The Applications Development section recognizes the role of SAS® software as a basis for the development of strategic applications and provides overviews of the application's code and the techniques used in its development. Presentations in this section deal with both the process and productivity tools used in the design, development, implementation and integration of enterprise solutions running in single or multi-platform environments. Presentations may include Web-enabled applications, object-oriented applications, modular applications or applications that integrate SAS software with other software products.

Coders' Corner (CC)

10-minute tutorials (1-2 pages) and 'how-to' talks on tips and techniques while using the SAS system. These brief tutorials on helpful hints in SAS can be the priceless gem you have been looking for to solve that pesky problem back at the office.

Data Management (DM)

Papers that tell how to deal with that pile of data. Topics will run the gamut of: collection and input, structure, validation, maintaining integrity, archiving, conversion between forms, warehousing and tracking of data.

Data Presentation (DP)

Papers for this section involve discussions of a variety of SAS tools and techniques for visually displaying your data, whether it’s graphical output or a customized report. Topics in this section are geared toward conveying meaningful data in a visually effective manner, which clearly and concisely communicates information to the intended audience using tools such as SAS/GRAPH®, SAS/INSIGHT, the TABULATE and REPORT procedures, and the Output Delivery System (ODS).

Hands On Workshops (HW)

Features SAS software experts to give workshop-style tutorials and provide the opportunity for attendees to practice using SAS software. These workshops are presented by well-known SAS experts and have been chosen based upon their knowledge and experience at conducting hands on type workshops/courses.

Intro to SAS (IN)

This is a one-day section designed to sequentially guide new SAS users through the basics of SAS programming. Presentations introduce the basic concepts of using DATA and PROC steps. All presentations are given by experienced users with expertise in the specific area being presented.

Posters (PS)

The Posters section is about any and all uses of SAS software. It is different from other sections in that the medium for presentation is a visual display rather than a formal lecture. The Posters section is presentations that include graphics or source code or that can best be summarized in a few main points. Posters are on display throughout the conference with a presentation period for authors to discuss their works on a one-to-one basis with conference attendees.

Serendipity (SE)

Papers that do not fit well into the other categories, but are interesting and informative nonetheless. Presentations will encompass a variety of subjects and promise to entertain and enlighten. Remember that feeling of discovering something that will solve that SAS problem? Webster's Dictionary calls it Serendipity!

Statistics and Data Analysis (SD)

Presentations in Statistics and Data Analysis cover statistical and data analysis techniques, including statistical procedures, methodologies and techniques for efficient data manipulation and preparation using the SAS System. Papers from many different industries are represented in this section and are geared toward a variety of audiences with a wide array of experience using the SAS System, from the beginner to the more advanced. Traditional DATA step programmers, statistical programmers, and statisticians, as well as others, will find topics of interest here.

Tutorials (TU)

In-depth explanations of a wide range of topics within the SAS System. Papers are designed to provide users at all levels of expertise with specific "how-to" tools presented in a step-by-step approach. Papers focus on one procedure or functional area or provide an initiation to some aspect of the SAS System. From the tutorial, attendees will gain a fundamental understanding of the topic and be able to immediately apply what they have learned to their jobs.

Pre-Conference Weekend Workshops (WW)

These are professional-level seminars on SAS subjects, presented in cooperation with SESUG ‘04. We sponsor a limited number of half- and full-day workshops before the actual conference at the same site. Please see pages 19-23 for complete details.

An Introduction to SAS/SHARE, By Example
Larry Altmayer, US Bureau of the Census

Software Testing Fundamentals-Concepts, Roles, and Terminology
John Bentley, Wachovia Bank

Creating Meaningful Data From Web Logs Using Base SAS
Jenine Eason, AutoTrader.com

Journeyman's Tools: Two Macros to Show Parameters and Calling Sequence of Routines
Ron Fehd, Centers for Disease Control

Building Web Applications Using SAS/IntrNet® Application Dispatcher
Steve James, Centers for Disease Control

A Quick and Dirty Query System Using HTML, PROC SQL, and SAS/IntrNet
Kevin McGowan, Constella Group, Inc.

Building A SAS Application to Manage SAS Code
Phillip Michaels, Independent Consultant

Generate a Metadata for Analysis
Maria-Alexandra Paladines, School District of Palm Beach County

Macros: Tips, Techniques, And Examples
Andrew M. Traldi, Cingular Wireless

Exceptional Exception Reports
Gary McQuown, Data and Analytic Solutions, Inc

Building a Drill-Down Application Using HTML and ODS
Deborah Skinner, Assurant

Using SAS at SAS: The Mining of SAS Technical Support
Annette M. Sanders & Craig D. DeVault, SAS

Tips of Installing SAS/IntrNet on Linux
Xiao Zhuang, University of North Carolina at Chapel Hill

Merging: Avoid the Cones
Jessica Bonow, Arkansas Foundation for Medical Care

Transferring Your Mainframe SAS Programs to Your PC in Three Easy Steps
Michael A. Raithel, Westat

Tools to Transfer Data Between SAS and Stata
Dan Blanchette, Carolina Population Center UNC-CH

Little Known Feature of SAS/Graph and ODS for Visualization of Longitudinal data
Kevin Delaney, Centers for Disease Control

SAS Dating Tips: A Beginner's Guide to Using SAS Dates
Erik Larsen, Independent Consultant

%WINDOW: SAS Diamond In the Rough
Alan Mann, Independent Consultant

Double Your Pleasure, Double Your Words
David Cassell, Design Pathways

Programmatic Handling of Varying Report Requirements
Jim Snider, AmSouth Bank

Data Set Options – What comes first?
Jim Snider, AmSouth Bank

Tip: How to use a 'quoted' SAS macro variable to select observations.
Gary W. Moore, Arkansas Foundation for Medical Care

Faster Flat File Sampling
John E. Bentley, Wachovia Bank

Using Acting Techniques to Create a Successful Presentation
Lois Levin, Independent Consultant

Your Program Header: What everyone who wants to reuse your program wants to know about it, so they won't be paid to reinvent the wheel.
Ron Fehd, Centers for Disease Control

Using Different Methods for Accessing Non-SAS Data to Build and Incrementally Load that Data Warehouse
Ben Cochran, The Bedford Group

Methods of Storing SAS Data into ORACLE Tables
Lois Levin, Independent Consultant

Using PROC COMPARE in a SAS/AF Application for Tracking Corrections Made to SAS Datasets for a Clinical Trial
Emily A. Mixon & Karen B. Fowler, University of Alabama

Building Efficient State Transition Diagrams from Transactional Feeds
Brette Peppe, Independent Consultant

Finding Needles in the Documentation Haystack
Susan Myers & David Smarrella, Research Triangle Institute

Sounding the Trumpets: Effective Failure Notification
Don Hopkins, Ursa Logic Corp.

Using SAS to Facilitate Data Comparisons
Elizabeth Heath & M. Rita Thissen, Research Triangle Institute

Text Mining and Medical Information
Chakib Battioui, University of Louisville

No Fuss Hashing: Data Step's Built-in Hash Object
Jason Secosky, SAS Institute

To MDDB or Not MDDB - That is the Question
Jeff Lessenberry, Jeff Lessenberry Consulting

Quality of Life Analysis for Patients Receiving Heart Implants
Christiana Petrou & David Nfodjo, University of Louisville

Using Dynamic Data Exchange to Customize Formatted Reports in Microsoft* Excel
Dennis Beal, Science Applications International Corporation

Text Mining and Medical Information
Chakib Battioui, University of Louisville

Statistical Analysis of Gene Expression Micro Arrays
John Schwarz, University of Louisville

A SAS Macro for Construction of Symbol Statements
Dr. James Blum, University of North Carolina at Wilmington

Automated Data Collection using SAS and FTP
Phil Busby

Building a Web Based EIS for Data Analysis
Ed Confer, KJC Programming

Next Step in Data Visualization: ODS Graphics Template Language
Jeff Cartier, SAS

ODS, Proc GMAP and SAS/Intrnet: MAP Your Own Response Data on the Web
Lakshmi Pandey , Georgia State University

Making the Most of Version 9 Features
Marje Fecht, Prowerk Consulting

Introduction to SQL
Steven First, Systems Seminars Consultants, Inc.

An Introduction to Macros
Deb Cassidy, Cardinal Health

Creating and Exploiting SAS Indexes
Mike Raithel, Westat

Version 9 ODS (Output Delivery System) - Basics
Dana Rafiee, Destiny

Moving Data and Analytical Results Between SAS and Microsoft Office
Vincent DelGobbo, SAS

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

Why the DATA Step Does What It Does
Neil Howard, i3 Statprobe

A Roadmap to SAS Documentation
Sean Gargan, SAS

What's That Note/Warning/Error Mean and How Do I Fix It?
Deb Cassidy, Cardinal Health

How to Incorporate Old SAS® Data into a New DATA Step, or "What is S-M-U?"
Andrew T. Kuligowski, Nielsen Media Research

(In)Formats (In)Decently Exposed
Harry Droogendyk, Stratia Consulting

When Bad Programs Happen to Good People: Shuffling, Shifting, and Structuring an Inherited SAS Program
Gary Schlegelmilch, US Bureau of Census

Here's the Data, Here's the Report I Want - How Do I Get There?
Debbie Buck, D. B. & P. Associates

The Utter Simplicity and Power of the TABULATE Procedure
Dan Bruns, Tennessee Valley Authority

ODS: What is it, Why would you use it, What can you do with it?
SAS Institute, SAS

Doing More with SAS/GRAPH GMAP: A New Look at an Old Procedure
Barbara B. Okerson, Ph. D., Virginia Health Quality Center

Matching SAS Data Sets: If at First You Don't Succeed, Match, Match Again
Imelda C. Go, South Carolina Department of Education

Installing SAS/IntrNet on Windows and Linux
Ms. Xiao Zhuang and Sharon Schiro, The University of North Carolina at Chapel Hill

SAS-L: The Basics
F. Joseph Kelley, University of Georgia

The Evolution of a SAS/Graph Application
Jenine Eason, Autotrader.com

SAS Programs to Select Controls for Matched Case-Control Studies
Robert Matthews and Ilene Brill, University of Alabama at Birmingham

Methods for Minimizing Errors in Address Data
Milorad Stojanovic, Research Triangle Institute

Where's the Match?
Jennifer Waller, Medical College of Georgia

Array: Construction and Usage of Arrays of Macro Variables
Rohn Fehd, Centers for Disease Control

Avoiding Mouse Elbow
Malachy Foley, University of North Carolina at Chapel Hill

Cutting the SAS® LOG Down to Size
Malachy Foley, University of North Carolina at Chapel Hill

Panel Discussion: Launching a Web Application
Mark Tabladillo, Moderator, markTab Consulting

Fresh SAS Programming Tunes from Hashville
Paul Dorfman, Independent Consultant

Stata for the Struggling SAS Mind
Dan Blanchette, Carolina Population Center

44 Tricks with the 4mat Procedure
Ben Cochran, The Bedford Group

SAS Add-In for MicroSoft Office
Jennifer Clegg, SAS

The Perks of PRX…
David L. Cassell, Design Pathways

SAS Application for Human Health Risk Assessment for Hazardous Waste Combustion Facilities
Samuel Stinnette, Science Applications International Corporation

Bring the Data Warehouse to the Office with SAS Integration Technologies
Peter Eberhardt, Fernwood Consulting Group Inc.

A Different Approach to Learning SAS Software
Mirjana Stojanovic, Independent Consultant

Getting to Generalized: A Utility Development Primer
Frank DiIorio, CodeCrafters, Inc.

Spatial Statistics Using the SAS Bridge for ESRI
Patricia Cerrito, University of Louisville

Binary Logistic Regression Model Optimization
Jerome Musial, Cingular Wireless

A System to Calculate Value-at-Risk Using SAS/IML and Oracle
George Rezek, GMAC - Enterprise Risk Management

Building and Analyzing Probabilistic Sampling Designs Using SAS
David L. Cassell, Design Pathways

Crossover Designs and PROC MIXED
Hossein Yarandi, North Carolina State University

Case Studies in Time Series
David Dickey, North Carolina State University

A Simulations Study to Evaluate ANOVA and GEE for Comparing Correlated Proportions with Missing Values
Mark S. Litaker, Medical College of Georgia

Electronic Medical Records
Particia B. Cerrito, University of Louisville

Mixed Models Analysis of Microarray Experiments Using Pooled Error Estimates
Dr. James E. Blum, University of North Carolina at Wilmington

Structural Equation Modeling Assessing Mircoarray Data
Mussie Tesfamicael, University of Louisville

Taking it Home and Putting it into Practice
Diane Cunningham, Southern Company Services

Mixed Model Influence Diagnostics
Oliver Schabenberger, SAS

8 Characteristics of a Successful Data Warehouse
Martin Brown, Lucid Analytics Corp.

A Gentle Introduction to SAS Graph
Ben Cochran, The Bedford Group

Picture Perfect: In depth look at the picture format
Carry Croghan, US Environmental Protectoin Agency

An Overview of Non-parametric Tests in SAS: When, Where, Why, and How
Paul Pappas & Venita DePuy, Duke Clinical Research Institute

Time Series with Input Variables
Dave Dickey, North Carolina State University

Dictionary Tables and Views: Essential Tools for Serious Applications
Frank DiIorio, CodeCrafters, Inc.