SPSS® 12.0 Command Syntax Reference

468 DISCRIMINANT
Example
Overview
Options
DISCRIMINANT GROUPS=OUTCOME (1,4)
/VARIABLES=V1 TO V7
/SAVE CLASS=PREDOUT.
DISCRIMINANT performs linear discriminant analysis for two or more groups. The goal of
discriminant analysis is to classify cases into one of several mutually exclusive groups based
on their values for a set of predictor variables. In the analysis phase, a classification rule is
developed using cases for which group membership is known. In the classification phase, the
rule is used to classify cases for which group membership is not known. The grouping
variable must be categorical, and the independent (predictor) variables must be interval or
dichotomous, since they will be used in a regression-type equation.
Variable Selection Method. In addition to the direct-entry method, you can specify any of
several stepwise methods for entering variables into the discriminant analysis using the
METHOD subcommand. You can set the values for the statistical criteria used to enter variables
into the equation using the TOLERANCE, FIN, PIN, FOUT, POUT, and VIN subcommands,
and you can specify inclusion levels on the ANALYSIS subcommand. You can also specify the
maximum number of steps in a stepwise analysis using the MAXSTEPS subcommand.
Case Selection. You can select a subset of cases for the analysis phase using the SELECT
subcommand.
Prior Probabilities. You can specify prior probabilities for membership in a group using the
PRIORS subcommand. Prior probabilities are used in classifying cases.
New Variables. You can add new variables to the working data file containing the predicted
group membership, the probability of membership in each group, and discriminant function
scores using the SAVE subcommand.
Classification Options. With the CLASSIFY subcommand, you can classify only those cases
that were not selected for inclusion in the discriminant analysis, or only those cases whose
value for the grouping variable was missing or fell outside the range analyzed. In addition,
you can classify cases based on the separate-group covariance matrices of the functions
instead of the pooled within-groups covariance matrix.
Statistical Display. You can request any of a variety of statistics on the STATISTICS subcommand.
You can rotate the pattern or structure matrices using the ROTATE subcommand. You
can compare actual with predicted group membership using a classification results table
requested with the STATISTICS subcommand or compare any of several types of plots or histograms
using the PLOT subcommand.