単発の殺人における犯人の犯罪経歴の予測手法<br/>―ロジスティック回帰分析と決定木の比較―

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.