Parameterization of Model Effects

Recall the general form of a linear regression model defined in , Regression Models and Models with Classification Effects :

This section describes how matrices of regressor effects such as are constructed in SAS/STAT. These constructions, or 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 GENMOD, GLMSELECT, LOGISTIC, SURVEYLOGISTIC, and PHREG procedures. These are discussed after the GLM parameterization of classification variables and model effects.

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