Three methods of transforming unordered categorical response variables are described: (1) analysis using dummy variables; (2) eigenanalysis of frequency patterns scaled relative to within-groups variance; (3) categorical variables analyzed separately with scale values generated so that the grouping variable and the categorical variable are…

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

A dichotomous dependent variable is used to determine a combination of variables that will predict group membership. Dichotomous variables are frequently encountered in multiple regression analysis. However, several textbooks question the appropriateness of using multiple regression analysis when analyzing dichotomous dependent variables. The…