Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

BACKGROUND: The application of statistical modeling techniques, including classification and regression trees, in the prediction of violence has increasingly received attention. METHODS: The predictive performance of logistic regression and classification tree methods in predicting violence was explored in a sample of patients with psychotic illness. RESULTS: Of 2 logistic regression models, the forward stepwise method produced a simpler model than the full model, but the latter performed better. The performance of the classification tree appeared to be high before cross-validation, but reduced when cross-validated. The standard logistic model was the most robust model. A simplified tree with extra weight given to violent cases was a reasonable competitor and was simple to apply. CONCLUSION: Although classification trees can be suitable for routine clinical practice, because of the simplicity of their decision-making processes, their robustness and therefore clinical utility was problematic in this sample. Further research is required to compare such models in large prospective epidemiologic studies of other psychiatric populations.


Journal article


Compr Psychiatry

Publication Date





296 - 303


Adolescent, Adult, Aged, Comorbidity, Female, Humans, Logistic Models, Male, Middle Aged, Personality Disorders, Psychotic Disorders, Risk Factors, Violence