Japanese Journal of Forensic Science and Technology
Online ISSN : 1881-4689
Print ISSN : 1880-1323
ISSN-L : 1880-1323
Technical Note
Methods for predicting offender's criminal history in single homicide cases: Comparison of logistic regression analysis and decision trees
Yusuke OtsukaKazuki HiramaKaeko YokotaKazumi WatanabeTaeko Wachi
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2017 Volume 22 Issue 1 Pages 25-34

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Abstract
 The present study compared decision tree analysis to logistic regression analysis in order to investigate whether decision tree analysis has sufficient ability to construct a model that predicts offender characteristics from the crime scene and/or victim information. The data used in this study were collected from solved single homicide cases that occurred in Japan between 2004 and 2009 (n=1226). After constructing models that predict offender's criminal history by logistic regression analysis and decision tree analysis, AUC (area under the ROC curve) of those models and the predictive values were compared. The AUC was .75 (p<.001) for logistic regression model and .71 (p<.001) for the decision tree model. A significant difference between these AUCs was not observed (χ2(1)=3.71, p=.05). The predictive values were 67.3% for both the logistic regression model and the decision tree model. These findings suggest that the decision tree is comparable to logistic regression analysis in constructing a model that predicts the offender's criminal history from offence characteristics in single homicide cases.
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© 2017 Japanese Association of Forensic Science and Technology
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