Abstract
Bayesian reasoning has already been applied in the area of assessing recidivism risk Based on single predictors for re-offending, various authors have pointed out that Bayesian analysis was suited to the problem because the base rate of recidivism could be accounted for in terms of a prior probability The present paper extends this argument towards the multivariate case The result is a ...
Abstract
Bayesian reasoning has already been applied in the area of assessing recidivism risk Based on single predictors for re-offending, various authors have pointed out that Bayesian analysis was suited to the problem because the base rate of recidivism could be accounted for in terms of a prior probability The present paper extends this argument towards the multivariate case The result is a case-specific probabilistic assessment that allows judges and juries to reach Informed decisions The present paper illustrates the method through the combination of offender's age with data from a structured professional risk assessment instrument, the Psychopathy Check list-Revised (PCL-R), for a sample of N = 393 German convicts The combination of these two criteria emerged as optimal from all available subsets of predictors (including the History Clinical Risk-20 and its components) The effect size for the Bayesian combination measure with regard to violent offense recidivism was large and significantly higher than the predictive value for each of its constituents The study design was retrospective, average time at risk was 6 5 years
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