All Conference Years


About SESUG

About SESUG

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ACADEMIC SECTIONS


 
 
 

Application Development

Chairs:   Brian Varney
              Charlotte Baker

The Applications Development section will present a wide array of papers on topics including SAS macro design, maximizing performance, and data cleaning.  Presentations on the different ways that SAS can be customized, extended, and used in concert with other software packages to develop or improve a process will also be included.  Other speakers will describe how to exploit SAS modules that can significantly improve performance and sustainability.  Authors come from different industries will give step-by-step instructions describing a process.  This is an outstanding opportunity to see how a project or industry-specific solution is accomplished, such as projects within drug development, predictive modeling, customer retention, healthcare, insurance or other business applications.

Author(s) Title
Christopher Johnson Integrating Microsoft VBScript and SAS
William Zupko One SAS To Rule Them All…
Raissa Kouadjo Using PROC SURVEYSELECT: Random Sampling
Stephen Sloan Using SAS PROC SQL to Create a Build Combinations Tool to Support Modularity
Mike Hunsucker SAS/GRAPH and Annotate Facility--More Than Just a Bunch of Labels and Lines
Kirk Paul Lafler Five Little Known, But Highly Valuable and Widely Usable, PROC SQL Programming Techniques
Bruce Gilsen Masking data to obscure confidential values: a simple approach
William Zupko Unlock SAS Code Automation with the Power of Macros
Brian Varney GreenSpace: A Macro to Improve a SAS Data Set Footprint
Vincent Hunter Automating Simulation Studies with Base SAS(r) Macros
David Abbott Rapidly Assessing Data Completeness
Patricia Guldin Programming Compliance Made Easy with a Time Saving Toolbox
Harry Droogendyk SAS Data Integration Studio – Take Control with Conditional & Looping Transformations
Haikuo Bian, Carlos Jimenez and David Maddox A Methodology for Truly Dynamic Prompting in SAS® Stored Processes
Andre Watts and Lisa Sklar The Perfect Marriage: Using SAS Enterprise Guide, the SAS Add-In for Microsoft Office, and Excel to support enrollment forecasting at a large university
Peter Davis and Mark Asiala You’ve Got Mail®: Automating SAS® from an Email
Tho Nguyen Data Labs with SAS and Teradata: Value, Purpose and Best Practices

  

 
 

Banking and Finance

Chairs:   Charyn Faenza
              Harry Drooogendyk

This section’s presentations focus on how Banking and Finance professionals leverage their SAS tool kits to address a myriad managerial and regulatory issues, covering a broad set of industry topics.  Presentations highlight how SAS is used to provide accurate, timely, and effective information to stakeholders in this section.  Presenters will discuss techniques in data integration, data analysis, and reporting using standard SAS Office Analytics and Visual Analytics as well as industry-specific SAS solutions such as SAS High-Performance Risk, SAS Anti-Money Laundering, and SAS Risk Management for Banking.

Author(s) Title
Phillip Julian Migrating Databases from Oracle to Teradata
Nancy Wilson Getting Your SAS® Program to do Your Typing for You!
Nate Derby and Mark Keintz Reducing Credit Union Member Attrition with Predictive Analytics
Bogdan Gadidov and Benjamin McBurnett Population Stability and Model Performance Metrics Replication for Business Model at SunTrust Bank
Svetlana Gavrilova and Maxim Terekhov Analysis of the Impact of Federal Funds Rate Change on US Treasuries Returns using SAS
Wei Chen Regulatory Stress Testing—A Manageable Process with SAS®

  

 
 

Building Blocks

Chairs:   Andrea Zimmerman
              Meenal Sinha

The Building Blocks section is aimed at both beginning and intermediate programmers.  It includes fundamental topics like the DATA step and simple PROCs, but also more advanced topics like ODS, Macro, SQL, as well as efficient DATA step programming.  Presentations provide a greater understanding of how to use SAS to solve analytical, reporting, and data management issues.  Some advanced papers will help intermediate programmers implement enhanced techniques, and take advantage of the many possibilities afforded by SAS software.

Author(s) Title
Kirk Paul Lafler and Mira Shapiro Point-and-Click Programming Using SAS® Enterprise Guide®
Ron Cody A Survey of Some Useful SAS Functions
Bruce Gilsen Tales from the Help Desk 6: Solutions to common SAS ® Tasks
Paul Dorfman Using the SAS Hash Object with Duplicate Key Entries
Keith Renison Introduction to SAS® Data Loader: The Power of Data Transformation in Hadoop
Sarah Woodruff A Beginner’s Babblefish: Basic Skills for Translation Between R and SAS®
Rachael Becker and Drew Doyle Sampling in SAS using PROC SURVEYSELECT
David Izrael and Elizabeth Axelrod Hash: Is it always the best solution?
John Cohen Table Lookups: Getting Started With Proc Format®
Renee Canfield No FREQ-in Way
Louise Hadden Better Metadata Through SAS® II: %SYSFUNC, PROC DATASETS, and Dictionary Tables
Lisa Eckler Don’t Forget About Small Data
Claudine Lougee To Macro or Not... that is the Question
Harry Droogendyk Arrays – Data Step Efficiency
Rachel Straney PROC TRANSPOSE: Flip your Data 90o and Save Time
Jack Hall Hash Objects for Everyone

  

 
 

Code Doctors

Do you have code that does not work?  Do you have a technique you cannot master?  What about a macro that gives you that strange error message, or a loop that does not quit?  Well you get the idea, bring all these things to the Code Doctor Table in the Demo area.  We may not be able to fix'em all but we'lll give it a try.

  

 
 

Coder's Corner

Chairs:   Sharon Avrunin-Becker
              Sarah Woodruff

Every SAS programmer, from the beginner to the expert, has found new or unusual ways to solve problems with SAS.  Coder’s Corner is the place where these tips and tricks come to light.  Presentations are 10 minutes in length and provide useful nuggets of programming, or techniques that make jobs easier.  You may find a solution to a problem that was bugging you for months, or find a dynamic shortcut.  Come and learn! What simple tricks can unlock a SAS mystery?

Author(s) Title
Lynn Imel and Thomas Mule Implementing a Bayesian Approach to Record Linkage
Robert Matthews RUN; RUN; RUN; - Methods for Running Multiple Programs in a Series
Stephen Sloan Running Parts of a SAS Program while Preserving the Entire Program
Nushrat Alam Merging and Analysis of Complex Survey Data Sets by using Proc Survey Procedures in SAS
Julio Ruiz A Macro to Copy, Rename, Update and Move Your SAS Programs- All In One Click
Kannan Deivasigamani Count the Number of Delimiters In the Input File
Seungyoung Hwang Tips for Identifying Patient Characteristics Associated with Diagnostic Concordance between Two Measures Using SAS®
Louise Hadden PROC CATALOG, the Wish Book SAS® Procedure
Louise Hadden and Roberta Glass Document and enhance your SAS(R) code, data sets, and catalogs with SAS functions, macros and SAS metadata
John Wedeles Using PROC MEANS to sum duration of eligibility for Medicaid beneficiaries
Pamela Reading The COMPRESS Function: Hidden Superpowers
Claudine Lougee Past, Present and Future... who KNEW (Knows New Exciting Ways)?
Jason Salemi All Data Are (Most Likely) Not Created Equal: A SAS® Macro to Compare Structure and Data Across Multiple Datasets
Huei-Ling Chen and Hong Zhang The Mystery of Automatic Retain in a SAS Data Step
Adetosoye Oladokun Successful Ways to Add and Drop Data, While Also Reformatting Data
Darryl Putnam 29 Shades of Missing
Christopher Johnson Date Dimension
Barbara Moss and Anna Flynn Delivering Quarterly Reporting Every Month – A Departure From the Traditional Calendar Definition, Using Formats
Christopher Aston Using Multilabel Formats in SAS to Analyze Data Over Moving Periods of Time
Julie Liu Where do the titles or footnotes go when using PROC SGPLOT in ODS PDF?
Suzanne Dorinski Beautiful PROC CONTENTS Output Using the ODS Excel Destination
William Zupko Having a Mean Headache on Summary Data? Using SAS to Compute Actual Data from Summary Data
Shane Rosanbalm The %LetPut Macro, and Other Proactive Macro Debugging Techniques
Yi-Hsin Chen IA_CTT: A SAS® Macro for Conducting Item Analysis Using the Classical Test Theory
Sai Mandagondi Accessing and Extracting Unstructured XML Data using SAS and Python
John Cohen Because We Can: Using SAS® System Tools to Help Our Less Fortunate Brethren

  

 
 

Hands On Workshop

Chairs:   Mike Sadof
              Kristen Harrington

These popular 2-hour presentations utilize live SAS sessions.  The presenter will demonstrate code and procedures in real time, and provide datasets and code for participants to submit the procedures concurrently.  The datasets and code will also be available for download prior to the session, enabling attendees to submit the code on their personal computers. A limited number of laptops will be provided for attendees to use as well.

Author(s) Title
Kirk Paul Lafler Quick Results with SAS® Enterprise Guide®
Ron Cody An Introduction to Perl Regular Expressions
Chuck Kincaid Introduction to ODS Graphics
Chuck Kincaid Intermediate ODS Graphics
John Cohen A Tutorial on the SAS® Macro Language
Ronald Fehd Applications Development, Theory or Practice
Paul Dorfman HOW to DoW
Kirk Paul Lafler Application Development Techniques Using PROC SQL

  

 
 

Pharma and Healthcare

Chairs:   Abbas Tavakoli
              Jeff Kromrey

Papers in this section focus on using the SAS System to find solutions for analysis and reporting as it relates to drug/device discovery, disease prevention, patient care and satisfaction, insurance risk and operations, as well as local and national healthcare agencies.

Author(s) Title
Angela Teng How to Build Study Quality Surveillance for a Clinical Study?
Lois Lynn and Marina Komaroff Multilevel Randomization
Verlin Joseph A Descriptive Analysis of Reported Health Issues in Rural Jamaica
Ram Poudel, Maleeha Shahid, Mark Wolraich and Jennifer Lockhart Use of SAS and SAS Bridge for ESRI in the Study of Spatial Patterns of Children with Special Health Needs and Providers in Oklahoma
Thanh Pham, Eun Sook Kim, Diep Nguyen, Yan Wang, Jeffrey Kromrey and Yi-Hsin Chen ANOVA_Robust: A SAS® Macro for Various Robust Approaches to Testing Mean Differences in One-Factor ANOVA Models
Michelle Dahnke and Tyra Dark Same Question, Different Name: How to Merge Responses
Michelle Dahnke and Tyra Dark Creating Quartiles from Continuous Responses: Making Income Data Manageable
An-Tsun Huang Using SAS Programing To Identify Super-utilizers And Improve Healthcare Services
Monika Lemke Prescription Opioid Use in the U.S. in 2012: Characterizing Sustained vs. Infrequent Use Using the Medical Expenditure Panel Survey

  

 
 

Planning, Support, and Administration

Chairs:   Jason Brinkley
              Ron Fehd

If all, or part, of your SAS time includes supporting users - whether through systems architecture and administration or through consulting, training, and hiring - this section is the place for you to learn from experiences of your peers in the SAS community!  Presentations include guidelines, best practices, techniques, and resources for working efficiently and effectively in the SAS support community.

Author(s) Title
Stephanie Thompson Handling Sticky Situations - The Paper
Tho Nguyen SAS In-Database Decision Management for Teradata: Making the Best Decisions Possible
Michael Sadof Tips and Tricks for Organizing and Administering Metadata
Scott Milbuta, Carlos Piemonti and Ulf Borjesson UCF SAS® Visual Analytics: Implementation, Usage, and Performance
Jason Brinkley Tips and Tricks for Introductory Workshops in SAS for Health Professionals
Xiangxiang Meng Predictive Modeling Using SAS® Visual Statistics: Beyond the Prediction
Steve Garrison Get cozy with your data sources using LSF queue technology: One LSF Cluster to Rule them All
Jiangtang Hu When Bad Things Happen to Good SAS Programmers
Barbara Okerson and Jennifer Harney Supporting SAS in the Workplace: A Corporate SAS User Community
Krisa Tailor Establishing a Health Analytics Framework
Kirk Paul Lafler A Review of "Free" Massive Open Online Content (MOOC) for SAS® Learners
Kirk Paul Lafler Differentiate Yourself
Kirk Paul Lafler and Charlie Shipp Downloading, Configuring, and Using the Free SAS® University Edition Software

  

 
 

Posters

Chairs:   Erik Larsen
              Charyn Faenza
              Bob Bolen

The Poster Section covers any area including: SAS fundamentals; statistics; business intelligence; medical research, data mining; survey/panel results; social networking; and industry applications for the pharmaceutical, finance, education, environmental and entertainment industries; and all other uses of SAS software.  Posters will be displayed electronically on a wide screen monitor.  In addition, a corresponding paper based upon the poster will be published in the conference proceedings.  There will also be a time to meet authors to discuss their posters with conference attendees (“Meet the Presenter” session).

Author(s) Title
Barbara Okerson Maintaining a 'Look and Feel' throughout a Reporting Package Created with Diverse SAS® Products
Elizabeth Stewart, Ivette A. Lopez and Charlotte Baker Assessing Health Behavior Indicators Among Florida Middle School Students
Abbas Tavakoli and Mary Boyd Using SAS to Examine Health-Promoting Life Style Activities of Upper Division Nursing Students one of the major University in South Eastern
Sheetal Shiralkar Reporting Of Treatment Emergent Adverse Events Based On Pooled Data Analysis or Country Specific Submissions: A Case Study
Alec Zhixiao Lin Automating Preliminary Data Cleaning in SAS
Abbas Tavakoli, Sabra Custer-Smith and Ni Yu-Min Using SAS to Examine Health Effects of Intimate Partner Violence among HIV+ Women
Nancy McGarry Ouch, how did that get here? The pitfalls of merging ...
Jin Liu and Fan Pan A SAS Macro to Investigate Statistical Power in Meta-analysis
Elizabeth Axelrod Documentation As You Go: aka Dropping Breadcrumbs
Rebecca Fink, David Izrael, Sarah W. Ball and Sara M.A. Donahue Many Tables, Short Turnaround: Displaying Survey Results Quickly and Efficiently
Imelda Go Using SAS® Macros to Split a Data Set into Several Output Files
Charles Coleman SAS Macros for Constraining Arrays of Numbers
Rachael Becker Time Series Analysis: U.S. Military Casualties in the Pacific Theater during World War Two
Deniz Soyer Streamlining Medicaid Enrollment Reporting and Calculation of Enrollment Trends Using Macro and PROC Statements in SAS
Yin Burgess PROC REG: A SAS Macro to Determine Cut Score for a Universal Pre-School Maladaptive Screener

  

 
 

Reporting and Information Visualization/JMP

Chairs:   Mira Shapiro
              Barbara Okerson

This section contains presentations that demonstrate visualizing and presenting data in unique and innovative ways for effective communication.  Visual representation and interactive techniques allow users to intuitively explore, discover and comprehend large amounts of information.

This section also includes JMP®, the statistical discovery software from SAS, which provides users with the ability to explore and discover hidden stories and trends in data while easily converting this information into visual displays to share with end users.

Author(s) Title
Tricia Aanderud How to Become the MacGyver of Data Visualizations
Li Hui Chen, Manuel Figallo and Josh McCullough Bridging the Gap: Importing Health Indicators Warehouse data into SAS® Visual Analytics using Stored Processes and APIs
Tim Beese Take Your Data Analysis and Reporting to the Next Level by Combining SAS® Office Analytics, SAS® Visual Analytics, and SAS® Studio
Ryan Kumpfmiller How We Visualize Data and How to Apply Those Findings in SAS® Visual Analytics
Shweta Doshi and Julie Davis A Journey From Data To Dashboard: Visualizing the University Instructional Classroom Utilization and Diversity Trends with SAS Visual Analytics
Yuxin (Ellen) Jiang Key Features in ODS Graphics for Efficient Clinical Graphing
Sharon Avrunin-Becker How to Make a Stunning State Map Using SAS/Graph® for Beginners
Christianna Williams and Louise Hadden PROC RANK, PROC SQL, PROC FORMAT and PROC GMAP Team Up and a (Map) Legend is Born!
Melvin Alexander Text Analytics Using JMP®
Shane Rosanbalm The Last Axis Macro You'll Ever Need
Charlie Shipp Design of Experiments (DOE) Using JMP® and SAS®
Rick Andrews Creating Geographic Rating Area Maps: How to Combine Counties, Split Counties, and use Zip Code Boundaries
Daniel Ralyea and Karen Price Layout the Grid and You Control the Document: ODS Meets OOP and You Reap the Benefits
Robert Seffrin From SAS Data to Interactive Web Graphics Built Through PROC JSON

  

 
 

Statistics and Data Analysis

Chairs:   Darryl Putnam
              Rachel Straney

Presentations in this section address the transformation of raw data into useful information.  This year, the section will include topics that will be of interest to a wide range of SAS users, including statistical analysts, statistical programmers, statisticians, and DATA step programmers.  Innovative applications of established methods to new or unusual scenarios are also provided within this section.  In addition, presentations involve the application of methods that many users of SAS statistics may not commonly see, such as methods for categorical, longitudinal or censored data.  The section will present methods to facilitate analysis of very large data arrays, such as those that result from genetic studies or national surveys.

Author(s) Title
Jason Schoeneberger and Bethany Bell MIXED_RELIABILITY: A SAS Macro for Estimating Lambda and Assessing the Trustworthiness of Random Effects in Multilevel Models
Rana Jaber Testing the Gateway Hypothesis from Waterpipe to Cigarette Smoking among Youth Using Dichotomous Grouped-Time Survival Analysis (DGTSA) with Shared frailty in SAS®
Andrew Hummel and Shevawn Christian Optimizing Pilot Connection Time Using PROC REG and PROC LOGISTIC
Drew Doyle Regression Analysis of the Levels of Chlorine in the Public Water Supply in Orange County, FL
Peter Flom Alternative Methods Of Regression When OLS Is Not the Right Choice
Whitney Smiley, Zhaoxia Guo, Mihaela Ene, Genine Blue, Elizabeth Leighton and Bethany Bell An Intermediate Guide to Estimating Multilevel Models for Categorical Data using SAS® PROC GLIMMIX
George Knafl Adaptive Fractional Polynomial Modeling in SAS®
Jessica Montgomery, Sean Joo, Anh Kellerman, Jeffrey Kromrey, Diep Nguyen, Thanh Pham, Patricia Rodriguez de Gil and Yan Wang High-Performance Procedures in SAS 9.4: Comparing Performance of HP and Legacy Procedures
Bruce Lund Probability Density for Repeated Events
Stephen Looney A SAS Macro for Improved Correlation Coefficient Inference
Deanna Schreiber-Gregory How Latent Structure Analyses Can Improve the Fit of a Regression Model
Tho Nguyen A Demonstration of SAS Analytics in Teradata
Seungyoung Hwang Introducing Two-Way and Three-Way Interactions into the Cox Proportional Hazards Model Using SAS®
Jiangtang Hu Confidence Intervals for Binomial Proportion Using SAS: The All You Need to Know and No More…
Macaulay Okwuokenye and Karl E. Peace A SAS Algorithm for Imputing Discrete Missing Outcomes Based on Minimum Distance
Dennis Beal A Macro for Calculating Percentiles on Left Censored Environmental Data using the Kaplan-Meier Method
Peter Wludyka Using SAS to Create an Effect Size Resampling Distribution for a Statistical Test
Chuck Kincaid How to be a Data Scientist with SAS(r)
John Castelloe Power and Sample Size Computations
Stephanie Thompson Where Did My Students Go?
Yusheng Zhai, Katherine Kahn, Alissa O’Halloran and Tammy Santibanez Comparing Results from Cox Proportional Hazards Models using SUDAAN® and SAS® Survey Procedures to a Logistic Regression Model for Analysis of Influenza Vaccination Coverage
Yan Wang, Seang-Hwane Joo, Patricia Rodriguez de Gil, Jeffrey Kromrey, Rheta E. Lanehart, Eun Sook Kim, Jessica Montgomery, Reginald Lee, Chunhua Cao and Shetay Ashford An Empirical Comparison of Multiple Imputation Approaches for Treating Missing Data in Observational Studies
Yan Wang, Yi-Hsin Chen, Issac Y. Li and Chunhua Cao Can Fit Indices Yielded from the SAS GLIMMIX Procedure Select the Accurate Q-matrix?
Alec Zhixiao Lin Integrating PROC REG and PROC LOGISTIC for Collinearity Examination, Sample Scoring and Model Evaluation
Jin Liu, Fan Pan, Yin Burgess and Christine DiStefano Behavioral Trajectories: An Analysis of Growth Patterns and Predictors of Changes from Preschool to First Grade

  

 
 
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