Problems with the Use of Regression Analysis in Prediction Studies

Abstract

This article reviews the basic assumptions which must be met before linear regression techniques can be applied with maximum effectiveness. Starting with an intuitive explana tion of simple regression, the article proceeds to a discussion of more complex models which have applications in criminal justice research.

Using this discussion as a background, it is shown that linear regression models which predict events with only two out comes violate two basic assumptions. Several alternative methods of dealing with this problem are examined, and one method, a multivariate logistic model, is used to estimate the probability of recidivism based on data provided by the Michigan Department o f Corrections.