The Development and Validation of Statistical Prediction Rules for Discriminating Between Genuine and Simulated Suicide Notes

Abstract

The suicide note is a valuable source of information for assisting police forces in equivocal death investigations. The present study endeavored to develop statistical prediction rules to discriminate between genuine and simulated suicide notes. Discriminant function analysis was performed on a sample of 33 genuine and 33 simulated notes to identify variables that serve as best predictors of note authenticity. Receiver operating characteristic analysis was then applied to validate these models and establish decision thresholds. The optimal model yielded an accuracy score of ⋅82, with average sentence length and expression of positive affect being particularly effective at discriminating between the notes. Theoretical implications are discussed as are the practical advantages of applying receiver operating characteristic analysis in the investigation of equivocal deaths.