This course focuses on the GLIMMIX procedure, a procedure for fitting generalized linear mixed models.
Learn how to
- analyze binomial data with random effects
- fit a Poisson regression model and a beta regression model with and without random effects
- analyze repeated measures data with discrete outcomes
- perform post-processing analysis
- use the EFFECT statement to define customized model effects
- jointly model multivariate responses with different distributions
- deal with convergence issues.
Who should attend
Analysts, statisticians, and researchers
Formats available | Duration | | |
Classroom: |
2.0 days | | |
|
Before attending this course, you should have taken
Exposure to matrix algebra will enhance your understanding of the material.
This course addresses SAS/STAT software.