General Discriminant Analysis Models Overview
The General Discriminant Analysis (GDA) module is called a "general" discriminant analysis program because it applies the methods of the general linear model (see also General Linear Models (GLM)) to the discriminant function analysis problem. A general overview of discriminant function analysis, and the traditional methods for fitting linear models with categorical dependent variables and continuous predictors, is provided in the context of the Discriminant Analysis module (see the Introductory Overview). In the GDA module, the discriminant function analysis problem is "recast" as a general multivariate linear model, where the dependent variables of interest are (dummy-) coded vectors that reflect the group membership of each case. The remainder of the analysis is then performed as described in the context of General Regression Models (GRM), with a few additional features noted below. See also, GDA - Index.
Other Introductory Overview
Coding the Categorical Dependent Variable
Comparison with Other Stepwise Discriminant Analysis Programs
- GDA Introductory Overview - Coding the Categorical Dependent Variable
- GDA - Methods for Specifying Designs
- GDA Models Results
- General Discriminant Analysis (GDA) Models - Examples