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Abstract

The weapon type used in a homicide predicts the victim-perpetrator relationship. However, there are some limitations in this past research including the common data analytic strategies. Our purpose was to build a model of weapon type, predicting relationship type, and to address previous limitations. We examined 363,927 homicides and used Bayesian multilevel categorical regression. In addition to analyzing weapon type (final model consisted of 16 weapon categories), we examined the victims’ sex, age, and race as covariates and modeled the data across states and counties. Results indicate that weapon type is highly informative, however, the age of the victim and sex of the victim interact in important ways.

Keywords

homicide weapons Bayesian statistics multilevel models categorical regression

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Examining the Relationship Between Weapon Type and Relationship Type in American Homicides: A Bayesian Approach

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