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MWSUG 2013 Conference Proceedings

Columbus, OH
September 22-24, 2013

Advanced Analytics

AA-02. PROC SURVEYSELECT as a Tool for Drawing Random Samples
Taylor Lewis, University of Maryland, College Park, MD

AA-03. Finding the Gold in Your Data: An Overview of Data Mining
David A. Dickey, North Carolina State University, Raleigh, NC

AA-04. Logistics Performance Metrics using SAS® Macros
Michael C. Frick, General Motors - Retired, Warren, MI

AA-05. Adventures in Path Analysis and Preparatory Analysis
*** BEST PAPER ***
Brandy R. Sinco, MS, University of Michigan, Ann Arbor, MI
Phillip L. Chapman, PhD, Colorado State University, Fort Collins, CO

AA-06. Managing and Monitoring Statistical Models
Nate Derby, Stakana Analytics, Seattle, WA

AA-07. Introduction to Market Basket Analysis
Bill Qualls, First Analytics, Raleigh, NC

AA-08. Improved Interaction Interpretation: Application of the EFFECTPLOT statement and other useful features in PROC LOGISTIC
Robert G. Downer, Grand Valley State University, Allendale, MI

AA-09. Analyzing Continuous Variables from Complex Survey Data Using PROC SURVEYMEANS
Taylor Lewis, University of Maryland, College Park, MD

AA-10. Analyzing Categorical Variables from Complex Survey Data Using PROC SURVEYFREQ
Taylor Lewis, University of Maryland, College Park, MD

AA-11. Ideas and Examples in Generalized Linear Mixed Models
David A. Dickey, North Carolina State University, Raleigh, NC

AA-12. Uncovering Patterns in Textual Data for SAS® Visual Analytics and SAS® Text Analytics
Daniel Zaratsian, SAS Institute, Inc., Cary, NC
Mary Osborne, SAS Institute, Inc., Cary, NC
Justin Plumley, SAS Institute, Inc., Cary, NC

AA-14. Information Value Statistic
Bruce Lund, Magnify Analytics Solutions, a Division of Marketing Associates, Detroit, MI
David Brotherton, Magnify Analytics Solutions, a Division of Marketing Associates, Detroit, MI

AA-15. Structural Equation Modeling Using the CALIS Procedure in SAS/STAT® Software (No paper available)
Yiu-Fai Yung, SAS Institute Inc., Cary, NC

AA-16. Leading and Lagging Indicators in SAS®
David J. Corliss, Magnify Analytic Solutions, Detroit, MI



BI Applications, Systems Architecture & Admin.

BI-01. Using the SAS® Projman Application for Scheduling Projects
Jon Patton, Miami University, Oxford, OH

BI-02. Seamless Dynamic Web (and Smart Device!) Reporting with SAS®
D.J. Penix, Pinnacle Solutions, Indianapolis, IN

BI-03. Building a Dynamic SAS HTML Report with JavaScript and SAS® Tagsets
Mike Libassi, Elsevier Corporation, Dayton, OH

BI-04. SAS Stored Processes on the Web - Building Blocks
Mark Roberts, Pinnacle Solutions, Indianapolis, IN

BI-05. Transitioning from Batch and Interactive SAS® to SAS® Enterprise Guide
Brian Varney, Experis Business Analytics, Portage, MI

BI-06. Improving Your Relationship with SAS® Enterprise Guide®
Jennifer Bjurstrom, SAS Institute, Inc., Cary, NC

BI-07. Beating Gridlock: Parallel Programming with SAS® Grid Computing and SAS/CONNECT®
*** BEST PAPER ***
Jack Fuller, Experis, Portage, MI

BI-08. Going From SAS/PC to SAS Enterprise Guide®?
Ira Shapiro, UnitedHealth Corporation, Minnetonka, MN



Banking and Financial Services

FS-01. PROC NLMIXED and PROC IML: Mixture distribution application in Operational Risk
Sabri Guray Uner, Union Bank, N.A., Monterey Park, CA
Yunyun Pei, Union Bank, N.A., Monterey Park, CA

FS-03. Use SAS/ETS to Forecast Credit Loss for CCAR
Xinpeng “Tom” Wang, Huntington National Bank, Columbus, OH

FS-04. SAS Automation - From Password Protected Excel Raw Data To Professional-Looking PowerPoint Report
Jeff Hao, PhD, JPMorgan Chase & Co., Columbus, OH

FS-05. Statistical Models for Proportional Outcomes
WenSui Liu, Fifth Third Bancorp, Cincinnati, OH
Kelly Zhao, Fifth Third Bancorp, Cincinnati, OH

FS-07. Advanced Multithreading Techniques for Performance Improvement of SAS® Processes
*** BEST PAPER ***
Viraj R Kumbhakarna, JPMorgan Chase & Co., Columbus, OH

FS-08. Changing a Static Condition to a Dynamic Data-Driven Field with SAS®
Misty Johnson, State of Wisconsin Department of Health Services, Madison, WI

FS-09. Addressing Fraudulent Payment Activity with Advanced Decision Management Analytics
Rex Pruitt, Capgemini, Charlotte, NC

FS-10. Data Quality Governance for Data Sourcing and Data Analytics Team
Anand Kumar, Arunam Technologies LLC, Columbus, OH



Beyond the Basics

BB-01. Add a Little Magic to Your Joins
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

BB-02. Same Data Different Attributes: Cloning Issues with Data Sets
Brian Varney, Experis Business Analytics, Portage, MI

BB-03. The Secret Life of DATA STEP
Swati Agarwal, OPTUM, Eden Prairie, MN

BB-04. “How Do I . . .?” There is more than one way to solve that problem; Why continuing to learn is so important
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

BB-05. A First Look at the ODS Destination for PowerPoint
Tim Hunter, SAS Institute, Inc., Cary, NC

BB-06. The Joinless Join; Expand the Power of SAS® Enterprise Guide® in a New Way
Kent Phelps, Illuminator Coaching, Inc., Des Moines, IA
Ronda Phelps, Illuminator Coaching, Inc., Des Moines, IA
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

BB-07. A Better Way to Flip (Transpose) a SAS® Dataset
Arthur S. Tabachneck, Ph.D., myQNA, Inc., Thornhill, ON, Canada
Xia Ke Shan, Chinese Financial Electrical Company, Beijing, China
Robert Virgile, Robert Virgile Associates, Inc., Lexington, MA
Joe Whitehurst, High Impact Technologies, Atlanta, GA

BB-08. Anatomy of a Merge Gone Wrong
James Lew, Compu-Stat Consulting, Scarborough, ON, Canada
Joshua Horstman, Nested Loop Consulting, Indianapolis, IN

BB-09. Optimize Your Delete
Brad Richardson, SAS Institute, Inc., Cary, NC

BB-10. Not All Equals are Created Equal: Nonstandard Statement Structures in the DATA Step
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

BB-11. Efficient and Smart Ways to Manage Datasets for Clinical Data- Let SAS® Do the Dirty Laundry!
*** BEST PAPER ***
Gowri Madhavan, Cincinnati Children?s Hospital and Medical Center, Cincinnati, OH
Alan Leach, Cincinnati Children?s Hospital and Medical Center, Cincinnati, OH

BB-12. Life Imitates Art: ODS Output Data Sets that Look like Listing Output
Dylan Ellis, Mathematica Policy Research, Washington, DC

BB-13. Creating Formats on the Fly
Suzanne M. Dorinski, U.S. Census Bureau, Washington, DC



Black Belt SAS

00-01. Using Microsoft® Windows® DLLs within SAS® Programs
*** BEST PAPER ***
Rajesh Lal, Experis, Portage, MI

00-02. Macro Design Ideas: Theory, Template, Practice
Ronald J. Fehd, Stakana Analytics, Atlanta, GA

00-03. SAS® Commands PIPE and CALL EXECUTE; Dynamically Advancing from Strangers to Best Friends
Kent Phelps, Illuminator Coaching, Inc., Des Moines, IA
Ronda Phelps, Illuminator Coaching, Inc., Des Moines, IA
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

00-04. Top 10 SAS Best Programming Practices They Didn't Teach You in School (No paper available)
Charu Shankar, SAS Institute, Inc., Toronto, ON, Canada



Customer Intelligence

CI-01. Few SAS PROCs that Help Improving College Recruitment and Enrollment Strategies
Harjanto Djunaidi, Association of American Education Analytics, Murfreesboro, TN
Monica Djunaidi, Association of American Education Analytics, Murfreesboro, TN

CI-02. Introducing PROC PSYCHIC
David J. Corliss, Magnify Analytic Solutions, Detroit, MI

CI-03. Marrying Customer Intelligence with Customer Segmentations to Drive Improvements to Your CRM Strategy
Phil Krauskopf, Elite Technology Solutions, Willoughby, OH

CI-04. sasNerd®: Better Searches = Better Results
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, Consider Consulting, Los Angeles, CA
Richard W. La Valley, Strategic Technology Solutions, Inc., Arlington, VA
Lex Jansen, lexjansen.com, Cary, NC

CI-05. Residential Energy Efficiency and the Principal-Agent Problem
*** BEST PAPER ***
Ryan Anderson, University of Nebraska Public Policy Center, Lincoln, NE

CI-06. SAS® Treatments: One to One Marketing with a Customized Treatment Process
Dave Gribbin, SAS Institute Inc., Cary, NC
Amy Glassman, SAS Institute Inc., Cary, NC

CI-07. SAS PROC REPORT: How It Helps Improving College Student Retention Rate
Harjanto Djunaidi, Association of American Education Analytics, Murfreesboro, TN
Monica Djunaidi, Association of American Education Analytics, Murfreesboro, TN

CI-08. Big Data, Fast Processing Speeds
Kevin McGowan, SAS Solutions on Demand, Cary, NC

CI-09. Applying Customer Analytics to Customer Decisions
Wanda Shive, SAS Institute, Inc., Cary, NC



Data Visualization and Graphics

DV-01. PROC SGPLOT over PROC GPLOT
Shruthi Amruthnath, Experis Business Analytics, Portage, MI

DV-03. The Graph Template Language: Beyond the SAS/GRAPH® Procedures
Jesse M. Pratt, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH

DV-04. SAS® Tile Charts: Thousands of Business Tips with One Click (No paper available)
Martha Hays, SAS Institute, Inc., Cary, NC

DV-05. Using ODS PDF, Style Templates, Inline Styles, and PROC REPORT with SAS® Macro Programs
Patrick Thornton, SRI International, Menlo Park, CA

DV-06. Bordering on Success with PROC GMAP in SAS®: Utilizing Annotate Datasets to Enhance Your Maps
*** BEST PAPER ***
Kathryn Schurr, M.S., Spectrum Health-Healthier Communities, Grand Rapids, MI
Jonathan Wiseman, Spectrum Health-Healthier Communities, Grand Rapids, MI

DV-07. A Concise Display of Multiple Response Items
Patrick Thornton, SRI International, Menlo Park, CA

DV-08. Time Contour Plots
David J. Corliss, Magnify Analytic Solutions, Detroit, MI



Hands-On Workshops

HW-01. Know Thy Data: Techniques for Data Exploration
Andrew T. Kuligowski, HSN, Dunedin, FL
Charu Shankar, SAS Institute, Inc., Toronto, ON, Canada

HW-02. Fast Access Tricks for Large Sorted SAS Files
Russ Lavery, Bryn Mawr, PA

HW-03. Getting Excel-lent Data: Generating SAS Datasets from a Directory of Spreadsheets
Ben Cochran, The Bedford Group, Raleigh, NC

HW-04. Using SAS® ODS Graphics
Chuck Kincaid, Experis Business Intelligence and Analytics, Portage, MI

HW-05. Building a Better Bar Chart with SAS® Graph Template Language
*** BEST PAPER ***
Perry Watts, Stakana Analytics, Elkins Park, PA

HW-06. Hands-On SAS® Macro Programming Tips and Techniques
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

HW-07. Using PROC FCMP to the Fullest: Getting Started and Doing More
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK



JMP

JM-01. Dealing with Data below the Detection Limit: Limit Estimation and Data Modeling
Mark Bailey, SAS Institute, Inc., Haddonfield, NJ
Diane K. Michelson, SAS Institute, Inc., Austin, TX

JM-02. 2x10-Minute JMP® (No paper available)
George Hurley, Plymouth Rock Assurance, NJ

JM-03. The JMP® Journal: An Analyst’s Best Friend
*** BEST PAPER ***
Nate Derby, Stakana Analytics, Seattle, WA

JM-04. Google® Search Tips and Techniques for SAS® and JMP® Users
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, Consider Consulting, Los Angeles, CA

JM-05. Design of Experiments (DOE) Using JMP
Charles Edwin Shipp, Consider Consulting, Los Angeles, CA

JM-06. When will it break? Exploring Product Reliability Using JMP (No paper available)
Erich Gundlach, SAS Institute, Inc., Cary, NC

JM-07. JMP, and JMP Training: a Panel Discussion
Charles Edwin Shipp, Consider Consulting, Los Angeles, CA



Pharmaceutical Apps

RX-01. Introduction to REDCap for Clinical Data Collection
Shannon M. Morrison, M.S., Cleveland Clinic Foundation, Cleveland, OH

RX-02. SAS® and REDCap API: Efficient and Reproducible Data Import and Export
*** BEST PAPER ***
Sarah Worley, Cleveland Clinic, Cleveland, OH
Dongsheng Yang, Cleveland Clinic, Cleveland, OH

RX-03. Let SAS® Do Your DIRty Work
Richann Watson, Experis, Batavia, OH

RX-04. An Analysis of Risk Behavior Trends and Mental Health in American Youth Using PROC SURVEYLOGISTIC
Deanna Schreiber-Gregory, North Dakota State University, Fargo, ND

RX-05. Reading and Writing RTF Documents as Data: Automatic Completion of CONSORT Flow Diagrams
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK
Dennis G. Fisher, Ph.D., CSULB, Long Beach, CA

RX-06. Creation and Implementation of an Analytic Dataset for a Multi-Site Surveillance Study using Electronic Health Records (EHR) and Medical Claims Data
Renuka Adibhatla, HealthPartners Institute for Education & Research, Minneapolis, MN
Gabriela VazquezBenitez, HealthPartners Institute for Education & Research, Minneapolis, MN
Mary Becker, HealthPartners Institute for Education & Research, Minneapolis, MN
Amy Butani, HealthPartners Institute for Education & Research, Minneapolis, MN

RX-07. Examining Risk Factors of Referred and Substantiated Child Maltreatment in California Latino Infants Using PROC GENMOD (No paper available)
Kechen Zhao, University of Southern California, Los Angeles, CA

RX-08. A Tutorial on PROC LOGISTIC
Arthur Li, City of Hope National Medical Center, Duarte, CA

RX-09. Using SAS® in Clinical Programming Project Management from Excel® Spreadsheets
Jean Crain, InVentiv Health Clinical LLC, Indianapolis, IN



Posters

PT-01. Exploring the PROC SQL _METHOD Option
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, Consider Consulting, Los Angeles, CA

PT-02. Macro to compute best transform variable for the model
Nancy Hu, Chicago, IL

PT-03. You Could Be a SAS® Nerd If . . .
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

PT-04. Trend Reporting Using the MXG® Trend Performance Database
Neal Musitano Jr., U. S. Department of Veterans Affairs, Philadelphia, PA

PT-05. Customizing a Multi-Cell Graph Created with SAS ODS Graphics Designer
Yanhong Liu, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH

PT-06. Aligning Parallel Axes in SAS® GTL
Perry Watts, Stakana Analytics, Elkins Park, PA

PT-07. Increase Pattern Detection in SAS® GTL with New Categorical Histograms and Color Coded Asymmetric Violin Plots
*** BEST PAPER ***
Perry Watts, Stakana Analytics, Elkins Park, PA

PT-08. The DO's and DON'Ts of PROC REPORT: Building From Introductory Ideas into Professional Results (No paper available)
Daniel Sturgeon, Priority Health, Grand Rapids, MI
Erica Goodrich, Grand Valley State University/MPI Research

PT-09. Twin Ports Area SAS Users Group: Doing great things on a great lake (No paper available)
Steve Waring, Essentia Institute of Rural Health (EIRH), Duluth, MN
Ron Regal, University of Minnesota-Duluth/EIRH
Paul Hitz, EIRH

PT-10. SAS Enterprise Guide® – Implementation Hints and Techniques for Insuring Success with Traditional SAS Programmers
Roger D. Muller, Ph. D., Data-to-Events, Inc, Carmel, IN

PT-11. Transposing a SAS® dataset from 'long' to 'wide‘
Peter Batra, University of Michigan, Ann Arbor, MI



Rapid Fire

RF-01. Getting Wild with Imports
Kathryn Schurr, M.S., Spectrum Health-Healthier Communities, Grand Rapids, MI
Jonathan Wiseman, Spectrum Health-Healthier Communities, Grand Rapids, MI

RF-02. Does foo Pass-Through? SQL Coding Methods and Examples using SAS® Software
Stephen Crosbie, UM (Universal McCann), Birmingham, MI

RF-04. Copy and Paste from Excel to SAS®
Arthur S. Tabachneck, Ph.D., myQNA, Inc., Thornhill, ON, Canada
Matthew Kastin, I-Behavior, Inc., Penn Valley, PA

RF-05. Increase Your Productivity by Doing Less
Arthur S. Tabachneck, Ph.D., myQNA, Inc., Thornhill, ON, Canada
Xia Ke Shan, Chinese Financial Electrical Company, Beijing, China
Robert Virgile, Robert Virgile Associates, Inc., Lexington, MA
Joe Whitehurst, High Impact Technologies, Atlanta, GA

RF-06. Reuse, Don't Reinvent: Extending Model Selection Using Recursive Macro
Anca M Tilea, University of Michigan, Ann Arbor, MI
Philip L Francis III, Eastern Michigan University, Ypsilanti, MI

RF-07. Data Review Information: N-Levels or Cardinality Ratio
Ronald J. Fehd, Stakana Analytics, Atlanta, GA

RF-08. Improve Your ODS Experience with These Essential VBScript Tools
Rose Grandy, Abbott Laboratories, Abbott Park, IL

RF-09. An Efficient Approach to Automatically Convert Multiple Text Files (.TXT) to Rich Text Format Files (.RTF) Using SAS
Xingxing Wu, inVentiv Health Clinical, New York City, NY
Jyoti N. Rayamajhi, Eli Lilly and Company, Indianapolis, IN

RF-10. Maintaining Formats when Exporting Data from SAS® into Microsoft® Excel®
Nate Derby, Stakana Analytics, Seattle, WA
Colleen McGahan, BC Cancer Agency, Vancouver, BC, Canada

RF-11. Don’t Get Blindsided by PROC COMPARE
*** BEST PAPER ***
Joshua Horstman, Nested Loop Consulting, Indianapolis, IN
Roger Muller, Data-to-Events.com, Carmel, IN

RF-12. The Utility of the DATA Step Debugger in Logic Errors
Darryl Nousome, MPH, University of Southern California, Los Angeles, CA



SAS 101

S1-01. The Essence of DATA Step Programming
Arthur Li, City of Hope National Medical Center, Duarte, CA

S1-02. SAS®: The Power of Macros
Audrey Yeo, Aviva USA, West Des Moines, IA

S1-03. Data Cleaning 101: An Analyst’s Perspective
Anca Tilea, University of Michigan, Ann Arbor, MI
Deanna Chyn, University of Michigan, Ann Arbor, MI

S1-04. Using SAS ® to Analyze Data Submitted to the National Healthcare Safety Network (NHSN)
Michelle Hopkins, Stratis Health, Bloomington, MN

S1-05. Strategies and Techniques for Debugging SAS® Program Errors and Warnings (No paper available)
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

S1-06. Power Trip: A Road Map of PROC POWER
Melissa Plets, Grand Valley State University, Allendale, MI
Julie Strominger, Grand Valley State University, Allendale, MI

S1-07. Insurance Designation Randomization Application or How to Automate Your Bragging
Irvin Snider, Assurant Health, Milwaukee, WI

S1-08. Let the CAT Out of the Bag: String Concatenation in SAS 9
Joshua Horstman, Nested Loop Consulting, Indianapolis, IN

S1-09. Introducing a Colorful Proc Tabulate
Ben Cochran, The Bedford Group, Raleigh, NC

S1-10. Effectively Utilizing Loops and Arrays in the DATA Step
Effectively Utilizing Loops and Arrays in the DATA Step

S1-11. SAS®: Tips and Tricks
Audrey Yeo, Aviva USA, West Des Moines, IA

S1-12. Data Presentation 101: An Analyst’s Perspective
*** BEST PAPER ***
Deanna Chyn, University of Michigan, Ann Arbor, MI
Anca Tilea, University of Michigan, Ann Arbor, MI

S1-13. I Heart SAS® Users
Joanne Ellwood, Progressive Insurance, Mayfield, OH

S1-14. A Poor/Rich SAS® User’s Proc Export
Arthur S. Tabachneck, Ph.D., myQNA, Inc., Thornhill, ON, Canada
Tom Abernathy, Pfizer, Inc., New York, NY
Randy Herbison, Westat, Rockville, MD
Matthew Kastin, I-Behavior, Inc., Penn Valley, PA

S1-15. Writing Macro Do Loops with Dates from Then to When
Ronald J. Fehd, Stakana Analytics, Atlanta, GA