A LOG‐MULTIPLICATIVE ASSOCIATION MODEL FOR ALLOCATING HOMICIDES WITH UNKNOWN VICTIM‐OFFENDER RELATIONSHIPS*

Abstract

This research note critically evaluates conventional methods for allocating homicides with an unknown victim/offender relationship to meaningful categories, and it proposes an alternative approach. We argue that conventional methods are based on a problematic assumption, namely, that the missing data mechanism is “ignorable.” As an alternative to these methods, we propose an imputation algorithm derived from a log‐multiplicative model that does not require this assumption. We apply this technique to estimate levels of homicides disaggregated by victim/offender relationship using the Federal Bureau of Investigation's Supplementary Homicide Report (SHR) data for 1996 and 1997, and we compare the resulting estimates with those obtained from the application of conventional procedures. Our results yield a larger proportion of stranger homicides than are obtained from the conventional methods.