A comparison of statistical models in predicting violence in psychotic illness.
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.


CONCLUSIONS
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.
Thomas
Stuart
S
Health Services Research Department, Institute of Psychiatry, De Crespigny Park, London SE5 8AE UK.
Leese
Morven
M
Walsh
Elizabeth
E
McCrone
Paul
P
Moran
Paul
P
Burns
Tom
T
Creed
Francis
F
Tyrer
Peter
P
Fahy
Thomas
T
D000293:Adolescent; D000328:Adult; D000368:Aged; D015897:Comorbidity; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010554:Personality Disorders / Q000453:epidemiology; D011618:Psychotic Disorders / Q000453:epidemiology*; D012307:Risk Factors; D014754:Violence / Q000706:statistics & numerical data*