Assessing Sex Offender Recidivism Using Multiple Measures

Abstract

While the recidivistic activity of sex offenders has received considerable attention from researchers, most studies have been limited by using a single measurement of recidivism. Using arrest/conviction episodes as the unit of analysis, the present study tracked 389 convicted sex offenders for up to 10 arrest/conviction episodes using 11 different measurements of recidivism for an average of 15.7 years. Logistic regression was used to create a model that successfully predicted recidivism with approximately 70% accuracy. The rate of recidivism as defined by new convictions for sex offenses was approximately 10% overall.