Discriminant Analysis with Categorical Data

Abstract

A method for studying relationships among groups in terms of categorical data patterns is described. The procedure yields a dimensional representation of configural relationships among multiple groups and a quantitative scaling of categorical data patterns for use in subsequent assignment of new individuals to the groups. Two examples are used to illustrate potential of the method. In the first, profile data that were previously analyzed by metric multiple discriminant function analysis are reanalyzed by the nonmetric categorical data pattern technique with highly similar results. The second example examines relationships among psychiatric syndrome groups in terms of similarities in patterns of categorical background variables. Results appear consistent with other available information concerning the epidemiology of psychiatric disorders.