Many procedures in SAS/STAT enable you to incorporate classification effects into your model and to perform statistical inferences for experimental factors and their interactions. These procedures do not necessarily rely on sums of squares decompositions to perform these inferences. Examples of such procedures are the CATMOD, GENMOD, GLIMMIX, LOGISTIC, NPAR1WAY, and TTEST procedures. In fact, any one of the more than two dozen SAS/STAT modeling procedures that include a CLASS statement can be said to perform analysis of variance in this general sense. For more information about individual procedures, refer to their corresponding chapters in this documentation.

The following section discusses procedures in SAS/STAT that compute analysis of variance in models with classification factors in the narrow sense—that is, they produce analysis of variance tables and form F tests based on sums of squares, mean squares, and expected mean squares.

The subsequent sections discuss procedures that perform statistical inference in models with classification effects in the broader sense.

The following section also presents an overview of some of the fundamental features of analysis of variance. Subsequent sections describe how this analysis is performed with procedures in SAS/STAT software. For more detail, see the chapters for the individual procedures. Additional sources are described in the section References.