A statistical model for predicting risk of re-imprisonment
The Criminal Re-imprisonment Estimate Scale (CRES) A statistical model for predicting risk of re-imprisonment CSNSW Vision LSI-R Percentage of Recidivists and Non-Recidivists Administered an LSI-R
Current Practice Percentage of Recidivists and Non-Recidivists Administered an LSI-R False Positive True Positives False Positives Risk Screening Tools LSI-R: SV OASys (ORGS) RoR-PV GRAM ROC ROI The Criminal Re-imprisonment Estimate Scale (CRES) Model Development 23,000 DYNAMIC STATIC EMPLOYMENT EDUCATION HOUSING
SUBSTANCE MENTAL HEALTH STATIC GENDER INDIGENOUS AGE SENTENCE LENGTH TIME IN COMMUNITY ADAPTED COPAS RATE PRIOR INCARCERATION OFFENCE 23,000 Adapted Copas rate n = # full-time custodial sentences
t = age at end current imprisonment age first adult imprisonment +5 makes the distribution closer to normal and makes it comparable for those offenders who are at the beginning of their criminal career. Final ModelAdjusted Odds Ratios of Re-imprisonment Area under the curve indicated acceptable fit for the model
Model Adequacy ROC AUC Area under the curve indicated acceptable fit for the model auc = 0.79 CRESLSI-R (Watkins, 2011) Female Indigenous Australian Female Non-Indigenous Australian Male Indigenous Australian Male Non-Indigenous Australian Reimprisonment by predicted probability
% not re-imprisoned % re-imprisoned Application of theCriminal Re-imprisonment Estimate Scale (CRES) to CSNSW Offender Management Model Thresholds Optimal Threshold True positives vs False Positives Model Thresholds Classification Accuracy
Screening Tool Number of Released Inmates with an LSI-R % Sensitivity(True Positives) Specificity (True Negatives) Not Applied 15317 (67) 68 34 >=.15 19337 (84) 97 25 >=.25 15322 89 50 >=.35 12972 (56) 81 62 False Positive Classification Accuracy
Current Practice CRES >=.25 Total Inmate Population 23,000 Total Inmate Population 23,000 LSI-R Administration 15,317 LSI-R Administration 15,317 Recidivists 9,826 Recidivists 9,826 True Positive 68% False Positive 64% True Positive 89% False Positive 50% Reductions in re-imprisonment
Conclusions and Implications Application of the CRES model to practice Redistribution of resources to higher risk offenders Reductions in re-imprisonment Questions? Classification Accuracy
Screening Tool Number of LSI-R Administrations % Sensitivity Specificity Positive predictive value Negative predictive value Not Applied 15317 (100) 94 24 49 85 >=.10 13975 (91) 93 36 51 89 >=.15 12901 (84) 92 38 53 86 >=.2 11793 (77) 45 55 False Positive