Differentiating Genuine and False Rape Allegations: A Model to Aid Rape Investigations

Abstract

The aim of this study was to compare the victimology, offence demographics and offence behaviours of genuine and false allegations of rape in order to develop a model that could be used to aid in differentiating between genuine and false rape allegations. Eighty false allegations of rape were compared with 160 genuine allegations of rape, obtained from the Serious Crime Analysis Section (SCAS). Data were taken directly from complainant statements and 62 variables were dichotomously coded. Chi-square, odds ratios and Mann-Whitney U tests were initially completed and then the more significant variables were entered into a backwards stepwise logistic regression. The resultant logistic regression model classified 91.7% of the sample correctly. The model was validated using an additional 12 cases, with an 83% success rate. This study found that a number of factors successfully discriminated between genuine and false rape allegations. It thus offers a tool that might aid police investigations, crime analysts and behavioural investigative advisors in the veracity assessment of rape allegations.