CONFERENCE OVERVIEW
 

 

Pre/Post Conference Classes

Helen Carey
Helen Carey
Helen Carey is an independent computing and training consultant. She previously worked for the University of Hawaii ITS department and in the insurance industry using SAS and SQL for analysis. She is an experienced programmer using a variety of features and products of the SAS Sytem. Helen has given invited and contributed papers at WUSS and SUGI conferences and local users groups. She has served as Section Chair at many SUGI conferences and at WUSS. Along with her sister, Helen co-authored the book SAS Today! A Year o Terffic Tips. She agrees with the quote by Michelangelo who at the age of 87 said "I am still learning."
SAS Essentials Workshop
Programming Basics I
Getting Your Data in and Understanding the Data Step
SAS data sets are used in the SAS analysis and reporting procedures. There are various ways to get your data into a SAS data set. In this presentation, we will concentrate on the DATA step and the Import/Export Wizard.The DATA step is one of the building blocks of SAS programming. Understanding the basic structure and components of the DATA step is fundamental in learning to create your own SAS data sets. You will learn how the DATA step works, which includes understanding the input buffer and program data vector, the structure of the SAS data set and what happens at program compile time and execution time. By understanding DATA step processing, you can debug your programs and interpret your results with confidence.
SAS Programming Basics II
Manipulating and Checking Your Data

Often data need to be manipulated and/or transformed to meet the needs of our analysis or as a means of exploring and checking the data. This session will focus on using the data manipulation and transformation features of the DATA step. The DATA step will be used to combine values of variables into several categories by recoding variables, to group variables using formats, to handle missing values, to select particular observations for analysis, to create new variables out of old variables by performing calculations and using built-in functions and to check the data. also multiple data sets will be combined using the SET and MERGE statements in the DATA step.

Once our data is in shape, the next step is to produce results from our data.

SAS Programming Basics III
Producing Results from your Data

This session explores how to choose the most appropriate tool for turning your data into results and tailoring the output to the needs of your intended audience.

SAS procedures are designed for easy reporting and analysis of SAS data. This session will look at some of the basic reporting procedures, such as PRINT, MEANS, UNIVARIATE and FREQ. The procedures SQL, REPORT and TABULATE will be used to produce summary reports. PROC FORMAT will be used with the reporting procedures to customize the appearance of data values and to group observations and values. Using the Output Delivery System (ODS) to change the destination and look of your reports, along with ODS Graphics to produce graphs will e explored.

Art Carpenter
Carpenter
Art Carpenter’s publications list includes five books, and numerous papers and posters presented at SAS Global Forum, SUGI, and other user group conferences. Art has been using SAS® since 1977 and has served in various leadership positions in local, regional, national, and international user groups. He is a SAS Certified Advanced ProgrammerTM and through California Occidental Consultants he teaches SAS courses and provides contract SAS programming support nationwide.
Advanced Reporting and Analysis Techniques: It's Not Just About The PROCs!
There are literally hundreds of techniques used on a daily basis by the users of SAS® software as they perform analyses and generate reports.  Although often obscure, most of these techniques are relatively easy to learn and generally do not require specialized training before they can be implemented.  Unfortunately a majority of these techniques are used by only a very small minority of the analysts and programmers.  They are not used more frequently, because a majority of SAS users have simply not been exposed to them.  Left to ourselves it is often very difficult to ‘discover’ the intricacies of these techniques and then to sift through them for the nuggets that have immediate value.

This one day course presents a series of those nuggets.  It covers a broad range of SAS topics that have proven to be useful to the intermediate and advanced SAS programmer who is involved with the analysis and reporting of data.  The intended audience is expected to have a firm grounding in Base SAS.  For most of the covered topics, the course will introduce useful techniques and options, but will not ‘teach the procedure’.  No matter how experienced we are, no matter how well we know a procedure or a technique, there is still more that we do not yet know.

The course includes options and techniques associated with:
New, powerful, and little used options in MEANS/SUMMARY
Reporting procedures including TABLULATE and REPORT
Understanding more about the REPORT compute block
 In the DATA step (functions, options, statements)
 Working with data
 Taking full advantage of formats
Interfacing with the Macro Language
Output Delivery System, ODS, extras
Operating System Interfaces and how you can take advantage of them
 Advanced Table look-up techniques
 Importing and exporting data
 . . . . much, much more
Students attending this seminar will be exposed to a broad range of techniques, procedures, options, and statements.  Throughout the seminar the discussion will include comparisons of coding and operating efficiencies.  Even the most advanced students will come away from the training with a broader appreciation for the SAS System, its depth and its flexibility, and the programmer’s ability to tap into those capabilities.
Building Dynamic Programs and Applications Using the SAS® Macro Language
This seminar shows you how to take advantage of SAS Macro Language capabilities that enable you to write dynamic programs and applications. By mastering the concepts and techniques presented in this class your programs will become free of hard-coded data dependencies, thus eliminating the need to re-write the code every time a data set name, variable name, or other data attribute, changes. Let “them” change the project's specifications as often as “they” want…your code is ready! The dynamic programming techniques that you will learn about during this seminar:

Are flexible and are easily adaptable to changing data structures, data table names, and variable (field) attributes
Reduce maintenance requirements by removing data dependencies from within the programs
Provide significant resource savings during program/application development cycles
Gives the end-user extensive control over program execution by using tables such as SAS data dictionaries, SAS data sets, and Excel tables
Reduce program validation efforts by providing reusable and generalized code that can be applied to many different applications
Establish controlled data environments, thus insuring data integrity throughout your organization

This course makes extensive use of example macros that have been gathered from real world applications, and it concentrates on the techniques necessary to make effective use of these tools.
Ben Cochran
Ben Cochran

After more than 11 years with SAS Institute in the Professional Services (as an Instructor) and Marketing Departments (as Marketing Manager for the SAS/EIS product), Ben Cochran left to start his own consulting and SAS Training business in the fall of 1996 – The Bedford Group. As an affiliate member of SAS Institute’s Alliance Partner Program, Ben has been involved in many consulting projects over the last 16 years and has been teaching SAS courses since 1985. Ben has authored and presented dozens of papers at SUGI/SGF and regional user groups on a variety of topics since 1988... and now finally at WUSS.

Getting Started with the Business Intelligence Tools from SAS

Overview:
This one day workshop explores the area Business Intelligence Tools that are offered by SAS Institute.
This course starts with a simple dataset and walks the student through all the necessary steps to get reports
and other output posted on the web. This course has been updated for the 4.3 / 9.3 release of SAS.

Audience:
Intermediate users of SAS software who want to gain a deeper understanding of these tools that SAS first shipped with the SAS9 release of the software.

Prerequisites:
This seminar is most appropriate for students with at least six months worth of experience using the SAS System, or who have completed a fundamentals course in SAS programming.

Seminar Topics

• Using SAS Management Console to Register Metadata.
• Using SAS OLAP Cube Studio to Build Cubes.
• Using SAS Information Map Studio to Build Information Maps
• Using SAS Web Report Studio to Build Web Reports
• Using SAS Information Delivery Portal to Display Reports
• SAS Add-in for Microsoft Office – (Optional)
• Building Dashboards with the BI Dashboard Toolset. (Optional)
Manipulating Data with SAS Functions and Arrays
Overview: 
This one day workshop explores the area of data manipulation and shows you how to accomplish this through using arrays and the myriad of functions provided by the SAS® System.  This course includes some of the SAS9 functions 

Audience:
Beginning to intermediate users of SAS software who want to gain a deeper understanding of the art of transforming and manipulating data.  This course focuses on the DATA step and goes into a great deal of detail on it’s inner workings.

Prerequisites:
This seminar is most appropriate for students with at least six months worth of  experience using the SAS System, or who have completed a fundamentals course in SAS programming.

Seminar Topics

Introduction to Data Manipulation
• The Structure of SAS Data Sets
• Processing Data with the SAS System.

SAS Functions
• Introduction to Functions
• Manipulating Numeric Data
• Manipulating Character Data
• Data Conversion
• Other Very Useful Functions

DO Loops
• A Quick Introduction to Iterative Processing
Arrays
• Introduction to Arrays
• Array Applications
• Special Array Functions
Cindy Cragin
Cindy Cragin

Cindy Cragin is a senior instructor who has been teaching classes for SAS for close to 14 years. She teaches the SAS programming classes including PRG1, PRG2, and SQL. Cindy also teaches all of the SAS Enterprise Guide classes. She has extensive knowledge in SAS Data Integration Studio and has passed the SAS Certification exams for DI as well as the BASE Programming Exams. Cindy is a well-respected instructor who consistently receives outstanding evaluations from her students. During her tenure at SAS Cindy has also been a software,
pre-sales systems engineer at SAS for 8 years. Cindy is a native from the Chicago land area but has resided in Southern California since 1980.

Becoming a Better Programmer with SAS Enterprise Guide® 4.3
Both existing and new users of SAS are turning to SAS Enterprise Guide to write and run their code. Long-time users are accustomed to typing all their code into the Program Editor window and simply hitting the Submit Key. New users do not have this same set of expectations and are more willing to point and click on occasion. But the truth is becoming clear; the winning programmer will be the one who has the expertise to create the best of both worlds--either coding or clicking, depending upon which is more efficient for a given task. SAS Enterprise Guide 4.3 contains new functionality that can help anyone become a better programmer. These pages address the all-important question: when is it appropriate to code, and when to click? The aim here is to expose new users --as well as those familiar with SAS -- to tips and best practices that will allow them to return to the office as better programmers.
Peter Eberhardt
Peter Eberhardt

Peter Eberhardt is SAS Certified Professional V8, SAS Certified Professional V6, and SAS Certified Professional Data Management V6. In addition his company, Fernwood Consulting Group Inc. is a SAS Alliance Partner. Peter is a regular speaker at SAS Global Forum, SESUG and NESUG as well as at local user groups in Canada, the US and the Caribbean.
Excel VBA: When You Have to Step outside SAS
As SAS programmers and analysts, we are comfortable and at home in an environment where we have programs and commands that automate our processing. The data change - we simply rerun our code to produce consistent results.
However, when we have to work with data in Excel, whether cleaning up worksheets so they can be imported by SAS, or dressing up worksheets for management review. Many SAS programmers are operating in a manual, nonreplicable environment. The data change - we have to repeat all of the manual steps again. Needless to say, this is not only time-consuming, but also error-prone.

In this workshop you will learn how to use the programming language and environment that comes with Excel: Visual Basic for Applications (VBA). VBA is essentially a specialized subset of the Microsoft Visual Basic (VB) programming language. We will start with a comparison of the two programming environments: the SAS (or SAS® Enterprise Guide®) programming window and VBA code modules with an initial focus on the editor. From there, we will look at some of the differences in common programming constructs, such as DO loops and IF statements. Once we have looked at some of the fundamentals of the VBA language, we will start to look at how a program accesses the worksheet with a focus on a few main concepts:
• Locating cells.
• Moving through rows and columns.
• Identifying cell content.
• Acting on cell content.
• Adding or removing rows and columns.
After we understand some of the basics of accessing the data in the Excel spreadsheet, we will then see how to build and execute Excel functions to tie it all together. The workshop will wrap up with examples showing how to take formatted Excel reports and convert them into worksheets that can be easily read by SAS, followed by examples of taking SAS tabular output and creating formatted Excel reports.
The workshop will use Excel 2010 VBA for the examples, but all of the content will be applicable to earlier versions of Excel.
Sunil Gupta
Gupta

Sunil is a best selling SAS author and global corporate trainer. Sunil is Principal Consultant at Gupta Programming since 1994. Most recently, Sunil launched his new SAS resource blog, www.SASSavvy.com, for smarter SAS searches and has released five new SAS e-Guides on Quick Results with PROC SQL, Quick Results with PROC REPORT, A to Z Analysis and Validation using PROC TABULATE, Compare and Conquer SAS Programming Techniques and Automating Tasks using SAS Macro Programming. He has been using SAS® software for over 20 years and is a SAS Base Certified Professional. He is also the author of Quick Results with the Output Delivery System, and Sharpening Your SAS Skills.

Automating Tasks using SAS Macro Programming
Ready to get the most out of SAS macros with a simple and logical approach to SAS macro programming? This unique course shows how the macro language serves as a dynamic character editor for SAS programs. Course examples show how macros can be used to standardize, automate, communicate, customize and create SAS code. From simple to complex real-word examples, we will break down the macro language into easily digestible chunks. Using macros saves time with data-driven processing and dynamic code generation. Attend with your challenging macro questions. References are made to my top 25 ‘must read’ SAS papers.
Gerry Hobbs
Hobbs
Gerry Hobbs is on the faculty in the Department of Statistics at West Virginia University as well as an Adjunct Associate Professor of Community Medicine within the WVU School of Medicine. He consults widely and frequently with students, faculty and, staff at the School of Medicine and has well over 150 publications relating to medical investigations in many different areas as well as publications in other disciplines. He has extensive experience with both observational data and with experimental investigations. He is a co-principal investigator, co-investigator and, consultant on several funded scientific and clinical research projects. Dr. Hobbs received both his MS and Ph.D. degrees at Kansas State University and teaches both Statistics and Biostatistics courses. Dr. Hobbs has served as a consultant to the SAS Institute for over twenty-five years. In that capacity he has taught numerous different SAS and JMP training courses that include courses that emphasize data management and those which are purely statistical in content. He has also authored and co-authored training materials that have been used by the statistics group, housed in the SAS Education Division. For over twenty years he has served on the Executive Board of the organization (SGUG) that puts on the annual SAS User's Group Conference and he served as Conference Co-Chair in 1988 when the conference was held in Orlando, Florida.
Methods of Survival Analysis in SAS
Survival analysis and its functional equivalent, reliability analysis, are widely used in many fields of work. Most notably, the methods have been widely used in medical research and quality assurance for manufacturing for a long time. More recently they have been applied to software engineering and warranty coverage. The fundamental idea stems from an interest in knowing how long an entity will continue to perform. Of course parts and systems eventually fail, but so do people. In a medical sense we failure may mean death but it may also mean progression to the next stage of disease or a relapse. There are a couple things that make these methods different than standard analyses. The first is that the data usually has an elongated tail – usually the right tail. The second is that some observations are censored or incomplete, e.g., the part has lasted for seven months and we don’t have time to wait for it to fail. The simple descriptive “statistic” in this area relates time (to event) to probabilities of the event in the form of a function that is most often estimated by a nonparametric device known as the Kaplan-Meier curve. Going beyond that, inferential methods are used to compare groups. Wilcoxon and Log-Rank tests are popular in that area. Several methods are available that allow us to study the effect of a factor, either categorical or continuous, while we control for one or more confounders, also categorical or continuous. In this presentation we will explore the ways in which SAS Software® empowers the user to perform these analyses.
Kirk Paul Lafler
Lafler

Kirk Paul Lafler is consultant and founder of Software Intelligence Corporation and has been programming in SAS since 1979. He is a SAS Certified Professional, SAS Institute Alliance Member (1996 – 2002), and provider of IT consulting services and training to SAS users around the world. As an author of four books including PROC SQL: Beyond the Basics Using SAS (SAS Institute. 2004), he has written more than five hundred papers and articles, been an Invited speaker at more than three hundred SAS International, regional, local, and special-interest user group conferences/meetings, and is the recipient of 19 “Best” contributed paper, HOW, and poster awards.
Output Delivery System (ODS): The Basics and Beyond
This course explores the various techniques associated with output formatting and delivery using the Output Delivery System (ODS). Numerous examples will be presented to command mastery of ODS capabilities while providing a better understanding of ODS statements and options to deliver output anyway that is needed. Topics include SAS-supplied Formatting statements and options; Formatting Output as RTF, PDF, MS-Excel®, and HTML; Selecting output objects with Selection or Exclusion Lists; using the Escape character to enhance output formats; exploring ODS statements and options; constructing drill-down applications with the DATA step, ODS, and SAS/GRAPH software; creating thumbnail charts; techniques on creating user-defined ODS styles; and an introduction to the customization of output with the TEMPLATE Procedure.
PROC SQL Programming: The Basics and Beyond
This course teaches SAS users core concepts and features about accessing data stored in relational database tables. Attendees learn how to use PROC SQL to access data stored in relational tables; accomplish tasks including retrieving, subsetting, ordering, and grouping data; construct tables and “virtual” tables known as views; define, access and manipulate data; produce “quality” looking output with PROC SQL options and Output Delivery System (ODS); use summary (statistical) functions to aggregate data; understand the difference between DATA step merges and joins; create complex queries using inner and outer joins; construct logic scenarios with case expressions; interface PROC SQL with the macro facility; understand index rules and strategies; and apply query performance techniques.
Taylor Lewis
Taylor Lewis

Taylor Lewis is a mathematical statistician for the U.S. Office of Personnel Management and a PhD student at the Joint Program in Survey Methodology at the University of Maryland, College Park. His primary research interests include missing data problems, analysis of complex survey data, and applications of responsive survey design. An avid SAS user for 10 years, he holds the SAS Certified Advanced programmer credential and has presented numerous papers and workshops at SAS conferences pertaining to various statistical topics.
Analyzing Complex Survey Data in SAS

This course introduces the statistical and syntactical modifications necessary when analyzing complex survey data. “Complex” implies data containing one or more of the following features: stratification, clustering, unequal respondent weights, or finite population correction factors. Each of these features is presented, in turn, with illustrative examples demonstrating why in practice it is necessary or even beneficial to deviate from the more familiar simple random sample design.

Attendees will gain an understanding of when and how to employ the SURVEY family of SAS procedures (for instance, using PROC SURVEYMEANS as opposed to PROC MEANS or PROC SURVEYREG in lieu of PROC REG). Nuances of analyzing survey data are highlighted using real, publicly-available survey data sets spanning multiple disciplines. For example, a thorough discussion of replication techniques and how replicate weights can be used to approximate survey estimate variability is included. Issues of domain estimation are explored, applicable to when one restricts analysis to a subset of the data. Also, idiosyncrasies introduced by fitting linear models to survey data are noted.
Techniques to Compensate for Missing Data

Missing data present a dilemma to applied researchers, especially those analyzing data from surveys. Although a common approach is case- or list-wise deletion, in which the missing data are essentially ignored, alternatives are available and may be preferable in many circumstances. Two classes of compensation techniques are explored in detail: 1) reweighting the observed data and 2) imputing, or filling in, the missing data. The course is a blend of theory and real-life examples, with a focus on the SAS syntax necessary to apply the methods in practice. Specific topics to be discussed include the following:

• adjustment cell reweighting
• propensity score reweighting
• poststratification
• raking
• cell-based (hot-deck) imputation
• model-based imputation
• single vs. multiple imputation
Sanjay Matange
Matange

Sanjay Matange is a Software Development Manager in the Data Visualization R&D area. His team is responsible for development and support of ODS Graphics, including Graph Template Language (GTL), SG Procedures, ODS Graphics Editor and ODS Graphics Designer.

Sanjay's group also develops and supports the Silk Components framework that is used in various analytical products and solutions such as Enterprise Miner and Marketing Automation.

Clinical Graphs Using SAS 9.2
Do you wish you could create modern clinical graphs using SAS? Have you heard that it is difficult to create such graphs using SAS? If the answer is yes to any of these questions, this course is for you. This half-day course will cover, in detail, how to create the graphs used in Health and Life Sciences industry, including graphs commonly used for analysis of safety data for clinical trials. In this course, we will build many such graphs from scratch using the most appropriate graph tools from the ODS graphics tool set, including SG Procedures and GTL.

Course outline:
• Brief review of ODS Graphics, SG Procedures and GTL.
• Create the following graphs using ODS graphics:
o Distribution of ASAT by Time and Treatment
o Distribution of LFT Values by Treatment
o Matrix Display of Maximum LFT Values
o LFT Patient Profile
o Hazard Function of Adverse Event
o Adverse Events Timeline
o Medications over time
o Lab results panels over time
o Symptoms over Time by Severity
o Top Twenty Adverse Events by Treatment
o Liver Function Test Panel
o LFT by Trial Day for At Risk Patients
o Survival distribution by Time and Illness
o Growth v/s BMI Chart
o And more
David Pasta
Pasta

Currently Vice President of Statistical & Strategic Analysis at ICON Late Phase & Outcomes Research, David pasta has been using SAS since 1977 for a wide array of statistical analysis and data management tasks. He has frequently presented contributed and invited papers at SGF and WUSS.
Practicalities of Building and Testing Models with Continuous and/or Categorical Predictors
Analysts trying to understand the contribution of predictor variables are faced with many choices. Treat them as continuous or categorical? Fit piecewise models? Which interactions should be included? What parameterization should be used? Also, testing the desired hypotheses often involves complicated coding of ESTIMATE and CONTRAST statements. This course will provide practical guidance on all these points.
Robin Way
Robin Way
Mr. Robin Way has over 20 years’ experience in the design, development, execution and improvement of applied analytics models for clients in the credit, payments, lending, brokerage, consumer packaged goods, health insurance and energy industries. Mr. Way operates his own management analytics consultancy, Corios LLC (http://coriosgroup.com), based in downtown Portland, Oregon. Mr. Way was previously employed with SAS Institute’s Financial Services Business Unit as a managing analytics consultant for 12 years, in addition to another 10+ years in analytic management roles for several client-side and consulting firms.

Mr. Way’s professional passion is devoted to democratizing and demystifying the science of applied analytics, and his contributions to the field correspondingly emphasize statistical visualization, analytical data preparation, predictive modeling, time series forecasting, and mathematical optimization applied to marketing & risk management strategies. Mr. Way is the lead faculty member for the Banking Analytics Research Council on behalf of the International Institute of Analytics. In cooperation with SAS Institute, Mr. Way is developing a training course on the practice of financial transaction sequence discovery and scoring techniques. Mr. Way’s undergraduate degree from the University of California at Berkeley and his subsequent graduate-level coursework emphasized the analytical modeling of human and consumer behavior.
Introduction to Enterprise Miner
If you've ever wanted to know whether you could apply your statistical analysis skills in a GUI environment like SAS E-Miner, here's an excellent opportunity to find out. The course will cover data preparation, exploratory analytics, information reduction, model specification, model validation and scoring code deployment.