Addressing problems with traditional crime linking methods using receiver operating characteristic analysis
Version of Record online: 24 DEC 2010
2009 The British Psychological Society
Legal and Criminological Psychology
Volume 14, Issue 2, pages 293–310, September 2009
How to Cite
Bennell, C., Jones, N. J. and Melnyk, T. (2009), Addressing problems with traditional crime linking methods using receiver operating characteristic analysis. Legal and Criminological Psychology, 14: 293–310. doi: 10.1348/135532508X349336
- Issue online: 24 DEC 2010
- Version of Record online: 24 DEC 2010
- Received 17 January 2007; revised version received 11 July 2008
Purpose. Through an examination of serial rape data, the current article presents arguments supporting the use of receiver operating characteristic (ROC) analysis over traditional methods in addressing challenges that arise when attempting to link serial crimes. Primarily, these arguments centre on the fact that traditional linking methods do not take into account how linking accuracy will vary as a function of the threshold used for determining when two crimes are similar enough to be considered linked.
Methods. Considered for analysis were 27 crime scene behaviours exhibited in 126 rapes, which were committed by 42 perpetrators. Similarity scores were derived for every possible crime pair in the sample. These measures of similarity were then subjected to ROC analysis in order to (1) determine threshold-independent measures of linking accuracy and (2) set appropriate decision thresholds for linking purposes.
Results. By providing a measure of linking accuracy that is not biased by threshold placement, the analysis confirmed that it is possible to link crimes at a level that significantly exceeds chance (AUC = .75). The use of ROC analysis also allowed for the identification of decision thresholds that resulted in the desired balance between various linking outcomes (e.g. hits and false alarms).
Conclusions. ROC analysis is exclusive in its ability to circumvent the limitations of threshold-specific results yielded from traditional approaches to linkage analysis. Moreover, results of the current analysis provide a basis for challenging common assumptions underlying the linking task.