MWSUG XX Training

MWSUG is offering extra-fee pre-conference and post-conference full-day training courses on Saturday, October 10, Sunday, October 11, and Wednesday, October 14. The cost for a full-day course is $320 with conference registration or $400 without conference registration.

Conference attendees will also have the opportunity to select up to 2 of the FREE half-day in-conference training classes.

Detailed training course descriptions will be available soon!

Pre-Conference Training

Date Instructor Course Title (click for description)
Saturday, October 10 Art Carpenter From %Macro to %MEND: An Introduction to the SASŪ Macro Language
Ben Cochran Manipulating Data with Functions and Arrays
Kirk Lafler PROC SQL Programming: The Basics and Beyond
Sunday, October 11 Art Carpenter Advanced Techniques in the SASŪ Macro Language
Ben Cochran Advanced SQL Processing
George Fernandez Exploratory Graphical Data Analysis and Model Selection in Multivariate Predictive Modeling
Kirk Lafler Advanced SAS Programming Techniques

FREE In-Conference Training

Day/Time Instructor Course Title (click for description)
Monday, 8:00-10:50am George Fernandez Mixed Model Selection
Monday, 9:00-11:50am Lauren Haworth ODS Workshop
Monday, 2:00-4:50pm Nathaniel Derby Generating Custom-Formatted Excel Output from SASŪ
Monday, 2:00-4:50pm Linda Jolley Best Practices in Base SASŪ Coding
Tuesday, 8:30-11:20am Patricia Cerrito Predictive Modeling in SASŪ Enterprise Miner Versus Regression
Tuesday, 1:00-3:50pm Ben Cochran Getting Started with the Business Intelligence Tools from SASŪ

Post-Conference Training

Date Instructor Course Title (click for description)
Wednesday, October 14 Art Carpenter Advanced Reporting and Analysis Techniques: It's Not Just About The PROCs!
Pat Cerrito Model Choice: from GLM to GLIMMIX with Examples





Descriptions of Training Courses

Pre-Conference Training

From %Macro to %MEND: An Introduction to the SASŪ Macro Language – Art Carpenter
Saturday, October 10, 2009, 8:30am - 4:30pm, Erie

This one-day course is designed for the SAS programmer who is new to the Macro Language. We will start at the basics and cover the fundamentals necessary to start applying SAS macros in your programs. By the end of the day you will understand how the Macro Language works, what the Macro Symbol Table is and how to values stored in it, how the SAS System uses Macro Variables, key Macro Language concepts, important SAS Macro Language Functions, and how to invoke Macros in your programs. The example Macros shown in the course materials demonstrate the power and flexibility of this part of the SAS System and will enable you to apply the functionality of the Macro Language to your own programs right away.

This session is suited for the SAS user who already has a basic understanding of the Data Step and Procedure Steps, and who is new to the Macro Language facility in SAS System software. It is a beginning-level course that assumes no prior understanding of the SAS Macro Language. It is also suitable for SAS users who want to understand the Macros found in programs they have "inherited" from other programmers.

Manipulating Data with Functions and Arrays – Ben Cochran
Saturday, October 10, 2009, 8:30am - 4:30pm, 401

This course is a one day subset of the SAS II course. It focuses solely on the DATA step and sheds much light on the power and functionality of the many Functions in the SAS System. An in-depth look is given to the Arrays, how to create them, how they work, and how to manipulate data with them. Includes many new SAS 9 functions.

PROC SQL Programming: The Basics and Beyond – Kirk Lafler
Saturday, October 10, 2009, 8:30am - 4:30pm, Superior

This course expands your PROC SQL programming skills using numerous examples and techniques of this powerful database language. Topics include strategies for creating and using virtual tables known as views, using case expressions to perform conditional logic and reclassification of data values, database design concepts including basic normalization rules, examples of implementing table integrity constraints, accessing information contained in read-only dictionary tables, interfacing PROC SQL with the Macro facility to create macro variables and macro variable lists, rules associated with index creation and usage, undocumented and hard-to-find PROC SQL features for debugging purposes, complex queries using inner and outer join constructs including set operators, and performance tuning strategies.

Advanced Techniques in the SASŪ Macro Language – Art Carpenter
Sunday, October 11, 2009, 8:30am - 4:30pm, Erie

This one day course is designed for students with a good understanding of the DATA and PROC steps and who already understand the basic structure and syntax of the SAS Macro Language. The course will start with a short review of the macro basics and quickly move on topics selected to improve your macro language expertise. Several key macro functions will be introduced, explained and demonstrated. Course topics include:

Learn how the macro language thinks as you use it to write your programs.

Advanced SQL Processing – Ben Cochran
Sunday, October 11, 2009, 8:30am - 4:30pm, Huron

This course is a sequel to the Intro to SQL course. It goes into more detail on some of the more complex queries. It follows a scenario of building a data mart for a Customer Relationship Management application.

Exploratory Graphical Data Analysis and Model Selection in Multivariate Predictive Modeling – George Fernandez
Sunday, October 11, 2009, 8:30am - 4:30pm, Salon A

Data exploration and graphical data analysis methods stress visualization to thoroughly study the structure of data and to check the validity of statistical model fit to the data. This full-day course covers fundamental concepts for understanding and successfully applying data exploration and graphical data analysis methods by using the powerful user-friendly SAS macro applications. These concepts will be illustrated via downloadable SAS macro files. The participants will learn data exploration and graphical data analysis methods used in exploratory factor analysis, k-mean cluster analysis, multiple and logistic regression.

This workshop is intended for data analysts, predictive modelers, statistical consultants, and bio-statisticians, in advanced training in data exploration and graphical data analysis methods for increasing the effectiveness, efficiency, and productivity of research and development. Participants are required to have an understanding in basic statistical methods and an introductory working knowledge in SAS systems.

Advanced SAS Programming Techniques – Kirk Lafler
Sunday, October 11, 2008, 8:30am - 4:30pm, Superior

SAS users who have acquired basic skills presented in a SAS Software Basics course and want to expand their knowledge in the DATA step as a programming language will want to attend the Advanced SAS Programming Techniques seminar. Attendees learn complex programming topics and techniques in the areas of data access, data manipulation, data management, data presentation, and much more. Topics include DATA step programming techniques including reading a variety of file formats; using column and line pointers; specifying system and language options; coding loops, ranges, and arrays; using operators and modifiers; testing and debugging techniques; reshaping columns of data; techniques on managing data ; custom report writing techniques; and integrating ODS for improved output.




FREE In-Conference Training

Getting Started with the Business Intelligence Tools from SASŪ – Ben Cochran
Tuesday, 1:00-3:50 p.m., Salon E

I want to create a drilldown report in Web Report Studio ... What do I need to do? Well, as you know, WRS has to have a Map (so we cover Info Map Studio), the map has to be registered, so we cover just enough SAS Management Console to register data. etc., etc., etc... . To answer this question, the course really starts with the SAS datasets needed, then goes quickly thru SMC, then OLAP Cube Studio, then Info Map Studio, then finally Web Report Studio. Again, not a lot of detail on each topic, but what you need to know to get up and running.

Mixed Model Selection – George Fernandez
Monday, 8:00-10:50 a.m., Salon E

A user-friendly SASŪ macro application to perform all possible model selection of fixed effects including quadratic and cross products within a user-specified subset range in the presence of random and repeated measures effects using SAS PROC MIXED will be demonstrated in this training class. This macro application, ALLMIXED2 will complement the model selection option currently available in the SAS PROC REG for multiple linear regressions and the new SAS procedure GLMSELECT that focuses on the standard independently and identically distributed general linear model for univariate responses. Options are also included in this macro to select the best covariance structure associated with the user-specified fully saturated repeated measures model; to graphically explore and to detect statistical significance of user specified linear, quadratic, interaction terms for fixed effects; and to diagnose multicollinearity, via the VIF statistic for each continuous predictors involved in each model selection step. Two model selection criteria, AICC (corrected Akaike Information Criterion) and MDL (minimal description length) are used in all possible model selection and summaries of the best model selection are compared graphically. The differences in the degree of penalty factors associated with the model dimension between AICC and MDL are investigated. Complete mixed model analysis of final model including data exploration, influential diagnostics, and checking for model violations using the experimental ODS GRAPHICS option available in Version 9.13 is also implemented. The ALLMIXED2 SAS macro application is an improved version of the SAS macro application ALLMIXED2 previously reported. Instructions for downloading and running this user-friendly macro application will be demonstrated.

Generating Custom-Formatted Excel Output from SASŪ – Nathaniel Derby
Monday, 2:00-4:50 p.m., Salon E

Do you spend too much time manually formatting your Excel output from SAS, such as setting font sizes, coloring cells, or cutting and pasting data onto a pre-formatted Excel template? Then this course is for you! Learn how to program SAS to automatically custom-format your Excel spreadsheets for you. In this course, you'll be introduced to many different techniques for creating customized Excel output from SAS, and the differences between them. You'll learn which technique is best for many different situations. Detailed examples will be given for each technique.

ODS Workshop – Lauren Haworth
Monday, 9:00-11:50 a.m., Salon A

Beginning with basic syntax and progressing to more complex techniques and custom styles, you will learn to take basic SAS output and transform it into an HTML page, a word-processor-friendly RTF file, or printer-friendly PDF output. For this workshop, the primary focus will be on RTF and PDF, though most of the examples will work for HTML as well.

In addition, you'll learn how to generate a Table of Contents page for RTF and PDF files, generate bookmarks for PDF files and generate custom page numbering for those destinations. You will learn the basic concepts of changing style templates and using tagset templates to generate custom markup language tags and output. Other new features of ODS are discussed, such as the ODS Graphics Framework and the new statistical graphics procedures.

Predictive Modeling in SASŪ Enterprise Miner Versus Regression – Patricia Cerrito
Tuesday, 8:30-11:20 a.m., Salon E

We investigate the difference between regression models in SAS/Stat and compare them to the predictive models in SASŪ Enterprise Miner. In large samples, the p-value becomes meaningless because the effect size is virtually zero. Therefore, there must be another way to determine the adequacy of the model. In addition, logistic regression cannot be used to predict rare occurrences. Such a model will be highly accurate, generally predicting all occurrences as non-occurrence. However, it will have no practical use whatsoever in identifying those at high risk. In contrast, predictive modeling in Enterprise Miner was designed to accommodate large samples and rare occurrences as well as providing many measures of model adequacy.

Best Practices in Base SASŪ Coding – Linda Jolley
Monday, 2:00-4:50 p.m., Salon G

How you write SASŪ code can have a tremendous impact on the use of computer and programmer resources. In this seminar, we'll look at techniques you should use whenever you write SAS code to minimize the use of CPU, I/O, memory, disk space, and networking resources. We'll examine SAS coding techniques that produce identical results and compare the computer resource usage of each technique. We'll also look at some "tricks of the trade" to minimize code maintenance.




Post-Conference Training

Advanced Reporting and Analysis Techniques for the SASŪ Power User: It's Not Just About The PROCs! – Art Carpenter
Wednesday, October 14, 2009, 8:30am - 4:30pm, Huron

There are literally hundreds of techniques used on a daily basis by the users of SASŪ 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 proved to be useful to the intermediate and advanced SAS programmer that 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’.

The course includes a wide variety of options and techniques associated with:

Model Choice: from GLM to GLIMMIX with Examples – Pat Cerrito
Wednesday, October 14, 2009, 8:30am - 4:30pm, Erie

I would like to include model assumptions and model problems. This includes the problem of predicting a rare occurrence using logistic regression.