PROC GLM Contrasted with Other SAS Procedures
As described previously, PROC GLM can be used for
many different analyses and has many special
features not available in other SAS procedures.
However, for some types of analyses,
other procedures are available.
As discussed in the "PROC GLM for Unbalanced ANOVA" and "PROC GLM for Quadratic Least Squares Regression"
sections,
sometimes these other procedures are more efficient than PROC GLM.
The following procedures perform some of the same analyses as PROC GLM:
 ANOVA

performs analysis of variance for balanced designs.
The ANOVA procedure is generally more efficient than PROC GLM for these designs.
 MIXED

fits mixed linear models by incorporating covariance structures in
the model fitting process. Its RANDOM and REPEATED statements are
similar to those in PROC GLM but offer different functionalities.
 NESTED

performs analysis of variance and estimates
variance components for nested random models.
The NESTED procedure is generally more efficient
than PROC GLM for these models.
 NPAR1WAY

performs nonparametric oneway analysis of rank scores.
This can also be done using the RANK procedure and PROC GLM.
 REG

performs simple linear regression.
The REG procedure allows several MODEL statements and gives additional
regression diagnostics, especially for detection of collinearity.
PROC REG also creates plots of model summary statistics
and regression diagnostics.
 RSREG

performs quadratic responsesurface regression,
and canonical and ridge analysis.
The RSREG procedure is generally recommended for data
from a response surface experiment.
 TTEST

compares the means of two groups of observations.
Also, tests for equality of variances for the two groups are available.
The TTEST procedure is usually more efficient than PROC GLM for this type of data.
 VARCOMP

estimates variance components for a general linear model.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.