Comparing the Predictive Accuracy of Case Linkage Methods in Serious Sexual Assaults

Abstract

The empirical support for linkage analysis is steadily increasing, but the question remains as to what method of linking is the most effective. We compared a more theory-based, dimensional behavioural approach with a rather pragmatic, multivariate behavioural approach with regard to their accuracy in linking serial sexual assaults in a UK sample of serial sexual assaults (n = 90) and one-off sexual assaults (n = 129). Their respective linkage accuracy was assessed by (1) using seven dimensions derived by non-parametric Mokken scale analysis (MSA) as predictors in discriminant function analysis (DFA) and (2) 46 crime scene characteristics simultaneously in a naive Bayesian classifier (NBC). The dimensional scales predicted 28.9% of the series correctly, whereas the NBC correctly identified 34.5% of the series. However, a subsequent inclusion of non-serial offences in the target group decreased the amount of correct links in the dimensional approach (MSA–DFA: 8.9%; NBC: 32.2%). Receiver operating characteristic analysis was used as a more objective comparison of the two methods under both conditions, confirming that each achieved good accuracies (AUCs = .74–.89), but the NBC performed significantly better than the dimensional approach. The consequences for the practical implementation in behavioural case linkage are discussed. Copyright © 2012 John Wiley & Sons, Ltd.