Taking the next step: combining incrementally valid indicators to improve recidivism prediction.
The possibility of combining indicators to improve recidivism prediction was evaluated in a sample of released federal prisoners randomly divided into a derivation subsample (n = 550) and a cross-validation subsample (n = 551). Five incrementally valid indicators were selected from five domains: demographic (age), historical (prior convictions), adjustment (prior incident reports), rating scale (Violation scale of the Lifestyle Criminality Screening Form), and self-report (General Criminal Thinking score from the Psychological Inventory of Criminal Thinking Styles). After converting scores on the five indicators to a common scale (z score), two combined scores were calculated: a simple summed score (unweighted summed score) and a score computed using beta weights from a Cox survival analysis of the derivation subsample (weighted summed score). Correlational and receiver operating characteristic analyses revealed that the unweighted and weighted summed scores produced equivalent results and that both improved significantly on the results of the five contributing indicators.