MWSUG 2011 Conference Proceedings
Kansas City, KS
September 25-27, 2011
Download the entire 2011 conference proceedings as a ZIP file (57MB)
Individual Paper PDFs:
Applications Development
AD01. ETL Anatomy 101Tom Miron, Systems Seminar Consultants, Madison, WI
AD02. Take a Fresh Look at SAS® Enterprise Guide®: From point-and-click ad hocs to robust enterprise solutions
Chris Schacherer, Clinical Data Management Systems, LLC, Madison, WI
AD03. SAS® BI Content Syndication with the REST Framework
Mike Vanderlinden, Experis, Portage, MI
AD04. Using the SAS BI Platform to Support Decision-making at a University
Ryan Cherland, University of Kansas, Lawrence, KS
AD05. Building a Data-Driven Computer-Assisted Interview Using SAS/AF®
Derek Morgan, Covidien, Hazelwood, MO
AD06. SAS® Analytic Solutions Win in Response to the “CARD Act of 2009”
Rex Pruitt, PREMIER Bankcard, LLC, Sioux Falls, SD
AD07. SAS® and Code Lists from Genericode
Larry Hoyle, Institute for Policy & Social Research, University of Kansas, Lawrence, KS
AD08. Leveraging the SAS® Open Metadata Architecture
Ray Helm, University of Kansas, Lawrence, KS
Yolanda Howard, University of Kansas, Lawrence, KS
AD09. “Compare Me” a SAS® Datasets Comparison Tool
Anurag Katare, Lake Hiawatha, NJ
Jayesh Soneji, Princeton, NJ
AD10. Application of SAS to monitoring loan defaults in consumer credit portfolios
Yevhen Yankovskyy, ATB Financial, Edmonton, Alberta, Canada
AD11. Software Time Estimation: Are We There Yet?
Jack Fuller, Experis Manpower Group, Portage, MI
AD12. What's in a (FILE)NAME: The important role of a simple statement
*** BEST PAPER ***
Chris Schacherer, Clinical Data Management Systems, LLC
AD13. Protecting Macros and Macro Variables: It Is All About Control
Eric Sun, sanofi-aventis, Bridgewater, NJ
Arthur L. Carpenter, CALOXY, Anchorage, AK
AD14. An Introduction to SAS® Hash Programming Techniques
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
AD15. An EXCEL- ent Method to %INCLUDE SAS Code
Irvin Snider, Assurant Health, Milwaukee, WI
AD16. Point-and-Click Programming Using SAS® Enterprise Guide®
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Mira Shapiro, Analytic Designers LLC, Bethesda, MD
AD17. Application for Survival Analysis through Microsoft Access GUI
Zhong Yan, i3, Indianapolis, IN
Jie Li, i3, Austin, TX
Jiazheng (Steven) He, i3, San Francisco, CA
AD18. Using SAS® to Extend Logistic Regression
Dachao Liu, Northwestern University, Chicago, IL
Coders Corner
CC01. Using SAS to Find the Best K for K-Nearest-Neighbor ClassificationCharlie Huang, Oklahoma State University, Stillwater, OK
CC02. How to Use SDTM Definition and ADaM Specifications Documents to Facilitate SAS Programming
Yan Liu, Sanofi Pasteur, Beijing, China
CC03. Your Age In People Years: Not All Formulas Are the Same
Art Carpenter, California Occidental Consultants, Anchorage, AK
CC04. Managing Datasets at Library Level via Dynamically Constructed, DICTIONARY Tables-Driven SAS Code
Jingxian Zhang, Quintiles, Overland Park, KS
CC05. Who are You? Use of Soundex and Merge to Cross-Walk one Dataset to Another
*** BEST PAPER ***
Misty Johnson, State of Wisconsin Dept. of Health Services, Madison, WI
CC06. Tracking Metadata within SAS Drug Development Using SDDPARMS
Bradford J. Danner, i3 Statprobe, Lincoln, NE
Matthew J. Wiedel, i3 Statprobe, Lincoln, NE
Katrina E. Canonizado, Celerion, Lincoln, NE
CC07. Using Recursion for More Convenient Macros
Nate Derby, Stakana Analytics, Seattle, WA
CC08. Customizing Survival Plot by %Survivalplot Macro
Zhong Yan, i3, Indianapolis, IN
CC09. Date/Time Issues with SAS: What to do if there is No Error
Diahn L. Allen, DLA Consulting LLC
CC10. Creating Metadata-Driven Program Logic with the SAS Call Execute Routine - An Example with CTC Grading of Laboratory Results
Robert W. Graebner, Quintiles, Overland Park, KS
CC13. Techniques for Creating Annotated 2D and 3D Pie Charts
Erika Kelly, MRIGlobal, Kansas City, MO
CC14. A Graphics Tool for the Evaluation of Longitudinal Outcomes in Clinical Care
Matthew C. Fenchel, M.S., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Laurie M. Kahill, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Katharine D. Sebastian, A.A.S., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Raouf S. Amin, M.D., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Rhonda D. VanDyke, Ph.D., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
CC15. In Search of the LOST CARD
Andrew T. Kuligowski
Data Visualization and Graphics
DG01. Case Study: Geospatial location analysis & reporting application using SAS, Google Maps & MS ExcelAdney Fernandes, Cognizant Technology Solutions Corporation, Pune, India
DG03. Contour Plots for Time Series Analysis
David J. Corliss, University of Toledo / Department of Physics and Astronomy, Toledo, OH
DG04. Annotate your SG Procedure Graphs
Mekhala Acharya, EMMES Corp., Rockville, MD
DG06. Using SAS® GTL to Visualize Your Data when there is Too Much of it to Visualize
*** BEST PAPER ***
Perry Watts, Stakana Analytics, Elkins Park, PA
Nate Derby, Stakana Analytics, Seattle, WA
DG07. Graphing a Progression of Time Series Plots with ODS Graphics
Nate Derby, Stakana Analytics, Seattle, WA
Laura Vo, Stakana Analytics, Seattle, WA
Perry Watts, Stakana Analytics, Elkins Park, PA
DG08. Interpreting the Differences Among LSMEANS in Generalized Linear Models
Robin High, University of Nebraska Medical Center, Omaha, NE
DG09. SG Techniques: Telling the Story Even Better!
Chuck Kincaid, Experis, Portage, MI
DG10. Creating Multidimensional Data in SAS for Excel Pivot Tables
Chandy Karnum, Ace Analytics Inc., Madison, WI
DG11. Clearing Hurdles in Report Optimization: Custom Sorting Macros, Traffic-lighting Entire Rows, and Forcing SAS Formats into Microsoft Excel®
Jacob Serafino, Analytics Infogroup®, Papillion, NE
Mitch Weiler, Analytics Infogroup®, Papillion, NE
Asha Jayaprakash, Analytics Infogroup®, Papillion, NE
DG12. Area under a Curve: Calculation and Visualization
Patricia M. Herbers, M.S., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Deborah A. Elder, M.D., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Jessica G. Woo, Ph.D., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Hands-On Workshops
HW01. Quick Results with PROC SQL®*** BEST PAPER ***
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
HW02. Quick Results with Output Delivery System (ODS)
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
HW03. An Introduction to SAS/GRAPH or Quick Tricks with the GPLOT and GCHART Procedures And the Annotate Facility
Ben Cochran, The Bedford Group, Raleigh, NC
HW04. Using SAS® Arrays to Manipulate Data
Ben Cochran, The Bedford Group, Raleigh, NC
HW05. Creating Stylish Multi-Sheet Microsoft Excel Workbooks the Easy Way with SAS®
Vincent DelGobbo, SAS Institute Inc., Cary, NC
HW06. Using the 9.2 Statistical Graphic Procedures
Chuck Kincaid, Experis, Portage, MI
HW07. PROC TABULATE: Getting Started
Art Carpenter, California Occidental Consultants
HW08. SAS® Macro: Symbols of Frustration? %Let us help! A Guide to Debugging Macros
Kevin P. Delaney, Centers for Disease Control and Prevention, Atlanta, GA
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK
JMP
JP01. Win With SAS®, JMP®, and Interest In-House GroupsCharles Edwin Shipp, Shipp Consulting, San Pedro, CA
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
JP02. Benefits of sasCommunity.org® for JMP® Coders
Charles Edwin Shipp, Shipp Consulting, San Pedro, CA
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
JP05. Using JMP® Visualizations to Build a Statistical Model
*** BEST PAPER ***
George J. Hurley, The Hershey Company, Hershey, PA
JP06. JMP® as an Analytic Hub: Using JMP to Build Custom Applications via SAS®and R
Kelci Miclaus, SAS Institute, Cary, NC
Clay Barker, SAS Institute, Cary, NC
Jun Ge, SAS Institute, Cary, NC
JP07. Introducing SAS® Structural Equation Modeling for JMP®: A New User Interface That Brings the Power of SAS/STAT® Software to JMP Software
Wayne Watson, SAS Institute Inc. Cary, NC
JP08. Driving Clinical Safety Reviews with Data Standards
Geoffrey Mann, SAS Institute, Cary, NC
Pharmaceutical Apps
PH01. Automated or Manual Validation: Which One is for You?Richann Watson, i3, Batavia, OH
Patty Johnson, i3, San Diego, CA
PH02. Summary Statistics in Rows
John Henry King, Ouachita Clinical Data Services, Inc., Mount Ida, AR
PH03. Data Quality Review for Missing Values and Outliers
Ying Guo, i3, Indianapolis, IN
Bradford J. Danner, i3, Lincoln, NE
PH04. Case Study: Generating a DSMC report from an ORACLE database with SAS® PROC REPORT
*** BEST PAPER ***
Shannon M. Morrison, M.S., Quantitative Health Sciences – Cleveland Clinic Foundation, Cleveland, OH
Matthew T. Karafa, PhD., Quantitative Health Sciences – Cleveland Clinic Foundation, Cleveland, OH
PH05. I Don’t Look Good in Orange or Stripes
Susan M. Fehrer, BioClin, Inc., Emporia, KS
PH06. Is It Time to Upgrade CDISC SDTM from v1.1/v3.1.1 to v1.2/v3.1.2?
Susan M. Fehrer, BioClin, Inc., Emporia, KS
PH07. Oncology Trials 101 - The Basics and Then Some
Dave Polus, Experis, Portage, MI
PH08. Using a Double DOW Loop to Compute Progression Free Survival
Matthew Nizol, United BioSource Corporation, Ann Arbor, MI
Posters
PO01. Objective tumor response and RECIST criteria in cancer clinical trialsJian Yu, I3, Indianapolis, Indiana
PO03. Consulting: Career Path Considerations
Charles Edwin Shipp, Shipp Consulting, Inc., San Pedro, CA
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
PO04. Pagination in Clinical Trial PROC REPORT ODS
Chao Su, Advanced Clinical, Deerfield, IL
William Conover, Advanced Clinical, Deerfield, IL
PO05. Creating a Clean Multi-Tabbed SDTM Dataset Specification Spreadsheet
Dongju Liu, Advanced Clinical, Deerfield, IL
William Conover, Advanced Clinical, Deerfield, IL
PO06. A Practical Approach to Process Improvement Using Parallel Processing
*** BEST PAPER ***
Viraj Kumbhakarna, Cognizant Technology Solutions Corporation, Lake Hiawatha, NJ
PO07. The Effects of Previous Trial Validity on the Gaze Cuing Effect: A Meta-Analysis
Deanna Schreiber-Gregory, North Dakota State University, Fargo, ND
PO08. Does Lawrence Smoking Ban Impact Kansas Liquor Sales?
Lijia Mo, Rouch Financial Group, Lincoln, NE
SAS 101
S101. Remove Orphan Claims and Third party Claims for Insurance DataQiling Shi, NCI Information Systems, Inc., Nashville, TN
S102. SAS® Macro Programming Tips, Tricks and Techniques
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
S103. Simple Rules to Remember When Working with Indexes
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
S104. Top Ten SAS® Sites for Programmers: A Review
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, JMP 2 Consulting, Inc., San Pedro, CA
S105. Utilizing SAS® for Complete Report Automation
*** BEST PAPER ***
Brent D. Westra, Mayo Clinic, Rochester, MN
S106. Connect with SAS® Professionals Around the World with LinkedIn® and sasCommunity.org®
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, Shipp Consulting, San Pedro, CA
S107. Moving between an XML document and SAS using the SAS XML Mapper
Margo Law, South Dakota State University, Brookings, SD
S108. You Can’t Spell ‘Assume’ without S.A.S.
Mike Tangedal, Capella University
S109. SAS® Enterprise Guide: A Revolutionary Tool!
Jennifer First, Systems Seminar Consultants, Madison, WI
S110. Fuzzy Merges - A Guide to Joining Data sets with Non-Exact Keys Using the SAS SQL Procedure
Robert W. Graebner, Quintiles, Overland Park, KS
S111. Dealing with Duplicates in Your Data
Joshua M. Horstman, First Phase Consulting, Inc., Indianapolis, IN
Roger D. Muller, First Phase Consulting, Inc., Carmel, IN
SAS Presents
SP01. Tips and Techniques for Automating the SAS(R) Add-In for Microsoft Office with Visual Basic for ApplicationsTim Beese, SAS Institute Inc., Cary, NC
SP02. Becoming a Better Programmer with SAS® Enterprise Guide® 4.3
Andy Ravenna, SAS Institute Inc., New York, NY
SP03. On Deck: SAS/STAT® 9.3
Maura Stokes, SAS Institute, Cary, NC
Fang Chen, SAS Institute, Cary, NC
Ying So, SAS Institute, Cary, NC
SP04. Optimizing Clinical Research Operations with Business Analytics
Dave Handelsman, SAS, Cary, NC
SP06. What Are People Saying about Your Company, Your Products, or Your Brand?
Kathy Lange, SAS Institute Inc., Cary, NC
Saratendu Sethi, SAS Institute Inc., Cambridge, MA
SP07. JMP® as an Analytic Hub: Using JMP to Build Custom Applications via SAS®and R
Kelci Miclaus, SAS Institute, Cary, NC
Clay Barker, SAS Institute, Cary, NC
Jun Ge, SAS Institute, Cary, NC
SP08. The Perfect Marriage: The SAS® Output Deliver System (ODS) and Microsoft Office
Chevell Parker, SAS Institute, Cary, NC
SAS and Platform Specific Topics
PS01. Consulting: Career Path ConsiderationsKirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA
Charles Edwin Shipp, JMP 2 Consulting, Inc., San Pedro, CA
PS02. A Hitchhiker's guide for performance assessment & benchmarking SAS® applications
*** BEST PAPER ***
Viraj Kumbhakarna, Cognizant Technology Solutions, Lake Hiawatha, NJ
Anurag Katare, Cognizant Technology Solutions, Lake Hiawatha, NJ
PS03. A Step by Step Approach to Preparing for a SAS® Intelligence Platform Environment Deployment/Migration
Brian Varney, Experis Business Analytics Practice, Portage, MI
PS04. The Emergence of Patterns in SAS Usage and Infrastructure
Chuck Kincaid, Experis, Kalamazoo, MI
Mike Vanderlinden, Experis, Kalamazoo, MI
Statistics, Data Mining, and Analysis
SA01. Money Demand Estimation using SAS®Gerard G Tano, Southern Illinois University Carbondale, Carbondale, IL
SA02. SAS® Model Selection Macros for Complex Survey Data Using PROC SURVEYLOGISTIC/SURVEYREG
Fang Wang, NORC at the University of Chicago, Chicago, IL
Hee-Choon Shin, NORC at the University of Chicago, Chicago, IL
SA03. Before Logistic Modeling - A Toolkit for Identifying and Transforming Relevant Predictors
*** BEST PAPER ***
Steven Raimi, Marketing Associates, LLC, Detroit, MI
Bruce Lund, Marketing Associates, LLC, Detroit, MI
SA06. Using SAS to Create Sales Expectations for Everyday and Seasonal Products
Lory Ellebracht, Hallmark Cards, Inc., Kansas City, MO
Jamie Netherton, Hallmark Cards, Inc., Kansas City, MO
Casey Gentry, Hallmark Cards, Inc., Kansas City, MO
SA07. The Full Monty
Joe Roma, Roma Statistical Consulting, Racine, WI
Irvin Snider, Assurant Health, Milwaukee, WI
SA08. Regression calibration with multiple imputations for red blood cell fatty acids
James V. Pottala, OmegaQuant, Sioux Falls, SD
SA09. Deep Dive into the PIM and DDI Data
Michelle Hopkins, Stratis Health, Bloomington, MN
SA10. PROC NLMIXED for Basic Non-Linear Regression
Keith Dunnigan, Strategic Staffing Solutions, St Louis, MO
SA11. Estimating Design Effects for Means, Proportions and Totals from Complex Sample Survey Data Using SAS® Proc Surveymeans
Trent D. Buskirk, Ph.D., Saint Louis University School of Public Health, Saint Louis, MO
SA13. Bootstrap power analysis using SAS®
Doug Thompson, Thompson Research Consulting LLC, Chicago, IL
Nort Holschuh, Bell Institute of Health and Nutrition, General Mills Inc., Minneapolis, MN
Bruce Barton, University of Massachusetts Medical School, Worcester, MA
Ann Albertson, Bell Institute of Health and Nutrition, General Mills Inc., Minneapolis, MN
SA14. Increased Life Expectancy from Positive Perceptions of Retirement
Reuben Ng, Yale School of Public Health, New Haven, CT
Deepak C. Lakra, University of Western Ontario, London, ON, Canada
Becca R. Levy, Yale School of Public Health, New Haven, CT
SA15. Dynamically Evolving Systems: Cluster Analysis Using Time
David J. Corliss, University of Toledo / Department of Physics and Astronomy, Toledo, OH
SA16. An Introduction to the Analysis of Rare Events
Nate Derby, Stakana Analytics, Seattle, WA
SA17. Evaluation of Novel Markers in Risk Prediction
Kevin F Kennedy, St. Luke’s Hospital-Mid America Heart Institute, Kansas City, MO
SA18. A Macro to Estimate Sample-size Using the Non-Centrality Parameter of a Non-Central F-Distribution
Matthew C. Fenchel, M.S., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Raouf S. Amin, M.D., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Rhonda D. VanDyke, Ph.D., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
SA19. A Lazy Programmer’s Macro for Descriptive Statistics’ Tables
Matthew C. Fenchel, M.S., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Gary L. McPhail, M.D., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
Rhonda D. VanDyke, Ph.D., Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
SA20. Comparing Over-the-Counter Drug Prices and Availability Using Nonparametric Tests
Deanna N Schreiber-Gregory, North Dakota State University, Fargo, ND
SA21. Outlier resistance of multivariate bioequivalence procedures
Dr. Srinand P. Nandakumar, Quintiles Inc., Overland Park, KS
Dr. Joseph W. McKean, Western Michigan University, Kalamazoo, MI
Tutorials and Solutions
TS01. The Essentials of SAS® Dates and TimesDerek Morgan, Covidien, Hazelwood, MO
TS02. Building Better Macros: Basic Parameter Checking for Avoiding "ID10T" Errors.
Matthew T. Karafa, PhD, Cleveland Clinic Foundation, Cleveland, OH
TS03. What to Do with a Regular Expression
Scott Davis, Experis, Portage, MI
TS04. Ways of Creating Macro Variables
Kelley Weston, Quintiles, Overland Park, KS
TS05. Data Manipulation with SQL
*** BEST PAPER ***
Mara Werner, Department of Health and Human Services, Office of Inspector General, Chicago, IL
TS06. Import and Output XML Files with SAS
Yi Zhao, Merck Sharp & Dohme Corp, Upper Gwynedd, Pennsylvania
TS07. Taming the Interactive SAS® Environment: Tips and Tricks for VIEWTABLE, The Enhanced Editor and More
Roger D. Muller, Ph.D., Phase Consulting, Carmel, IN
Joshua M. Horstman, First Phase Consulting, Indianapolis, IN