STEPDISC Procedure
Given a classification variable and several quantitative variables, the STEPDISC procedure performs a stepwise discriminant analysis
to select a subset of the quantitative variables for use in discriminating among the classes. The set of variables that make up each
class is assumed to be multivariate normal with a common covariance matrix. The following are highlights of the STEPDISC procedure's
features:
 selection methods include forward selection, backward elimination, and stepwise selection
 variables are chosen to enter or leave the model according to one of two criteria:
 the significance level of an F test from an analysis of covariance, where the variables already
chosen act as covariates and the variable under consideration is the dependent variable
 the squared partial correlation for predicting the variable under consideration from the
CLASS variable, controlling for the effects of the variables already selected for the model

 performs BY group processing, which enables you to obtain separate analyses on grouped observations
 perform weighted analysis
 creates a SAS data set that corresponds to any output table

For further details see the SAS/STAT User's Guide:
The STEPDISC Procedure
( PDF  HTML )
Examples