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MWSUG 2008 Conference Proceedings

Indianapolis, Indiana
October 12-14, 2008

Download the entire 2008 conference proceedings as a ZIP file (15.5MB)

Individual Paper PDFs:

Application Development

A01. A Toolbox of Technologies: Integrating SAS Applications with Flash Multimedia Incorporating HTML, and JavaScript
Tony Goodman, Dynamics Research Corporation
Terry Miller, Dynamics Research Corporation
Jeff Agnew, Software Consultant

A02. Data Set Investigator - Automated Exception Reporting from an electronic data dictionary with %DSI()
Matthew T. Karafa, PhD
Julie Thornton, MS

A03. Scheduling College Classes Using Operations Research Techniques
Barry E. King, Butler University, Indianapolis, IN
Terri Friel, Roosevelt University, Chicago, IL

A05. Loop-Do-Loop Around Arrays
Wendi L. Wright, CTB McGraw Hill, Harrisburg, PA

A06. How to Generate Dynamical and Flexible Codes in Clinical Trial
Xianming (Steve) Zheng, Eli Lilly and Company



Data Visualization

D01. Let Me Look At It! Graphic Presentation of Any Numeric Variable
Anastasiya Osborne, Farm Service Agency (USDA), Washington, DC

D02. A Picture Is Worth A Thousand Data Points - Increase Understanding by Mapping Data
Paul Ciarlariello, Sinclair Community College, Dayton, OH

D03. Creating Special Symbols in SAS® Graph
Shiqun (Stan) Li, Minimax Information Services, NJ
Wei Zhou, Eli Lilly and Company, IN



Hands-On Workshops

HOW07. PROC REPORT: Compute Block Basics – Part II Practicum
Arthur L. Carpenter, California Occidental Consultants

HOW08. The Plot Thickens from PLOT to GPLOT
Wendi L. Wright, CTB/McGraw-Hill, Harrisburg, PA



JMP

J02. Chemical Informatics using JMP™ PowerMV and ChemModLab
S. Stanley Young, National Institute of Statistical Sciences
Thomas H. Burger, Research Consultant
Michael S. Lajiness, Eli Lilly and Company
Wolf-D. Ihlenfeldt, Xemistry

J03. The Effective Billet Heating Method for Ultimate Seamless Tube Size Control
Nathan Abboud, The Timken Company
Michael Seifert, The Timken Company

J04. Analytical Method Improvement Yields Dramatic Decrease in Variation for a Final Formulation Process
Roger Norris, Eli Lilly and Company

J05. So, Who’s Afraid of Nonlinear Regression?
Heinz Plaumann, Ph.D., BASF Corporation, Wyandotte, MI

J06. Experimental Learning: Use of JMP Journal in Six Sigma Green and Black Belt Training
Amurthur Ramamurthy, Senior Master Black Belt, Covance Central Labs, Indianapolis, IN
Paul Cook, Master Black Belt at AMAZON.com, UK

J09. Consensus NMF: A unified approach to two-sided testing of micro array data
Paul Fogel, Consultant, Paris, France
S. Stanley Young, National Institute of Statistical Sciences

J11. Visualization and the Improvement of Anodized Parts Using JMP
Philip J. Ramsey, Ph.D., North Haven Group, LLC
Marie A. Gaudard, Ph.D., North Haven Group, LLC
Mia L. Stephens, M.S., North Haven Group, LLC

J12. Classification of Breast Cancer Cells Using JMP
Marie Gaudard, North Haven Group, Hernando, FL

J14. P Charts for Improved Analysis
Vin Kane, Principal Quality / Reliability Engineer, Tellabs

J15. SIPOC and Recursive Partitioning: Powerful Tool Combination for Transactional Six Sigma Projects
Amurthur Ramamurthy, Senior Master Black Belt, Covance Central Labs, Indianapolis, IN



Pharmaceutical Applications

P01. One-Step Change from Baseline Calculations, and Other DOW-Loop Tricks
Nancy Brucken, i3 Statprobe, Ann Arbor, MI

P02. Inverse Prediction Using SAS® Software: A Clinical Application
Jay N. Mandrekar, PhD, Division of Biostatistics, Mayo Clinic, Rochester, MN
Cristine Allmer, BS, Division of Biostatistics, Mayo Clinic, Rochester, MN

P03. Global Clinical Data Classification: A Discriminate Analysis
Amurthur Ramamurthy, Covance Central Laboratories, Indianapolis, IN
Gordon Kapke, Covance Central Laboratories, Indianapolis, IN
Jodi Yoder, Covance Central Laboratories, Indianapolis, IN

P04. A Multivariate Ranking Procedure to Assess Treatment Effects
Alan Y Chiang, Eli Lilly and Company, Indianapolis, IN
Grace Li, Eli Lilly and Company, Indianapolis, IN
Ying Ding, University of Michigan, Ann Arbor, MI
Ming-Dauh Wang, Eli Lilly and Company, Indianapolis, IN

P05. Data Mining and Analysis to Lung Disease Data
Guoxin Tang,University of Louisville,Louisville, KY

P06. Mastectomy Versus Lumpectomy In Breast Cancer Treatment
Beatrice Ugiliweneza, University of Louisville, Louisville, KY

P07. Blinding Sponsors for Open Label Studies: Challenges and Solutions
Quan Jenny Zhou, Eli Lilly and Company, Indianapolis, IN
Shengyan Hong, Eli Lilly and Company, Indianapolis, IN
Zhengping Ma, Eli Lilly and Company, Indianapolis, IN

P08. Confidence Interval Calculation for Binomial Proportions
Keith Dunnigan, Statking Consulting, Inc.



SAS Presents

SAS01. Find Out What You're Missing: Programming with SAS® Enterprise Guide®
Chris Hemedinger, SAS Institute Inc., Cary, NC

SAS02. Getting Started with ODS Statistical Graphics in SAS® 9.2
Robert N. Rodriguez, SAS Institute Inc., Cary, NC

SAS03. SAS® Stat Studio: A Programming Environment for High-End Data Analysts
Rick Wicklin, SAS Institute Inc., Cary, NC

SAS04. You Want ME to use SAS® Enterprise Guide® ??
Vincent DelGobbo, SAS Institute Inc., Cary, NC

SAS05. A Sampler of What's New in Base SAS® 9.2
Jason Secosky, SAS Institute Inc., Cary, NC

SAS06. Tips and Tricks for Creating Multi-Sheet Microsoft Excel Workbooks the Easy Way with SAS®
Vincent DelGobbo, SAS Institute Inc., Cary, NC

SAS07. New SAS® Performance Optimizations to Enhance Your SAS® Client and Solution Access to the Database
Mike Whitcher, SAS Institute, Cary, NC



Statistics

S01. Long-Term Value Modeling in the Automobile Industry
Jeff Ames, Ford Motor Company, Dearborn, MI
Cathy Hackett, Trillium Teamologies, Royal Oak, MI
Bruce Lund, Marketing Associates, Detroit, MI

S02. Survival Methods for Correlated Time-to-Event Data
James Bena, Cleveland Clinic, Cleveland, OH
Shannon McIntyre, Cleveland Clinic, Cleveland, OH

S03. The Difference Between Predictive Modeling and Regression
Patricia B. Cerrito, University of Louisville, Louisville, KY

S04. The Over-Reliance on the Central Limit Theorem
Patricia B. Cerrito, University of Louisville, Louisville, KY

S05. Imputation of Categorical Missing Data: A comparison of Multivariate Normal and Multinomial Methods
Holmes Finch, Ball State University
Matt Margraf, Ball State University

S06. A Comparison between Correlated ROC Curves Using SAS and DBM MRMC: A Case Study in Image Comparison
Dachao Liu, Northwestern University, Chicago, IL

S07. Creating Macros for Survival Data in Oncology Study
Jagannath Ghosh, MedFocus LLC, Chicago, IL



Tutorials

T01. Advanced PROC REPORT: Getting Your Tables Connected Using Links
Arthur L. Carpenter, California Occidental Consultants

T02. Exploring Efficient Ways to Collapse Variables
Yubo Gao, University of Iowa Hospitals and Clinics, Iowa City, Iowa

T03. PROC REPORT: Compute Block Basics – Part I Tutorial
Arthur L. Carpenter, California Occidental Consultants

T04. SAS® Tips, Tricks and Techniques
Kirk Paul Lafler, Software Intelligence Corporation

T06. A Tutorial on Reduced Error Logistic Regression (Paper not available)
Daniel M. Rice, Ph.D., Rice Analytics, St. Louis, MO

T07. Using Direct Standardization SAS® Macro for a Valid Comparison in Observational Studies
Daojun Mo, Eli Lilly and Company, Indianapolis, IN
Xia Li, inVentiv Clinical Solutions LLC, Indianapolis IN
Alan Zimmermann, Eli Lilly and Company, Indianapolis, IN