MWSUG 2009 Conference Proceedings

Cleveland, Ohio
October 11-13, 2009

Download the entire 2009 conference proceedings as a ZIP file (24.2MB)

Individual Paper PDFs:

Application Development

A01. High Performance Analytics with In-Database Processing
Stephen Brobst, Chief Technology Officer, Teradata Corporation, San Diego, CA
Keith Collins, Senior Vice President & Chief Technology Officer, SAS Institute, Cary, NC
Paul Kent, Vice President, R&D, Platform Research and Development, SAS Institute, Cary, NC
Michael Watzke, Teradata Architect, Teradata Corporation, Fitchburg, WI

A02. Using PROC OLAP to Build Cubes with NON-Additive Measures
Ben Cochran, The Bedford Group, Raleigh, NC

A03. A Cup of Coffee and Proc FCMP: I Cannot Function Without Them
*** BEST PAPER ***
Peter Eberhardt, Fernwood Consulting Group Inc, Toronto, ON

A04. No More Blue Screens - Running SAS® on Windows Servers
Joanne Ellwood, Progressive, Mayfield, Ohio

A05. Using AJAX and SAS® Stored Processes to Create Dynamic Search Suggest Functionality Similar to Google's®
Jeffery A. Fallon, Cardinal Health, Dublin, OH

A06. When the List Grows Too Long: A Strategy to Utilize Freeform User Input in Your SAS Stored Process Web Applications
Jeffery A. Fallon, Cardinal Health, Dublin, OH

A07. Turn-Key Performance Metrics using Base SAS® and Excel VBA
Michael C. Frick, Warren, MI

A08. Revolutionary BI: A Vision for Business Intelligence
Charles D. Kincaid, Engagement Director, SAS Center of Excellence, COMSYS

A09. An Example of Website “Screen Scraping”
Eric Lewerenz, My InnerView, Wausau, WI

A10. Using SAS® as an Archival Repository for DB2 under z/OS (or other DBMS)
Rich Morris, Progressive Insurance, Mayfield Village, Ohio

A14. The Super Genius Guide to Generating Dummy Data
Brian Varney, COMSYS, Portage, MI

A15. Demonstration of Organic Growth Modeling for B to B Marketing
Karen Ziton, Elite Technology Solutions

A16. SAS® 9.2 Enterprise BI Framework (Paper not provided)
Carmen Murico, SAS Institute Inc.

Data Visualization

G01. Visual + Detail = Effective Communication: Web-enabled Graph + Spreadsheet, Using SAS/GRAPH®, ODS, PROC PRINT, and Excel
LeRoy Bessler, Assurant Health, Milwaukee, WI

G02. Communication-Effective Reporting with Email/BlackBerry/iPhone, PowerPoint, Web/HTML, PDF, RTF/Word, Animation, Images, Audio, Video, 3D, Hardcopy, or Excel
*** BEST PAPER ***
LeRoy Bessler, Assurant Health, Milwaukee, WI

G04. Visualizing Key Performance Indicators using the GKPI Procedure
Brian Varney, COMSYS, Portage, MI

G05. Using graph template language to customize ODS statistical graphs
Dongsheng Yang, Cleveland Clinic Foundation, Cleveland, OH
Anne S. Tang, Cleveland Clinic Foundation, Cleveland, OH

G06. Seamlessly Delivering Web Based Information to an Organization (Paper not provided)
D.J. Penix, Pinnacle Solutions, Inc.

G07. A Guided Tour of ODS Graphics (Paper not provided)
Sanjay Matange, SAS Institute Inc.

Hands-On Workshops

H01. List Processing Basics: Creating and Using Lists of Macro Variables
Ronald J. Fehd, Centers for Disease Control and Prevention, Atlanta, GA
Art Carpenter, CA Occidental Consultants, Vista, CA

H02. 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, Oceanside, CA

H03. PROC REPORT: Compute Block Basics
Arthur L. Carpenter, California Occidental Consultants, Anchorage, AK

H04. Table Lookups: From IF-THEN to Key-Indexing
Arthur L. Carpenter, California Occidental Consultants, Vista, CA

H05. Exploring DICTIONARY Tables and SASHELP Views
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

H06. SAS® Performance Tuning Strategies and Techniques
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

H07. Exploring DATA Step and PROC SQL Programming Techniques
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

H08. More Tips and Tricks for Creating Multi-Sheet Microsoft Excel Workbooks the Easy Way with SAS®
Vincent DelGobbo, SAS Institute Inc, Cary, NC

In-Conference Training

I01. Getting Started with the Business Intelligence Tools from SAS®
Ben Cochran, The Bedford Group, Raleigh, NC

I02. Mixed Model Selection
George Fernandez, University of Nevada - Reno, Reno, NV

I03. Generating Custom-Formatted Excel Output from SAS® (Paper not provided)
Nathaniel Derby

I04. Advanced Topics in ODS
Lauren Haworth, Genentech, Inc., South San Francisco, CA

I05. Predictive Modeling in Enterprise Miner Versus Regression
Patricia B. Cerrito, University of Louisville, Louisville, KY

I06. Best Practices in Base SAS® Coding (Paper not provided)
Linda Jolley

JMP

J01. Improving Insurance Loss Ratios: Using JMP and SAS to See the Solution (Paper not provided)
Sam Gardner, SAS/JMP

J02. Application of JMP Custom Design Platform to Optimize a Crystallization Process for Competing Responses (Paper not provided)
*** BEST PAPER ***
Roger Norris, Eli Lilly and Company

J03. Drive Better Decisions with Market Information: Technology Forecasting (Paper not provided)
Heinz Plaumann, BASF

J04. Choice Experiments for Market Research and Other Features in JMP® 8 (Paper not provided)
John Sall, SAS Institute Inc.

J05. Data-Driven Story-Telling: Showcasing Visualization and Analytic Techniques with SAS® and JMP® (Paper not provided)
Jon Weisz, SAS

J06. Retention Modeling and Understanding the Lifetime Value of Your Insurance Customers (Paper not provided)
Mike Sweeney, Elite Technology Solutions
Sam Gardner, SAS Institute – JMP Team

Pharmaceutical Applications

P02. Obtaining the Patient Most Recent Time-stamped Measurements
Yubo Gao, University of Iowa Hospitals and Clinics, Iowa City, IA

P03. The Impact of the Food Safety Information on U.S. Poultry Demand
Lijia Mo, Kansas State University, Manhattan, KS

P05. Analysis of Metabolic Disorder - Gout
Sireesha Ramoju, University of Louisville, Louisville, KY

P06. Irritable Bowel Syndrome and Mood Disorders
Pedro Ramos, University of Louisville, Louisville, KY

P08. Analysis of Breast Cancer and Surgery as Treatment Options
Beatrice Ugiliweneza, University of Louisville, Louisville, KY

P09. Analysis of Emergency Room Waiting Time in SAS
Brent Wenerstrom, University of Louisville, Louisville, KY

P10. Dietary Glycemic Load and Risk of Colon Cancer: A Guide to Data Management
*** BEST PAPER ***
Svetlana Zelenskiy, Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, OH
Lauren Byrne, Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, OH
Cheryl L. Thompson, Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, OH
Thomas C. Tucker, Kentucky Cancer Registry, University of Kentucky, Lexington, KY
David Bruckman, Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, OH
Li Li, Department of Epidemiology & Biostatistics, Case Western Reserve University, Cleveland, OH

SAS 101

B01. A Little Stats Won’t Hurt You
*** BEST PAPER ***
Nathaniel Derby, Statis Pro Data Analytics, Seattle, WA

B02. Base-SAS® Tips, Tricks and Techniques
Kirk Paul Lafler, Software Intelligence Corporation, Spring Valley, CA

B03. Handy Procedures to Expand Your Analytics Skill Set
Mary MacDougall, PNC, Cleveland, OH

B04. Fun with SAS® Date/Time Formats and Informats
Randall Reilly, Covance Clinical Pharmacology, Madison, WI

B07. Eliminating Redundant Custom Formats (or How to Really Take Advantage of Proc SQL, Proc Catalog, and the Data Step)
Philip A. Wright, University of Michigan, Ann Arbor, MI

SAS Presents

S01. Best Practices for Configuring your IO Subsystem for SAS®9 Applications
Margaret A. Crevar, SAS Institute Inc.
Tony Brown, SAS Institute Inc.
Leigh A. Ihnen, SAS Institute Inc.

S02. How to Maintain Happy SAS® Users
Margaret Crevar, SAS Institute Inc., Cary, NC

S03. Introduction to Logistic Regression Using SAS® Software (Paper not provided)
Bob Derr, SAS Institute Inc.

S04. The XML Super Hero: An Advanced Understanding of Manipulating XML with SAS®
Richard Foley, SAS Institute Inc.
Paul Kent, SAS Institute Inc.

S05. Getting from SAS® 9.1.3 to SAS® 9.2: Migration Tools or Promotion Tools
Diane Hatcher and Sandy McNeill, SAS Institute Inc., Cary, NC

S06. Dear Miss SASAnswers: A Guide to Efficient PROC SQL Coding
Jane Stroupe and Linda Jolley, SAS Institute Inc., Cary, NC

S07. Methods, Models, and More: New Analyses Available with SAS/STAT® 9.2
Maura Stokes, SAS Institute Inc.
Robert Rodriguez, SAS Institute Inc.
Tonya Balan, SAS Institute Inc.

S08. R U There? (Interface to R in IML Studio) (Paper not provided)
Robert Rodriguez, SAS Institute Inc.

S09. CSSSTYLE: Stylish Output with ODS and SAS® 9.2
Cynthia L. Zender, SAS Institute Inc., Cary, NC

S10. Group Sequential Analysis Using the New SEQDESIGN and SEQTEST Procedures
Yang Yuan, SAS Institute Inc., Rockville, MD

Statistics & Data Mining

D02. A Comparison of Decision Tree and Logistic Regression Model
Xianzhe Chen, North Dakota State University, Fargo, ND

D03. Time Series Analysis 101: an introduction using Base SAS and SAS STAT
David Corliss, University of Toledo Department of Physics and Astronomy, Toledo, OH

D04. Using PROC CALIS and PROC CORR to Compare Structural Equation Modeling Based Reliability Estimates and Coefficient Alpha When Assumptions are Violated
Fei Gu, University of Kansas, Lawrence, KS
Todd Little, University of Kansas, Lawrence, KS
Neal M. Kingston, University of Kansas, Lawrence, KS

D05. A SAS Macro to Compute Added Predictive Ability of New Markers in Logistic Regression
Kevin F Kennedy, St. Luke’s Hospital-Mid America Heart Institute, Kansas City, MO
Michael J Pencina, Dept. of Biostatistics, Boston University, Harvard Clinical Research Institute, Boston, MA

D09. Mail Merge using SAS
Michael Stout, DePuy Orthopaedics, Inc, a Johnson & Johnson Company, Warsaw, IN

D10. Ranking Predictors in Logistic Regression
*** BEST PAPER ***
Doug Thompson, Assurant Health, Milwaukee, WI

D11. A Class of Predictive Models for Multi-Level Risks
Wensui Liu, JP Morgan Chase
Chuck Vu, Acxiom, Alpharetta, GA
Sandeep Kharidhi, Acxiom, Alpharetta, GA

D12. Outcome Research for Diabetic Inpatients with SAS Enterprise Miner 5.2
Xiao Wang, Department of Mathematics,University of Louisville, Louisville, KY

D13. Using the Data Step’s ATTRIB Statement to both Manage and Document Variables in a SAS® Dataset (lightly)
Philip A. Wright, University of Michigan, Ann Arbor, MI

D14. Effective Use of RETAIN Statement in SAS® Programming
Yi Zhao, Merck & Co. Inc., Upper Gwynedd, PA

Tutorials and Solutions

T01. Getting By with a Little Help from My Regular Expressions
Scott Davis, COMSYS, Portage, MI

T02. Connect with SAS Professionals Around the World with LinkedIn and sasCommunity.org
Kirk Paul Lafler, Software Intelligence Corporation
Charles Edwin Shipp, Shipp Consulting

T03. Using Base SAS® and SAS® Enterprise Miner™ to Develop Customer Retention Modeling
Rex Pruitt, PREMIER Bankcard, LLC, Sioux Falls, SD

T04. DO’s and DON’Ts of Generating Performance Metrics
Michael C. Frick, Warren, MI

T05. Clinical Programming at a Crossroads: Meeting Today’s Challenges and Preparing for Tomorrow
vid J. Polus, COMSYS Clinical, Portage, MI

T06. Making Your LinkedIn Profile Effective (Paper not provided)
Michael Mina

T07. Getting Correct Results from PROC REG
*** BEST PAPER ***
Nathaniel Derby, Statis Pro Data Analytics, Seattle, WA

T08. Things Dr Johnson Did Not Tell Me: An Introduction to SAS® Dictionary Tables
Peter Eberhardt, Fernwood Consulting Group Inc, Toronto, ON

T09. Where Does This Where Go?
Scott Davis, COMSYS, Portage, MI

T10. The SAS Data Step: Where Your Input Matters
Peter Eberhardt, Fernwood Consulting Group Inc., Toronto, ON

T11. Decision Making Using PROC OPTMODEL
Joseph Czyzyk, Central Michigan University Research Corporation, Mount Pleasant, MI