The Development of a Parolee Classification System Using Discriminant Analysis

Abstract

A parolee classification system using discriminant analysis is presented. Approximately 13,000 parolees released in 1969 and followed for two years constitute the data base. The sample is split into two parts so that the model can be first tested and then validated. The results of both the test and holdout samples suggest that the discriminant model is quite useful for classifying parolees into "good" versus "poor" parole risks.

When we compare the multivariate results with those obtained using un ivariate analysis, we show that the multivariate results are superior to the un ivariate results and demonstrate that results generated from univariate analyses can be quite misleading. In particular, it is demonstrated that the "best" univariate discriminator is a relatively poor multivariate discriminator. Moreover, the best multivariate discriminator appears to be a far less impor tant discriminator in a univariate framework.