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MWSUG 2017 Conference Proceedings

St. Louis, Missouri
October 8-10, 2017

BI / Customer Intelligence

BI02-SAS. If You Build It, Will They Understand? Designing Reports for the General Public in SAS® Visual Analytics
Jesse Sookne, SAS
Ed Summers, SAS
Julianna Langston, SAS
Karen Mobley, SAS

BI03-SAS. Accessibility and SAS® Visual Analytics Viewers: Which Report Viewer Is Best for Your Users' Needs?
Jesse Sookne, SAS
Kristin Barker, SAS
Joe Sumpter, SAS
Lavanya Mandavilli, SAS



Banking and Finance

BF01. The Cox Hazard Model for Claims Data: Bayesian non-parametric approach
Samuel Berestizhevsky, Consultant
Tanya Kolosova, Co-author

BF02. Computing Risk Measures for Loan Facilities with Multiple Lines of Draws
Chaoxian Cai, BMO Harris Bank

BF03. Untangle Customer's Incrementality using Uplift Modeling with a Case Study on Direct Marketing Campaign
Hairong Gu, Alliance Data
Yi Cao, Alliance Data
Chao Xu, Alliance Data



Beyond the Basics SAS

BB015. Advanced Macro: Driving a Variable Parameter System with Metadata
Art Carpenter, CA Occidental Consultants

BB042. Demystifying Intervals
Derek Morgan, PAREXEL

BB047. Extraction and Use of Text Strings with SAS when Source exceeds the 32k String Length Limit
John Schmitz, Luminare Data

BB071. Fifteen Functions to Supercharge Your SAS Code
Josh Horstman, Nested Loop Consulting

BB113. You Did That With SAS? Combining Text with Graphics Output to Create Great Looking Reports.
Ben Cochran, The Bedford Group

BB114. Tackling Unique Problems by Using TWO SET Statements in ONE DATA Step
Ben Cochran, The Bedford Group

BB124. Exploring HASH Tables vs. SORT/DATA Step vs. PROC SQL
Lynn Mullins, PPD
Richann Watson, Experis

BB129-SA. DATA Step in SAS Viya: Essential New Features
Jason Secosky, SAS

BB142. DOSUBL and the Function Style Macro
John King, Ouachita Clinical Data Services, Inc.



Data Visualization and Graphics

DV01. An Introduction to ODS Statistical Graphics
Kirk Paul Lafler, Software Intelligence Corporation

DV02. Waterfall Plots in Oncology Studies in the Case of Multi-Arms Design
Ilya Krivelevich, Eisai Inc
Kalgi Mody, Eisai Inc
Simon Lin, Eisai Inc

DV04. A Macro that can Create U.S State and U.S County KML Files
Ting Sa, Cincinnati Children's Hospital Medical Center

DV07. A Big Data Challenge: Visualizing Social Media Trends about Cancer using SAS® Text Miner
Mia Lyst, Pinnacle Solutions, Inc
Scott Koval, Pinnacle Solutions, Inc
Yijie Li, Pinnacle Solutions, Inc.

DV08-SAS. Data Can Be Beautiful: Crafting a Compelling Story with SAS® Visual Analytics
Cheryl Coyle, SAS

DV09. Patient Safety with SAS® Visual Analytics
Piyush Singh, TCS
Prasoon Sangwan, TCS
Ghiyasudin Khan, TCS



Data for Good

DG01. Correlation and Structural Equation Analysis on the Effects of Anti-Discrimination Policies and Resources on the Well Being of Lesbian, Gay, and Bisexual College Students
Brandy Sinco, University of Michigan
Michael Woodford, Wilfred Laurier University, Ontario, CA
Jun Sung Hong, Wayne State University
Jill Chonody, Indiana University

DG02. Exploring the Relationship Between Substance Abuse and Dependence Disorders and Discharge Status: Results and Implications
Deanna Schreiber-Gregory, Henry M Jackson Foundation for the Advancement of Military Medicine

DG03. Lag Models with Social Response Outcomes
David Corliss, Peace-Work

DG04. The (Higher) Power of SAS®
Andrea Frazier, Presence Health



Hands-on Workshops

HW01. Hands-on Introduction to SAS® and the ODS Excel® Destination
Kirk Paul Lafler, Software Intelligence Corporation

HW02. Using a Few SAS Functions to Clean Dirty Data
Ben Cochran, The Bedford Group

HW03. Base SAS® and SAS® Enterprise Guide® ~ Automate Your SAS World with Dynamic Code; Your Newest BFF (Best Friend Forever) in SAS
Kent Phelps, Illuminator Coaching, Inc.
Ronda Phelps, Illuminator Coaching, Inc.

HW04. A Hands-On Introductory Tour of SAS® ODS Graphics
Ted Conway, Self

HW05. Intermediate SAS® ODS Graphics
Chuck Kincaid, Experis Business Analytics



Pharmaceutical Applications

PH01. Mapping MRI data to SDTM and ADaM
Lingling Xie, Eli Lilly and Company
Xiaoqi Li, Eli Lilly and Company

PH02. ISO 8601 and SAS®: A Practical Approach
Derek Morgan, PAREXEL

PH04. AIR Binder 2.0: A Dynamic Visualization, Data Analysis and Reporting SAS Application for Preclinical and Clinical ADME Assays, Pharmacokinetics, Metabolite Profiling and Identification
Hao Sun, Covance, Inc.
Kristen Cardinal, Covance, Inc.
Richard Voorman, Covance, Inc.

PH05. Automated Validation of Complex Clinical Trials Made Easy
Richann Watson, Experis
Josh Horstman, Nested Loop Consulting

PH06. ADQRS: Basic Principles for Building Questionnaire, Rating and Scale Analysis Datasets
Nancy Brucken, InVentiv Health Clinical
Karin Lapann, Shire



Rapid Fire

RF01. Ignorance is not bliss - understanding SAS applications and product contents
Jayanth Iyengar, Data Systems Consultants LLC

RF02. Quotes within Quotes: When Single (') and Double (") Quotes are not Enough
Art Carpenter, CA Occidental Consultants

RF03. No News Is Good News: A Smart Way to Impute Missing Clinical Trial Lab Data
Ming Yan, Eli Lilly

RF05. Macro that can Provide More Information for your Character Variables
Ting Sa, Cincinnati Children's Hospital Medical Center

RF06. Cleaning Messy Data: SAS Techniques to Homogenize Tax Payment Data
Aaron Barker, Iowa Department of Revenue

RF07. PROC DOC III: Self-generating Codebooks Using SAS®
Louise Hadden, Abt Associates Inc.

RF08. What Are Occurrence Flags Good For Anyway?
Nancy Brucken, InVentiv Health Clinical



SAS 101

SA01. An Introduction to PROC REPORT
Kirk Paul Lafler, Software Intelligence Corporation

SA02. If you need these OBS and these VARS, then drop IF, and keep WHERE
Jayanth Iyengar, Data Systems Consultants LLC

SA03. The Essentials of SAS® Dates and Times
Derek Morgan, PAREXEL

SA04. PROC SORT (then and) NOW
Derek Morgan, PAREXEL

SA05. Working with Datetime Variable from Stata
Haiyin Liu, University of Michigan
Wei Ai, University of Michigan

SA06. Merge with Caution: How to Avoid Common Problems when Combining SAS Datasets
Josh Horstman, Nested Loop Consulting

SA07. Beyond IF THEN ELSE: Techniques for Conditional Execution of SAS® Code
Josh Horstman, Nested Loop Consulting

SA09. Parsing Useful Data Out of Unusual Formats Using SAS®
Andrew Kuligowski, HSN

SA10. The Building Blocks of SAS® Datasets - S-M-U (Set, Merge, and Update)
Andrew Kuligowski, HSN

SA11. Before You Get Started: A Macro Language Preview in Three Parts
Art Carpenter, CA Occidental Consultants

SA12. Writing Code With Your Data: Basics of Data-Driven Programming Techniques
Joe Matise, NORC

SA13. Make That Report Look Great Using the Versatile PROC TABULATE
Ben Cochran, The Bedford Group

SA14. The Battle of the Titans (Part II): PROC TABULATE versus PROC REPORT
Kirk Paul Lafler, Software Intelligence Corporation
Ben Cochran, The Bedford Group
Ray Pass, Retired - and loving it!

SA15. A Walk through Time: Growing Your SAS Career
Art Carpenter, CA Occidental Consultants



Statistics / Advanced Analytics

AA01. Using SAS to Compare Two Estimation Methods on the Same Outcome: Example from First Trimester Pregnancy Weights
Brandy Sinco, University of Michigan
Edith Kieffer, University of Michigan
Kathleen Welch, University of Michigan
Diana Welmerink Bolton, University of Michigan

AA02. Logistic Model Selection with SAS® PROC's LOGISTIC, HPLOGISTIC, HPGENSELECT
Bruce Lund, Independent Consultant

AA04. Claim Analytics
Mei Najim, Gallagher Bassett Services, Inc.

AA05. Unconventional Statistical Models with the NLMIXED Procedure
Robin High, University of Nebraska Medical Center

AA06. Multiple Imputation of Family Income Data in the 2015 Behavioral Risk Factor Surveillance System
Jia Li, NIOSH
Aaron Sussell, NIOSH

AA07. GREMOVE, Reassign, and let's GMAP! A SAS Trick for Generating Contiguous Map Boundaries for Market-Level Research
Chad Cogan, Arbor Research Collaborative for Health
Jeffrey Pearson, Arbor Research Collaborative for Health
Purna Mukhopadhyay, Arbor Research Collaborative for Health
Charles Gaber, Arbor Research Collaborative for Health
Marc Turenne, Arbor Research Collaborative for Health

AA08. Correcting for Selection Bias in a Clinical Trial
Shana Kelly, Spectrum Health

AA11. Dimensionality Reduction using Hadamard, Discrete Cosine and Discrete Fourier Transforms in SAS
Mohsen Asghari, Computer Engineering and Computer Science Department, University Of louisville
Aliasghar Shahrjooihaghighi, Computer Engineering and Computer Science Department, University Of louisville
Ahmad Desoky, Computer Engineering and Computer Science Department, University Of louisville

AA12. Nothing to SNF At: Evaluating an intervention to reduce skilled nursing home (SNF) length of stay
Andrea Frazier, Presence Health

AA13. How Can an NBA Player Be Clutch?: A Logistic Regression Analysis
Logan Edmonds, Oklahoma State University

AA14. Multicollinearity: What Is It and What Can We Do About It?
Deanna Schreiber-Gregory, Henry M Jackson Foundation for the Advancement of Military Medicine

AA15. Oscars 2017 - Text Mining & Sentimental Analysis
Karthik Sripathi, Oklahoma State University

AA16. Text and Sentiment Analysis of customer tweets of Nokia using SAS® Enterprise Miner and SAS® Sentiment Analysis Studio
Vaibhav Vanamala, Oklahoma State University

AA17. Tornado Inflicted Damages Pattern
Vasudev Sharma, Oklahoma State University

AA18. Agricultural Trip Generation - Linking Spatial Data and Travel Demand Modeling using SAS
Alan Dybing, North Dakota State University - Upper Great Plains Transportation Institute

AA19-SAS. Getting Started with Multilevel Modeling
(No paper available)
Mike Patetta, SAS

AA20-SAS. Power and Sample Size Computations
(No paper available)
John Castelloe, SAS

AA99. Tips and Best Practices Using SAS® in the Analytical Data Life Cycle
(No paper available)
Tho Nguyen, Teradata
Paul Segal, Teradata



System Architecture and Administration

SY01. Using Agile Analytics for Data Discovery
(No paper available)
Bob Matsey, Teradata

SY04-SAS. The Future of the SAS Platform
(No paper available)
Amy Peters, SAS



Tools of the Trade

TT01. Generating Reliable Population Rates Using SAS® Software
Jack Shoemaker, MDwise

TT02. Check Please: An Automated Approach to Log Checking
Richann Watson, Experis

TT03. Arbovirus, Varicella and More: Using SAS® for Reconciliation of Disease Counts
Misty Johnson, State of WI-DHS

TT04. Code Like It Matters: Writing Code That's Readable and Shareable
Paul Kaefer, UnitedHealthcare

TT06. From Device Text Data to a Quality Dataset
Laurie Smith, Cincinnati Children's Hospital Medical Center

TT07. Proc Transpose Cookbook
Doug Zirbel, Wells Fargo and Co.

TT08. Get Smart! Eliminate Kaos and Stay in Control - Creating a Complex Directory Structure with the DLCREATEDIR Statement, SAS® Macro Language, and Control Tables
Louise Hadden, Abt Associates Inc.

TT09. An Array of Possibilities: Manipulating Longitudinal Survey Data with Arrays
Lakhpreet Gill, Mathematica Policy Research

TT10. Fully Automated Updating of Arbitrarily Complex Excel Workbooks
David Oesper, Lands' End



e-Posters

PO01. Red Rover, Red Rover, Send Data Right Over: Exploring External Geographic Data Sources with SAS®
Louise Hadden, Abt Associates Inc.

PO02. SAS/GRAPH® and GfK Maps: a Subject Matter Expert Winning Combination
Louise Hadden, Abt Associates Inc.

PO03. Data Quality Control: Using High Performance Binning to Prevent Information Loss
Lakshmi Nirmala Bavirisetty, Independent SAS User
Deanna Schreiber-Gregory, Henry M Jackson Foundation for the Advancement of Military Medicine

PO05. Let's Get FREQy with our Statistics: Let SAS® Determine the Appropriate Test Statistic Based on Your Data
Lynn Mullins, PPD
Richann Watson, Experis