Evaluating Human Service and Correctional Programs By Modeling the Timing of Recidivism

Abstract

This paper develops and illustrates a new statistical model of recidivism which enables program evaluators to (1) examine short-run program impact on the postponement of recidivism, through estimates of the average time at which recidivism occurs; (2) measure long-run program impact on the prevention of recidivism, through estimates of the ultimate probability ofrecidivism and (3) help determine when individuals have been successful long enough to be considered "safe," through estimates of their conditional probability of future recidivism.