NCJ Number
34749
Journal
Journal of Research in Crime and Delinquency Volume: 13 Issue: 1 Dated: (JANUARY 1976) Pages: 64-81
Date Published
1976
Length
18 pages
Annotation
THIS ARTICLE REVIEWS THE BASIC ASSUMPTIONS WHICH MUST BE MET BEFORE LINEAR REGRESSION TECHNIQUES CAN BE APPLIED WITH MAXIMUM EFFECTIVENESS IN PREDICTIVE CRIMINAL JUSTICE RESEARCH.
Abstract
STARTING WITH AN INTUITIVE EXPLANATION 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 OUTCOMES 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 OF CORRECTIONS. (AUTHOR ABSTRACT)