Mixed Models Analyses Using the SAS System
Classroom duration: 3.0 days Live Web duration: 6 half-day sessions CEU: 1.8
This course teaches you how to analyze linear and generalized mixed models using the MIXED and GLIMMIX procedures, respectively.
Learn how to
- analyze data (including binary data) with random effects
- fit random coefficient models and hierarchical linear models
- analyze repeated measures data
- obtain and interpret the best linear unbiased predictions
- deal with convergence issues.
Who should attend
Statisticians, experienced data analysts, and researchers with sound statistical knowledgePrerequisites
Before attending this course, you should- know how to create and manage SAS data sets
- have experience performing analysis of variance using the GLM procedure of SAS/STAT software
- have completed and mastered the Statistics II: ANOVA and Regression course or completed a graduate-level course on general linear models.
Exposure to matrix algebra will enhance your understanding of the material. Some experience manipulating SAS data sets and producing graphs using SAS/GRAPH software is also recommended.
Course Contents
Introduction to Mixed Models- identifying fixed and random effects
- describing linear mixed model equations and assumptions
- fitting a linear mixed model for a randomized complete block design using the MIXED procedure
- writing CONTRAST and ESTIMATE statements to perform custom hypothesis tests
- fitting a linear mixed model for two-way mixed models
- fitting a linear mixed model for nested mixed models
- fitting a linear mixed model for split-plot designs
- fitting a linear mixed model for crossover designs
- fitting analysis of covariance models with random effects
- performing random coefficient regression analysis
- conducting hierarchical linear modeling
- explaining BLUPs and EBLUPs
- producing parameter estimates associated with the fixed effects and random effects
- explaining the difference between LSMEANS and EBLUPs
- computing LSMEANS and EBLUPs using the MIXED procedure
- discussing issues on repeated measures analysis, including modeling covariance structure
- analyzing repeated measures data using the two-stage approach with the MIXED procedure
- discussing issues associated with unbalanced data, estimation of variance parameters, degrees of freedom, the estimated GLS inference, and nonconvergence problems
- discussing the situations where nonlinear mixed models analysis are needed
- performing the analysis using generalized linear mixed models and the GLIMMIX procedure
Software Addressed
This course addresses the following software product(s): SAS/STAT.Classroom Course Materials
Students receive a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.Live Web Course Materials
Students attend Live Web classes using a Web browser and a telephone and interact with their instructor and fellow classmates in real time. Each student receives an e-mail with instructions on how to join the class three business days before the class begins. The instructions e-mail includes a link to download the course materials, including the exercise files. Students need to download and print the course materials prior to class.System Requirements
For Live Web, you must- review and follow the general system requirements.
- complete the course exercises through our virtual lab. The virtual lab allows you to access the software used in class over the Internet, so that you do not need this software on your local machine.
- run this
test to connect to a virtual lab session. If firewall problems prevent you from connecting to the virtual lab, then you will need the following software installed and configured in your environment to participate in the course exercises:
- Base SAS, SAS/STAT, and SAS/GRAPH software, Release 9.1.3 under a Windows operating system
U.S. Schedule
| 14JAN2009 New York, NY | 19MAY2009 Live Web, | 17JUN2009 Cary, NC |
Check for additional and updated schedule information online at support.sas.com/courses/aglm.html.