-08. Get the highest bangs for your marketing bucks using Incremental Response Models in SAS® Enterprise Miner™
Delali Agbenyegah, Alliance Data Systems, Columbus, OH

AA-09. Using SAS for the Longitudinal Analysis of Difference Scores
Brandy R. Sinco, MS, University of Michigan, Ann Arbor, MI
Edith Kieffer, PhD, University of Michigan, Ann Arbor, MI
Michael S. Spencer, PhD, University of Michigan, Ann Arbor, MI
Gloria Palmisano, BS, MA, CHASS Center, Detroit, MI
Gretchen Piatt, PhD, University of Michigan, Ann Arbor, MI
Michele Heisler, M.D., University of Michigan, Ann Arbor, MI

AA-10. Cross-Cultural Comparison of the School Factors Affecting Students' Achievement in Mathematical Literacy: Based on the Multilevel Analysis of PISA 2012
Yage Guo, University of Nebraska-Lincoln, Lincoln, NE

AA-11. Shifting Expectations: A practical algorithm for detecting level shifts using robust rolling statistics
*** BEST PAPER ***
Matt Bates, J.P. Morgan Chase, Columbus, OH

AA-12. Predictive Modeling Using Artificial Neural Networks in SAS® Enterprise Miner
Kechen Zhao, University of Southern California

AA-13. Two-Stage Attribute Match and Its Applications in Loyalty Marketing
Jie Liao, Alliance Data Card Service, Columbus, OH
Yi Cao, Alliance Data Card Service, Columbus, OH

BI / Customer Intelligence

BI-01. Decision Management with DS2
Helen Fowler, Teradata Corporation, West Chester, OH
Tho Nguyen, Teradata Corporation, Raleigh, NC

BI-02. Creating Multi-Sheet Microsoft Excel Workbooks with SAS: The Basics and Beyond Part 2
Vince DelGobbo, SAS Institute Inc., Cary, NC

BI-03. In Search of the LOST CARD
Andrew T. Kuligowski, HSN

BI-04. Staying Relevant in a Competitive World: Using the SAS® Output Delivery System to Enhance, Customize, and Render Reports
Chevell Parker, SAS Institute Inc., Cary, NC

BI-05. Introduction to ODS Graphics
*** BEST PAPER ***
Chuck Kincaid, Experis Business Analytics, Kalamazoo, MI

BI-06. Introduction to SAS® Data Loader: The Power of Data Transformation in Hadoop
Keith Renison, SAS Institute Inc.

BI-07. Intermediate SAS® ODS Graphics
Chuck Kincaid, Experis Business Analytics, Kalamazoo, MI

BI-08. Easy Come, Easy Go — Interactions between the DATA Step and External Files
Andrew T. Kuligowski, HSN

BI-09. Debt Collection Through SAS® Analytics Lens
Karush Jaggi, Oklahoma State University
Thomas Waldschmidt, SquareTwo Financial
Harold Dickerson, SquareTwo Financial
Eric Hayes, SquareTwo Financial
Goutam Chakraborty, Oklahoma State University

BI-10. SAS® Enterprise Guide® System Design
Jennifer First-Kluge, Systems Seminar Consultants, Inc.
Steven First, Systems Seminar Consultants, Inc.

BI-11. The Joinless Join ~ The Impossible Dream Come True; Expanding the Power of SAS® Enterprise Guide® in a New Way
Kent Phelps, The SASketeers, Des Moines, IA
Ronda Phelps, The SASketeers, Des Moines, IA

BI-12. Using Enterprise Miner™ to Create Model Documentation And/or Reproducible Research
Rex Pruitt, SAS Institute, Indian Trail, NC

Beyond the Basics

BB-01. Five Little Known, But Highly Valuable and Widely Usable, PROC SQL Programming Techniques
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

BB-02. Greenspace: A Macro to Improve a SAS® Data Set Footprint
Brian Varney, Experis Business Intelligence and Analytics Practice, Portage, MI

BB-03. Just passing through… Or are you? Determine when SQL Pass-Through occurs to optimize your queries
Misty Johnson, State of Wisconsin Department of Health Services, Madison, WI

BB-04. SAS® Spontaneous Combustion: Securing Software Portability through Self-Extracting Code
Troy Martin Hughes

BB-05. Retrieving Survey Data using the Qualtrics REST API with SAS®
Katie Tanner, Capella University, Minneapolis, MN

BB-06. Color, Rank, Count, Name; Controlling it all in PROC REPORT
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

BB-07. Controlling Colors by Name; Selecting, Ordering, and Using Colors for Your Viewing Pleasure
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

BB-08. Table Lookup Techniques: From the Basics to the Innovative
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

BB-09. Data Labs with SAS® and Teradata: Value, Purpose and Best Practices
Helen Fowler, Teradata Corporation, West Chester, OH
Tho Nguyen, Teradata Corporation, Raleigh, NC

BB-10. An Autoexec Companion, Allocating Location Names during Startup
Ronald J. Fehd, Stakana Analytics

BB-11. Do we need Macros? An Essay on the Theory of Application Development
Ronald J. Fehd, Stakana Analytics

BB-12. Wow! You Did that with SAS® Stored Processes?
Dave Mitchell, Solution Design Team, Littleton, CO

BB-13. Tips and Tricks for Getting the Most Out of the SAS® Macro Facility
*** BEST PAPER ***
Scott A. Miller, Wells Fargo, Des Moines, IA

BB-16. Cleaning Data with Just a Handful of SAS® Functions
Ben Cochran, The Bedford Group, Raleigh, NC

BB-17. When Reliable Programs Fail: Designing for Timely, Efficient, Push-Button Recovery
Troy Martin Hughes

BB-18. Beyond a One-Stoplight Town: A Base SAS® Solution to Preventing Data Access Collisions through the Detection, Deployment, Monitoring, and Optimization of Shared and Exclusive File Locks
Troy Martin Hughes

BB-19. Getting Started with SAS® Add-in for MicroSoft® Office Product
Ben Cochran, The Bedford Group, Raleigh, NC

Career Development

CD-01. What's Hot, What's Not: Skills for SAS® Professionals
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, Consider Consulting Corporation, San Pedro, CA

CD-02. SAS® Software as an Essential Tool in Statistical Consulting and Research
Erika Larsen, Loyola University, Chicago, IL
Timothy E. O’Brien, Loyola University, Chicago, IL

CD-03. Preparing for Future Careers in Big Data, Marketing Analytics and Data Warehousing (No paper available)
Helen Fowler, Teradata

CD-04. Career Development Panel Discussion (No paper available)
John Xu, First Consulting

Data Visualization and Graphics

DV-02. A Macro to Easily Generate an interactive Google Map Report
*** BEST PAPER ***
Ting Sa, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH

DV-03. Sales Force Alignment Visualization with SAS®
Yu (Daniel) Wang, Experis, Cincinnati, OH

DV-04. Visualize the Geography of your Business Insights using SAS® MAP tools
Xingrong(Candice) Zhang, Alliance Data Card Services, Columbus, OH

DV-05. Getting Productive Fast in SAS® ODS Graphics – a “Simple Look-See” Approach
Roger D. Muller, Ph.D., Data-To-Events, Inc., Carmel, IN

DV-06. Intuitive Demonstration of Statistics through Data Visualization of Pseudo-Randomly Generated Numbers in R and SAS
Jack Sawilowsky, Union Pacific Railroad

DV-07. Cutpoint Determination Methods in Survival Analysis using SAS®: Updated %FINDCUT macro
J. P. Meyers, Mayo Clinic, Rochester, MN
J. N. Mandrekar, Mayo Clinic, Rochester, MN

Pharmaceutical Applications

PH-01. Transitions in Depressive Symptoms After 10 Years of Follow-up Using PROC LTA in SAS® and Mplus
Seungyoung Hwang, Johns Hopkins University Bloomberg School of Public Health

PH-02. Project Management of SAS Tasks - Excel Dashboard without Using Any Program
Kalaivani Raghunathan, Quartesian Clinical Research Pvt. Ltd, Bangalore, India

PH-03. How to Build a Hierarchical Mixed Model in SAS
*** BEST PAPER ***
Sara Burns, Washington University School of Medicine, St. Louis, MO
Amit Amin, Washington University and Barnes Jewish Hospital, St. Louis, MO
Eric Novak, Washington University and Barnes Jewish Hospital, St. Louis, MO

PH-06. Plotting LSMEANS and Differences in Generalized Linear Models with GTL
Robin High, University of Nebraska Medical Center, Omaha, NE

PH-07. Utilizing Propensity Score Analyses to Adjust for Selection Bias: A Study of Adolescent Mental Illness and Substance Use
Deanna Schreiber-Gregory, National University, Moorhead, MN

PH-08. Ushering SAS® Emergency Medicine into the 21st Century: Toward Exception Handling Objectives, Actions, Outcomes, and Comms
Troy Martin Hughes

Posters

PO-01. Keep the Formats When Exporting to Excel
*** BEST PAPER ***
Ting Sa, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH

Rapid Fire

RF-01. Essential DATA Step Merge Techniques Using SAS® University Edition Software
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, Consider Consulting Corporation, San Pedro, CA

RF-02. Essential PROC SQL Join Techniques Using SAS® University Edition Software
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

RF-03. SAS® Dates with Decimal Time
John Henry King, Ouachita Clinical Data Services, Inc., Caddo Gap, AR

RF-04. Reading a Column into a Row to Count N-levels, Calculate Cardinality Ratio and Create Frequency and Summary Output In One Step
Ronald J. Fehd, Stakana Analytics

RF-05. ‘V’ for … Variable Information Functions to the Rescue
Richann Watson, Experis, Batavia, OH
Karl Miller, inVentiv Health, Lincoln, NE

RF-06. Automated LSTtoRTFtoPDF Converter
Palanisamy Mohan, Icon Clinical Research India Pvt. Ltd, Bangalore

RF-07. Macro to Create Multiple SQL IN Clauses from One Column of Data
Mark Millman, Optum, Eden Prairie, Minneapolis, MN

RF-08. Essentials of Macro Quoting Functions in SAS
Kaushal Raj Chaudhary, Sanford Research, Sioux Falls, SD

RF-09. %SYSFUNC Is Your Friend
*** BEST PAPER ***
Kaushal Raj Chaudhary, Sanford Research, Sioux Falls, SD
Deanna Naomi Schreiber-Gregory, National University, La Jolla, CA

RF-10. A Macro for Systematic Treatment of Special Values in Weight of Evidence Variable Transformation
Chaoxian Cai, Automated Financial Systems, Exton, PA

RF-11. Why Would You Not Want to Learn About PROC DOCUMENT?
Roger D. Muller, Ph.D., Data-To-Events, Inc., Carmel, IN

RF-12. Find your Way to Quick and Easy Table Lookups with FINDW
Joshua M. Horstman, Nested Loop Consulting, Indianapolis, IN

RF-13. Building PROC FORMAT Code from Data Dictionary Automatically
Ran Gu, Nebraska DHHS /UNL, Lincoln, NE
Ashley Newmyer, Nebraska Department of Health and Human Service, Lincoln, NE

RF-14. Using a Picture Format to Create Visit Windows
Richann Watson, Experis, Batavia, OH

RF-15. A Simple Adjustment for Selection Bias Through Use of Propensity Scoring
Deanna Schreiber-Gregory, National University, Moorhead, MN

RF-16. Making Historical Versions of SAS® Code While Developing in Enterprise Guide 7.1
Roger D. Muller, Ph.D., Data-To-Events, Inc., Carmel, IN

SAS 101

SA-01. The REPORT Procedure: A Primer for the Compute Block
Jane Eslinger, SAS Institute Inc., Cary, NC

SA-02. Introduction to PROC SQL
Jennifer First-Kluge, Systems Seminar Consultants, Inc., Madison, WI

SA-03. SAS® Enterprise Guide for Managers and Executives
Jennifer First-Kluge, Systems Seminar Consultants, Inc., Madison, WI

SA-05. Pruning the SASLOG – Digging into the Roots of NOTEs, WARNINGs, and ERRORs
Andrew T. Kuligowski, HSN

SA-06. Let SAS Cleanse Your Dirty Data
Kaushal Raj Chaudhary, Sanford Research, Sioux Falls, SD
Deanna Naomi Schreiber-Gregory, National University, Moorhead, MN

SA-07. Getting and Staying Organized: Tips for Improving the SAS® Data Analysis/Analyst Experience
Harlan Sayles, University of Nebraska Medical Center, Omaha, NE

SA-08. Are You Missing Out? Working with Missing Values to Make the Most of What is not There
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

SA-09. Importing multiple spreadsheets in an Excel Workbook: An introduction to Macros
Nathan Becker, Pearson Vue, Bloomington, MN
William Muntean, Pearson Vue, Chicago, IL

SA-10. Improving Data Collection Efficiency And Programming Process Flow Using SAS® Enterprise Guide® With Epi Info™
*** BEST PAPER ***
Chad Wetzel, MPH, Douglas County Health Department, Omaha, NE
Dr. Anne O’Keefe, MD, MPH, Douglas County Health Department, Omaha, NE
Justin Frederick, MPH, Douglas County Health Department, Omaha, NE

SA-11. Basic SAS® PROCedures for Quick Results
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

SA-12. Top Ten SAS® Performance Tuning Techniques
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

SA-13. Downloading, Configuring, and Using the Free SAS® University Edition Software
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, Consider Consulting Corporation, San Pedro, CA

SA-14. Beyond IF THEN ELSE: Techniques for Conditional Execution of SAS Code
Joshua M. Horstman, Nested Loop Consulting, Indianapolis, IN

SA-15. Good SAS Programming Practices
Pat O’Meara, Pat O’Meara Associates, Inc., Lincoln, NE

Tools of the Trade

TT-01. Dynamic Dashboards Using Base-SAS® Software
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

TT-02. You Can't Spell 'Assume' without S.A.S.
*** BEST PAPER ***
Mike Tangedal, Capella University

TT-03. Leveraging Hadoop from the Comfort of SAS®
Emily Hawkins, UnitedHealthcare, Minnetonka, MN
Lal Puthenveedu Rajanpillai, UnitedHealthcare, Minnetonka, MN

TT-04. Multiple Imputation for Arbitrary Missing Data: SAS and R
Kaushal Raj Chaudhary, Sanford Research, Sioux Falls, SD
Deanna Naomi Schreiber-Gregory, National University, Moorhead, MN

TT-05. SAS® Enterprise Guide® Base SAS® Program Nodes ~ Automating Your SAS World With a Dynamic FILENAME Statement, Dynamic Code, and the CALL EXECUTE Command; Your Newest BFF (Best Friends Forever) in SAS
Kent Phelps, The SASketeers, Des Moines, IA
Ronda Phelps, The SASketeers, Des Moines, IA

TT-06. Using SAS Programs to Conduct Discriminate Analysis
Mengyu Liu, University of Southern California, Los Angeles, CA

TT-09. A Demonstration of SAS Analytics in Teradata
Helen Fowler, Teradata Corporation, West Chester, OH