Quantifying the contributions of three types of information to the prediction of criminal conviction using the receiver operating characteristic

Abstract

Background: Quantifying the contributions that different types of information make to the accurate prediction of offending offers the prospects of improved practice and better use of resources. Aims: To quantify the contributions made by three types of information - demographic data alone, demographic and criminal record and demographic, criminal record and legal class of disorder - to the prediction of criminal conviction in patients. Method: All 425 patients discharged from the three special (high secure) hospitals in England and Wales over 2 years were followed for 10.5 years. The contribution of each type of information was described in terms of the area under the receiver operating characteristic curve (AUC) and the number needed to detain (NND). Results: The AUC values using the three types of information were 0.66, 0.72 and 0.73 respectively. Prediction based on the full model using an optimal probability cut-off implies an NND of 2. The AUCs for serious offences were 0.67, 0.69 and 0.75 respectively. Conclusions: For long-term prediction of conviction on any charge, information on legal class adds little to the accuracy of predictions made using only a patient's age, gender and criminal record. In the prediction of serious offences alone the contribution of legal class is significant. Declaration of interest: None.