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doi:10.1093/ejo/21.5.561

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“…Cox regression-a popular model in survival analyses-is a semiparametric test that models the relationship between predictor variables (i.e., risk and protective factors) and an event (i.e., recidivism), while accounting for differences in time to the occurrence of the event (Blakely & Cox, 1972). given the variation in follow-up times across youth (ranging from 7 to 15 months), and that every youth did not recidivate during the study period (i.e., censored cases), the Cox regression was the ideal technique as it estimates time to a hypothetical date of recidivism for censored cases, based on the survival times of juveniles who actually reoffending (Hosmer & Lemeshow, 1999). Cox regression is popular as its mathematical modeling approach is similar to a logistic regression yet allows for the estimation of survival curves, while accounting for multiple explanatory variables (Kleinbaum & Klein, 2005).…”

Section: Analytic Proceduresmentioning

confidence: 99%

Protective Factors for Reducing Juvenile Reoffending: An Examination of Incremental and Differential Predictive Validity

Barnes-Lee

Campbell

2020

Criminal Justice and Behavior

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Juvenile court practitioners and researchers have recently gained interest in evaluating internal and external strengths, or protective factors. Some scholars assert that incorporating measures of strengths into the risk assessment process can increase the accuracy of identifying odds of recidivating. Relatively few juvenile risk assessment validation studies have evaluated the predictive validity of strengths. This study employed a diverse sample ( N = 278) of juveniles under supervision in a Midwestern court. The Protective Factors for Reducing Juvenile Reoffending (PFRJR) significantly predicted recidivism for the total sample, males, and White youth. There was no evidence of differential predictive validity across gender; however, strengths predicted differently across race/ethnicity. Strengths did not increase the amount of variance explained in recidivism after accounting for the variance explained by risk factor scores. Findings contribute to the paucity of validation studies that investigated the differential and incremental predictive validity of strengths.

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Section: Analytic Proceduresmentioning

confidence: 99%