Multivariate analysis ('forensiometrics')--a new tool in forensic medicine. Differentiation between sharp force...

Multivariate projective statistical methods (PCA, PLS-DA) and logistic regression analysis were used to create models to make predictions regarding whether a certain fatality shows similarities to homicide or suicide. The 'model set' consisted of 174 deaths due to sharp force injuries that in previous medicolegal investigation had been judged as homicides and 105 as suicides. The models were then validated on a new set of 40 homicides and 27 suicides that had not been used to create the models (test set validation). The model based on the PLS-DA technique had regarding its ability to identify homicides a sensitivity of 40/40 = 100% and a specificity of 25/27 = 93%. The model's predictions agreed with previously performed medicolegal investigations except in two suicides which according to the model were likely to be homicides. The reliability of this model was somewhat better than predictions achieved by means of logistic regression analysis, where six otherwise proven homicides were wrongly classified as suicides and two actual suicides were misclassified as homicides. The technique not only identifies variables but also ranks their importance. Ranked according to falling positive correlation (falling 'importance' of a finding) to the dependent variable 'death caused by homicide', the predictors were: Injuries to clothing, blood alcohol level, presence of defence injuries, injuries due to other type of violence than sharp force, chest stabs with vertical axis of the entrance wound, sharp force injuries to the upper extremity (except wrist and crook of the arm), sharp force injuries to the head and back. Ranked in increasing positive correlation to 'death caused by suicide' were the predictors: sharp force injuries to the crook of the arm, venue being the victim's home, presence of farewell letter, victim's age, sharp force injuries to the wrist, known suicidal ideation and presence of tentative injuries.