The GLIMMIX Procedure

Parameterization of Generalized Linear Mixed Models

PROC GLIMMIX constructs a generalized linear mixed model according to the specifications in the CLASS, MODEL, and RANDOM statements. Each effect in the MODEL statement generates one or more columns in the matrix bold upper X, and each G-side effect in the RANDOM statement generates one or more columns in the matrix bold upper Z. R-side effects in the RANDOM statement do not generate model matrices; they serve only to index observations within subjects. This section shows how the GLIMMIX procedure builds bold upper X and bold upper Z. You can output the bold upper X and bold upper Z matrices to a SAS data set with the OUTDESIGN= option in the PROC GLIMMIX statement.

The general rules and techniques for parameterization of a linear model are given in GLM Parameterization of Classification Variables and Effects in ChapterĀ 20, Shared Concepts and Topics. The following paragraphs discuss how these rules differ in a mixed model, in particular, how parameterization differs between the bold upper X and the bold upper Z matrix.

Last updated: December 09, 2022