Target group
Analysts, statisticians, and researchers
Course structure
Introduction to Generalized Linear Mixed Models and the GLIMMIX Procedure
- introduction to generalized linear mixed models
- introduction to the GLIMMIX procedure using logistic regression with random effects
Applications Using the GLIMMIX Procedure
- Poisson regression with random effects
- an example of beta regression
- repeated measures data with discrete response
- introduction to radial smoothing (self-study)
GLIMMIX Procedure Topics
- estimation methods used in PROC GLIMMIX
- processing models by subjects
- the FIRSTORDER adjustment to the KR degrees of freedom estimation method
- covariance matrix diagnostics
- constructed effects using the EFFECT statement
- processing models by subjects
- comparison of the GLIMMIX procedure and the NLMIXED procedure
- comparison of the GLIMMIX procedure and the GENMOD procedure
- modeling multivariate responses
- dealing with convergence problems
