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Competing Risks, Persistence, and Desistance in Analyzing Recidivism
Authors:Gabriel Escarela  Brian Francis  Keith Soothill
Affiliation:(1) Centre for Applied Statistics, Lancaster University, Fylde College, Lancaster, LA1 4YF, United Kingdom;(2) Department of Applied Social Science, Lancaster University, Cartmel College, Lancaster, LA1 4YL, United Kingdom
Abstract:A statistical procedure is developed to analyze recidivism in samples whichare subject to the presence of desisters and to multiple modes ofreconviction. This allows for a more accurate study of individuals'transition and hazard in the type and timing of offenses following aspecific type of conviction. The use of a nonparametric approach forinvestigating failure in the presence of other acting causes is shown;initial estimators of the probabilities of reconviction for different typesof offenses are obtained, and the method can be used both to display thedata and to choose an appropriate parametric family for the survivaltimes. An exponential mixture model for competing risks is presented insuch a way that it allows us to adjust for concomitant variables and toassess their effects on the probabilities both of reconviction forpredetermined types of offenses and desistance and of the hazards ofreconviction; a method for assessing calibration of predicted survivalprobabilities is suggested. A 21-year follow-up of persons convicted ofindecent assault on a female in 1973 illustrates the methods; we find ahigh probability of sexual reconviction for individuals with previoussexual convictions and evidence of diversity and a raised hazard ofreconviction for young chronic offenders.
Keywords:survival analysis  event-specific hazard  split population models  sex offenders  indecent assault
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