|Introduction to Analysis-of-Variance Procedures
This chapter reviews the SAS/STAT software procedures that are used
for analysis of variance: GLM, ANOVA, CATMOD, MIXED, NESTED,
NPAR1WAY, TRANSREG, TTEST, and VARCOMP.
Also discussed are SAS/STAT and SAS/QC software procedures for
constructing analysis of variance designs: PLAN, FACTEX, and OPTEX.
The flagship analysis-of-variance procedure is the GLM
which handles most standard problems. The following are descriptions
of PROC GLM and other procedures that are used for more
- performs analysis of variance, multivariate analysis of variance,
and repeated measures analysis of variance for balanced designs.
PROC ANOVA also performs several multiple comparison tests.
- fits linear models and performs analysis of variance and repeated
measures analysis of variance for categorical responses.
- fits generalized linear models and performs analysis of variance
in the generalized linear models framework. The methods are
particularly suited for discrete response outcomes.
- performs analysis of variance, regression, analysis of covariance,
repeated measures analysis, and multivariate analysis of variance.
PROC GLM produces several diagnostic measures, performs tests for random
effects, provides contrasts and estimates for customized
hypothesis tests, performs several multiple comparison tests, and
provides tests for means adjusted for covariates.
- performs mixed-model analysis of variance and repeated
measures analysis of variance via covariance structure
modeling. Using likelihood-based or
method-of-moment estimates, PROC MIXED constructs
statistical tests and intervals, allows customized
contrasts and estimates, and computes empirical
- performs analysis of variance and analysis of covariance for
purely nested random models.
- performs nonparametric one-way analysis of rank scores.
- compares the means of two groups of observations.
- fits univariate and multivariate linear models, optionally
with spline and other nonlinear transformations.
- estimates variance components for random or mixed models.
The following section 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 "References" section.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.