Discriminant analysis comprises two approaches to analyzing group data: descriptive discriminant analysis (DDA) and predictive discriminant analysis (PDA). Both use continuous (or intervally scaled) data to analyze the characteristics of group membership. However, PDA uses this continuous data to predict group membership (i.e., How accurately can a classification rule classify the current sample into groups?), while DDA attempts to discover what continuous variables contribute to the separation of groups (i.e., Which of these variables contribute to group differences and by how much?). In addition to the primary goal of discriminating among groups, DDA can examine the most parsimonious way to discriminate between groups, investigate the amount of variance accounted for by the discriminant variables, and evaluate the relative contribution of each discriminant (continuous) variable in ...