Shared Concepts and Topics

Parameterization of Model Effects

The general form of a linear regression model is defined in the section Regression Models and Models with Classification Effects in ChapterĀ 3, Introduction to Statistical Modeling with SAS/STAT Software, as

StartLayout 1st Row 1st Column bold upper Y 2nd Column equals bold upper X bold-italic beta plus bold-italic epsilon EndLayout

This section describes how matrices of regressor effects such as bold upper X are constructed in SAS/STAT software. These constructions (parameterization rules) apply to regression models, models with classification effects, generalized linear models, and mixed models. The simplest and most general parameterization rules are the ones used in the GLM procedure, and they are discussed first. Several procedures also support alternate parameterizations of classification variables, including the CATMOD, GENMOD, GLMSELECT, LOGISTIC, PHREG, SURVEYLOGISTIC, and SURVEYPHREG procedures. These are discussed after the GLM parameterization of classification variables and model effects.

All modeling procedures that have a CLASS statement support classification variables and effects, and those procedures that additionally support the supplemental parameterizations have a PARAM= option in the CLASS statement.

Last updated: December 09, 2022