Discriminant analysis is a method of predicting the level of a one-way classification variable based on known values of the responses. The technique is based on how close the measurement variables are to the multivariate means of the levels being predicted. Discriminant analysis is more fully implemented in the Discriminant Platform. See “Discriminant Analysis” in Multivariate Methods.
In the Manova personality of the Fit Model platform, specify the measurement variables as Y effects and the classification variable as a single X effect. The multivariate fitting platform gives estimates of the means and the covariance matrix for the data, assuming that the covariances are the same for each group. You obtain discriminant information with the Save Discrim option in the Manova Fit red triangle menu. The Save Discrim option saves distances and probabilities as columns in the current data table using the initial E and H matrices. For an example of the Save Discrim option, see Example of the Save Discrim Option.
For a classification variable with k levels, the Save Discrim option adds k distance columns, k classification probability columns, the predicted classification column, and two columns of other computational information to the current data table.