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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