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All Conferences Years 




Application/Macro Development

Co-Chairs:   Sarah Woodruff
                    Sharon Avrunin-Becker

The Application and Macro Development section wants to include your ideas on how SAS communicates with other programs and software as well as wanting to see your innovative macro designs.  Presentations can come from any industry and solutions could be for problems large or small.  Papers should give users the tools they need to implement these concepts in their own projects.  Have you gotten SAS to “play well with others” as part of a multi-step task?  Have you developed macros that could save others from a headache at the end of the day?  We want to read about your solutions and see you presenting in 2016!

Author(s) Title
John R. Gerlach Creating Viable SAS® Data Sets From Survey Monkey® Transport Files
David Vandenbroucke Universal File Flattener
Ross Bettinger %SUBMIT_R: A SAS® Macro to Interface SAS and R
Jiangtang Hu New Game in Town: SAS® Proc Lua with Applications
Alex Buck Breaking up (Axes) Isn't Hard to Do: A Macro for Choosing Axis Breaks
Harry Droogendyk Moving Data and Results Between SAS® and Microsoft Excel
Tsung-hsun Tsai and Yung-chen Hsu Using PROC FCMP for Short Test Assembly
Troy Hughes A Waze App for Base SAS®: Automatically Routing around Locked Data Sets, Bottleneck Processes, and Other Traffic Congestion on the Data Superhighway
Chao-Ying Hsieh The Demystification of a Great Deal of Files
Saritha Bathi Multiple Studies! DataDefinitionTracker, Made Easy!



Co-Chairs:   Charyn Faenza
                    Ken Swann

We are looking for SAS users in the financial services and insurance sector to discuss the important issues facing our industry.  Share your experiences with others in your peer group highlighting how SAS was able to deliver timely and accurate results within your organization.  We strongly encourage first time presenters to step forward to share their insights.  Chances are, if you have encountered a challenge you could solve with SAS, many others have or will find that same challenge and could benefit from your experiences.  We are interested in a broad range of subjects specific to financial services and insurance: regulatory reporting; anti-money laundering and fraud detection; risk analysis; predicative modeling; forecasting; analyzing complex assets and their values; and customer relationship management are just a sampling of the available subject areas - feel free to propose your own!

Author(s) Title
Mark Keintz Leads and Lags: Static and Dynamic Queues in the SAS® DATA STEP
Jonas Bilenas Using SAS®/QC to Design Optimal Experimental Designs in Consumer Lending
Jonas Bilenas and Nish Herat Using Regression Splines in SAS® STAT Procedures
Chaoxian Cai Computing Risk Measures for Cross Collateralized Loans Using Graph Algorithms
Anirban Chakraborty Know your Interest Rate


Building Blocks

Co-Chairs:   Jeffrey Kromrey
                    Rachel Straney

Building Blocks is intended for SAS programmers at all levels from beginner to advanced.  Appropriate topics include fundamentals such as DATA step manipulations and simple PROCs, but the section also includes advanced topics in ODS, Macro programming, and SQL.  These presentations will provide beginners with a greater understanding of how to use SAS to solve analytical, reporting, and data management issues, and will help more advanced programmers implement enhanced techniques to build on the power and flexibility afforded by SAS software.

Author(s) Title
Stephen Sloan and Dan Hoicowitz Fuzzy Matching: Where Is It Appropriate and How Is It Done? SAS® Can Help
Ronald Fehd True is not False: Evaluating Logical Expressions
Shane Rosanbalm AutoHotKey: an Editor-independent Alternative to SAS® Keyboard Abbreviations
Jayanth Iyengar If you need these OBS and these VARS, then drop IF and keep WHERE
Kirk Paul Lafler An Introduction to SAS® Hash Programming Techniques
Kirk Paul Lafler Building a Better Dashboard Using Base-SAS® Software
Mike Zdeb An Easy Route to a Missing Data Report with ODS+PROC FREQ+A Data Step
John Cohen Array Programming Basics
Chao-Ying Hsieh Dynamically Changing Time Zones and Daylight Savings on Time Series Data
Kirk Paul Lafler Introduction to PROC REPORT
Jonas Bilenas and Kajal Tahiliani The Power of PROC FORMAT
Dylan Holt and Wilhelmina Ross Divide & Conquer: Simple Sub-Datasets Creation with Call Execute
Michael Raithel PROC DATASETS; The Swiss Army Knife of SAS® Procedures
Kirk Paul Lafler SAS® Debugging 101
Kirk Paul Lafler Introduction to ODS Statistical Graphics
LaSelva Gwen Creating Test Data Using SAS® Hash Tables
Bob Bolen Taming the Bear Make Your Programs Easier to Control and Monitor
Matthew Hoolsema Using PROC EXPAND to Easily Manipulate Longitudinal and Panel Data
Fuad Foty Handling Numeric Representation SAS® Errors Caused by Simple Floating-Point Arithmetic Computation
Joe Matise Writing Code With Your Data: Basics of Data-Driven Programming Techniques
William E Benjamin Jr. All Aboard! Next Stop is the Destination Excel


Coder's Corner

Co-Chairs:   Charlotte Baker
                    Linda Sullivan

Every SAS programmer from the beginner to the expert has found new or unusual ways to solve problems with SAS.  Coders' Corner is the place to share tips and tricks, useful nuggets of programming, or techniques that make jobs easier.  Presentations are 10 minutes in length and can come from any of a broad range of topics.  If you have found a solution to a problem that was (de)bugging you or have worked out a dynamic short-cut, come and share your knowledge.  What might now seem simple to you could unlock a SAS mystery for another user!

Author(s) Title
Verlin Joseph Using an Array to Examine Gastric and Colorectal Cancer Risk Factors
Patricia Guldin and Young Zhuge What Do You Mean My CSV Doesnt Match My SAS® Dataset?
Imelda Go Using SAS® to Get a List of File Names and Other Information from a Directory
Louise Hadden PROC DOC III: Self-generating Codebooks Using SAS(R)
Aaron Brown A Five-Step Quality Control Method: Checking for Unintended Changes to SAS® Datasets
Elizabeth Axelrod Talk to Me!
Lifang Zhang Extract Information from Large Database Using SAS® Array, PROC FREQ, and SAS Macro
John Cohen Tips for Pulling Data from Oracle® Using PROC SQL® Pass-Through
Mike Zdeb Some _FILE_ Magic
Jinson Erinjeri and Angela Soriano Personalized Birthday Wisher (PBW): An Indispensable SAS® Tool for Your Workplace
Ronald Fehd Macro Code to Test Existence of Various Objects
Alex Buck When PROPCASE Isnt Proper: A Macro Supplement for the SAS® Function
Raghav Adimulam Using CALL VNAME to Populate Missing Data from a Default Values Lookup Dataset
Alec Zhixiao Lin Simplifying the Use of Multidimensional Array in SAS®
Joe Matise Flexible Programming with Hash Tables
Rachel Straney Using SAS® Macros to Extract P-values from PROC FREQ
Brandon Welch Dynamically Setting Decimal Precision Using PUTN
Yinghua Shi Your Own SAS® Macros Are as Powerful as You Are Ingenious
Shane Rosanbalm Cover Your Assumptions with Custom %str(W)ARNING Messages
Nushrat Alam From Professional Life to Personal Life: SAS® Makes It Easy
Jack Shoemaker WAPTWAP, but remember TMTOWTDI


Data Management/Big Data

Co-Chairs:   Chuck Kincaid
                    Bob Eichelman

From the beginning, Data Integration has been one of the mainstays of SAS software.  Since then it has grown to include the full suite of Data Management capabilities including Data Quality, Data Governance, Master Data Management and Data Federation.  SESUG is creating a new section to highlight the capabilities of SAS Data Management including the various ways SAS leverages Big Data.  We invite technical papers that show others how to use any of the Data Management components.  These presentations will include case studies demonstrating analyses and implementations, while providing helpful insights and lessons learned along the way.

Author(s) Title
John Gao A New Method To Deal With 2 Level Variables in Big Data Analysis
Alan Dunham Fuzzy Name-Matching Applications
Christine Warner Using Proc FCMP To Improve Fuzzy Matching
Ahmed Al-Attar Super Boost Data Transpose Puzzle
Ahmed Al-Attar Using SAS® Hash Object to Speed and Simplify Survey Cell Collapsing Process
Stanley Legum Removal of PII
Tom McCall and Louise Hadden What to Expect When You Need to Make a Data Delivery: Helpful Tips and Techniques
Troy Hughes Sorting a Bajillion Records: Conquering Scalability in a Big Data World
Troy Hughes Spawning SAS® Sleeper Cells and Calling Them into Action: Implementing Distributed Parallel Processing in the SAS University Edition Using Commodity Computing To Maximize Performance
Harry Droogendyk Your database can do complex string manipulation too!
Troy Hughes Stress Testing and Supplanting the SAS® LOCK Statement: Implementing Mutex Semaphores To Provide Reliable File Locking in Multi-User Environments To Enable and Synchronize Parallel Processing



Co-Chairs:   Abbas Tavakoli
                    William Benjamin

The e-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 uses of SAS software.  Ideally, a well-developed poster is a self-explanatory PowerPoint, achieving both coverage and clarity.  Posters will be displayed on a large monitor.  In addition, a corresponding paper based upon the e-poster will be published in the conference proceedings.  There will be a time to meet authors to discuss their posters with conference attendees (“Meet the Presenter” session).  Submissions are welcomed from attendees at all levels of SAS experience.

Author(s) Title
Abbas Tavakoli and Karen Worthy Using SAS® to Examine Relationships among Leadership Styles of College of Nursing Deans and Faculty Job Satisfaction Levels in Research Intensive Institutions
Abbas Tavakoli, Katherine Chappell and Senna Dejardins Using SAS® to Examine the Relationship between Primary Caregivers' Adverse Childhood Experiences (ACE) and Child Abuse Allegations
Yubo Gao Patients with Morbid Obesity and Congestive Heart Failure Have Longer Operative Time and Room Time in Total Hip Arthroplasty
Yu Feng The Power of Interleaving Data
Pallabi Deb and Piyush Lashkare Formula 1: Analytics behind the tracks to the podium
Michelle White, Thomas Schroeder, Li Hui Chen and Jean Mah Privacy Protection using Base SAS®: Purging Sensitive Information from Free Text Emergency Room Data
Alec Zhixiao Lin Extracting Email Domains and Geo-Processing IP Addresses in SAS®
Sangar Rane and Mohit Singhi The Orange Lifestyle
Stephen Sloan Using SAS® to create a Build Combinations Tool to Support Modularity
Nancy McGarry Strike a pose! Quick and Easy Camera Ready Reporting with SAS®
Troy Hughes A Failure to EXIST: Why Testing for Data Set Existence with the EXIST Function Alone Is Inadequate for Serious Software Development in Asynchronous, Multi-User, and Parallel Processing Environments
Drew Doyle An Analysis of the Repetitiveness of Lyrics in Predicting a Songs Popularity
Fan Pan and Jin Liu SAS® Macro for Automated Model Selection Involving PROC GLIMMIX and PROC MIXED
Vivek Doijode and Neha Singh Predicting student success based on interactions with virtual learning environment
Jametta Magwood-Golston, Abbas Tavakoli, Nurses of Moultrie Heart Failure Unit at Palmetto Health Richland, Christina Payne, Harmony Robinson, Veronica Deas and Forrest Fortier Applying SAS® to Explore the Utilization and Impact of Sensitive Clinical Indicators on a Heart Failure Unit
Mukesh Kumar Singh Text mining and sentiment analysis on video game user reviews using SAS® Enterprise Miner" and SAS® Sentiment Analysis Studio
Rajesh Tolety Text Analysis of American Airline Reviews


Hands On Workshops

Co-Chairs:   Michael Sadof
                    Jason Brinkley

These 2-hour sessions will be presented utilizing a live SAS session where the presenter will demonstrate code and procedures in real time with a specific task or goal in mind to accomplish within the two hour HOW session.  The datasets and code will also be available for download prior to the session, enabling attendees to submit the code on their personal computers if desired.  This session is best for step-by-step presentation of:

  • Data step programming
  • Report writing
  • Dates and times
  • Macro language
  • Functions and formats
  • New features of SAS
Papers will be selected based upon content and the presenter's proven ability to present in an interactive SAS session.  The presenter will need to prepare a power point as well as sample code for demonstration.

Author(s) Title
John Cohen A Tutorial on the SAS® Macro Language
Paul Dorfman Fundamentals of the SAS® Hash Object
Jonas Bilenas and Kajal Tahiliani Making Sense of PROC TABULATE
Vince DelGobbo New for SAS® 9.4: A Technique for Including Text and Graphics in Your Microsoft Excel Workbooks, Part 1
Jason Brinkley Introduction to Data Simulation
Leanne Goldstein A Short Introduction to Longitudinal and Repeated Measures Data Analyses
Kirk Paul Lafler, Mira Shapiro and Ryan Paul Lafler Quick Results with SAS® Enterprise Guide®


Life Sciences/Healthcare/Insurance

Co-Chairs:   Andrea Zimmerman
                    Lesa Caves

Papers in the Life Sciences/Healthcare/Insurance section will 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.  Possible topics include:

  • Discussions of the use of SAS® Drug Development, SAS Clinical Data Integration and SAS Patient Safety.
  • Various aspects of implementing CDISC standards such as the Study Data Tabulation Model (SDTM) and the Analysis Data Model (ADaM).
  • Solutions to reporting and data processing requirements which relate to the Affordable Care Act.
  • The use of healthcare data to evaluate quality of care, possible fraud and patient satisfaction in a hospital setting.

Author(s) Title
Karen Wallace A Novel Approach to Calculating Medicare Hospital Readmissions for the SAS® Novice
Stanley Legum Protecting the Innocent (and your data)
Yichen Zhong Sankey Diagram with Incomplete Data From a Medical Research Perspective
Aran Canes How is Healthcare Cost Data Distributed? Using Proc Univariate to Draw Conclusions about Millions of Different Customers
Gregory Weller and Alex Buck Are You Sure That Is Correct?: An Overview Of Good Practices For Dataset And Output Validation
Desiree Jonas and Shamarial Roberson Evaluating Sociodemographic and Geographic Disparities of Hypertension in Florida using SAS®
Kathy Fraeman A General SAS® Macro to Implement Optimal N:1 Propensity Score Matching Within a Maximum Radius
Kathy Fraeman I See de Codes: Using SAS® to Process and Analyze ICD-9 and ICD-10 Diagnosis Codes Found in Administrative Healthcare Data
Venita DePuy SDTM What? ADaM Who? A Programmers Introduction to CDISC
Adeline Wilcox Sample Size Estimation with PROC FREQ and PROC POWER
Binoy Varghese and Sagar Rana Building Efficiencies in Standard Macro Library using Polymorphism



Co-Chairs:   Harry Droogendyk
                    Darryl Putnam

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 share your experiences with other members of the SAS community. This section will include guidelines, best practices, techniques, and resources for working efficiently and effectively in the SAS support community. Possible topics are:

  • SAS Systems architecture and administration, including:
    • Installation, deployment, and migration
    • Virtualization
    • Performance monitoring and tuning
  • Other SAS systems support, including:
    • Recruiting, hiring and maintaining qualified staff
    • Training and skill development
    • SAS help desk support
    • Project planning and management

Author(s) Title
Kirk Paul Lafler Whats Hot Skills for SAS® Professionals
Troy Hughes Take a SPA Day with the SAS® Performance Assessment (SPA): Baselining Software Performance across Diverse Environments To Elucidate Performance Placement and Performance Drivers
Troy Hughes Your Local Fire Engine Has an Apparatus Inventory Sheet and So Should Your Software: Automatically Generating Software Use and Reuse Libraries and Catalogs from Standardized SAS® Code
Bruce Gilsen Tales from the Help Desk 7: Solutions to Common SAS® Tasks
Kirk Paul Lafler Downloading, Configuring, and Using the Free SAS® University Edition Software
Priscilla Gathoni How To Win Friends and Influence People A Programmers Perspective in Effective Human Relationships
Doug Haigh Divide and ConquerWriting Parallel SAS® Code to Speed Up Your SAS Program



Co-Chairs:   Barbara Okerson
                    Shane Rosanbalm

The Reporting and Information Visualization/JMP section contains presentations that demonstrate visualizing and presenting data in unique and innovative ways.  Visual representation and interactive techniques allow users to intuitively explore, discover and comprehend large amounts of information.

Topics include but are not limited to:

  • SAS Styles, Templates, Output Delivery System (ODS) and Graphics Template Language (GTL)
  • Customized reports, dashboards, scorecards, graphs, maps
  • SAS Visual Analytics
  • JMP applications
JMP® provides users with the ability to explore hidden stories and trends in data while easily converting this information into visual displays.  We would like to hear about innovative uses of JMP software, especially scenarios where integration between JMP and SAS has made a major impact.

Papers submitted should include a display of the system or results and should include some programming code where applicable.

Author(s) Title
Amber Carlson, Amelia Stein and Xiaobin Zhou Proc Report, the Graph Template Language, and ODS Layouts: Used in Unison to Create Dynamic, Customer-Ready PowerPoints
Tim Beese Building Interactive Microsoft Excel Worksheets with SAS® Office Analytics
Ryan Kumpfmiller Make the jump from Business User to Data Analyst in SAS® Visual Analytics
Ryan Kumpfmiller and Craig Willis Success Takes Balance, Don't Fall Over With Your SAS® Visual Analytics Implementation
Dan Heath Annotating the ODS Graphics Way!
Barbara Okerson Mapping Roanoke Island: from 1585 to present
Charlotte Baker Creating a Publication Quality Graphic with SAS®
Harry Droogendyk SAS® Formats: Effective and Efficient
Fred Edora A Real World Example: Using the SAS® ODS Report Writing Interface to revamp South Carolina's School District Special Education Data Profiles
Carlos Piemonti and Geoffrey Wical UCF Stored Process Conversion for Current STEM Retention Reports
Mira Shapiro CMISS® the SAS® Function You May Have Been MISSING
Sivakumar Jaganathan, Thanuja Sakruti and Abhishek Uppalapati Time-to-Degree Issue Solution using Academic Analytics
Ilya Krivelevich, Andrea Dobrindt, Simon Lin and Xiaomin He Enhanced Swimmer Plots: Tell More Sophisticated Graphic Stories in Oncology Studies
Huei-Ling Chen and Jialin Xu Utilize SAS® 9 SGPLOT to Create Genome Wide Association Studies Plots
Melvin Alexander Exploring JMP®'s Image Visualization Tools in Medical Diagnostic Applications
Adetosoye Oladokun and Rahel Dawit Diabetes Self-Management Education Services in Florida
Jason Brinkley Using JMP to Apply Decision Trees and Random Forests as Screening Tools for Limiting Candidate Predictors in Regression Models
Tricia Aanderud 5 Secrets for Building Fierce Dashboards
Venu Perla Data Visualization Through 3-D Graphs Using SAS® Graph Template Language (GTL)
Jaime Thompson Color Speaks Louder than Words
Mike Jadoo Geospatial Analysis with SAS®


Statistics/Data Analysis

Co-Chairs:   Meenal Sinha
                    Brandon Welch

Presentations in the Statistics and Data Analysis section address the transformation of raw data into useful information.  This section will include topics that will interest a wide range of SAS® users, including statistical analysts, statistical programmers, statisticians, and DATA step programmers.  Papers do not need to present new statistical methods, although such topics are always welcome.  Innovative applications of established methods to new or unusual scenarios are also appropriate for this section.  In addition, presentations are sought that involve the application of methods that many users of SAS statistics may not commonly see, such as methods for categorical, longitudinal or censored data.  Methods to facilitate analysis of very large data arrays, such as those that result from genetic studies or national surveys, are also sought for this section.  It is important to keep in mind that the audience will represent a broad spectrum of users of statistical methods, so the presentations can range from basic applications to complex analyses.

Author(s) Title
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®
Tyler Hicks and Jeffrey Kromrey Mixture Priors 101: Using SAS® to Obtain Powerful Frequentist Inferences with Bayesian Methods
Seth Hoffman Finding the Area of a Polygon... On a Sphere!
Bill Bentley Factors of Multiple Fatalities in Car Crashes
Tyler Hicks and Jeffrey Kromrey In the Pursuit of Balanced Groups: A SAS® Macro for an Adaptive Randomization Test with continuous covariates
Tho Nguyen and Bob Matsey Empowering Self-Service Capabilities with Agile Analytics
Bruce Gilsen Identifying Gaps in Time Series Data
Taylor Lewis and Stanislas Ezoua A Simple SAS® Macro to Perform Blinder-Oaxaca Decomposition
Peter Flom PROC LOGISTIC: Traps for the unwary
Anh Kellermann, DeAnn Trevathan and Jeffrey Kromrey Missing Data and Complex Sample Surveys Using SAS®: The Impact of Listwise Deletion vs. Multiple Imputation on Point and Interval Estimates when Data are MCAR and MAR
Anh Kellermann and Jeffrey Kromrey The HPSUMMARY® Procedure: A Younger (and Brawnier) Cousin to an Old SAS® Friend
Dennis Beal A Macro for Calculating Kendalls Tau-b Correlation on Left Censored Environmental Data
Youyou Zheng, Sivakumar Jaganathan, Thanuja Sakruti and Abhishek Uppalapati A Data Mining Approach to Predict Student-at-risk
Venita DePuy Surviving the Interim: Insights Into Interim Survival Analyses
Pushpal Mukhopadhyay Designing and Analyzing Surveys with SAS/STAT® Software
Antarlina Sen and Gaurang Margaj A prediction model for which country will win the highest number of Golds in 2016 Olympics
Niloofar Ramezani and Ali Ramezani Analyzing non-normal data with categorical response variables
Robert Rodriguez Statistical Model Building for Large, Complex Data: Five New Directions in SAS/STAT® Software


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