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.

凶杀中使用的武器类型可以预测受害者与犯罪者之间的关系。但是，在过去的研究中存在一些局限性，包括常见的数据分析策略。我们的目的是建立武器类型模型，预测关系类型并解决以前的局限性。我们检查了363,927起凶杀案，并使用贝叶斯多级分类回归。除了分析武器类型（最终模型包括16种武器类别）之外，我们还检查了受害者的性别，年龄和种族作为协变量，并对各个州和县的数据进行了建模。结果表明，武器类型具有丰富的信息，但是，受害者的年龄和受害者的性别以重要方式相互作用。