Wendy C. Regoeczi

Uncleared Homicides: A Canada/United States Comparison

Beginning in the 1960s, there has been a marked decline in clearance rates of homicides, a finding that has generated little interest among criminological researchers. This article presents a comparative analysis of homicide clearance in Canada and the United States using data generated by the Canadian Centre of Justice Statistics and the U.S. Federal Bureau of Investigations Supplementary Homicide Reports. Using logistic regression, homicide clearance is predicted on the basis of specific victim and offense characteristics for cases in Canada versus the United States and in Ontario versus New York State. The results indicate that the model is a good fit for homicide clearance in both countries as a whole. Whereas the homicide weapon, circumstances surrounding the offense, age, and gender of the victim were found to be significant homicide clearance predictors in New York State, only the circumstances surrounding the offense emerged as an important predictor in Ontario.

Clearing Murders Is It about Time

This study uses data from the National Incident-Based Reporting System (NIBRS) to explore the impact of model selection on determining the association of victim-level and incident-level factors to the likelihood of homicide clearance. We compare both traditional operationalizations of clearance rates as well as the time to clearance as dependent variables in examinations of correlates of solvability in homicide cases. Using a different approach than most other analyses of this problem, the results affirm the consistency of some effects but also reveal some important differences when the aspect of time is factored into the model. Implications for analyses of efficiency and effectiveness of police response to homicide, cold-case analyses, and other strategies for solving crime are discussed.

The Application of Missing Data Estimation Models to the Problem of Unknown Victim/Offender Relationships in Homicide Cases

Homicide cases suffer from substantial levels of missing data, a problem largely ignored by criminological researchers. The present research seeks to address this problem by imputing values for unknown victim/offender relationships using the EM algorithm. The analysis is carried out first using homicide data from the Los Angeles Police Department (1994-1998), and then compared with imputations using homicide data for Chicago (1991-1995), using a variety of predictor variables to assess the extent to which they influence the assignment of cases to the various relationship categories. The findings indicate that, contrary to popular belief, many of the unknown cases likely involve intimate partners, other family, and friends/acquaintances. However, they disproportionately involve strangers. Yet even after imputations, stranger homicides do not increase more than approximately 5%. The paper addresses the issue of whether data on victim/offender relationships can be considered missing at random (MAR), and the im-plications of the current findings for both existing and future research on homicide.

Missing Data in Homicide Research

This article is an introduction to the special issue of Homicide Studies on missing data. The first section is an overview of the status of missing data approaches in homicide research. It begins by describing the importance of missing data estimation in homicide. This is followed by a discussion of missing data mechanisms, complete case analysis, imputation and weighting, and model-based procedures. The second section is a brief description of each of the articles in this issue. The conclusion describes the myth associated with imputing missing data, the use of missing data approaches in public records, the Supreme Court case that found hot-deck imputation acceptable for the census, and guidelines for handling missing data published by the American Psychological Association. This section concludes by describing the kinds of research that need to be done.

Crowding in Context : An Examination of the Differential Responses of Men and Women to High-Density Living Environments

This study examines the question of gender-equivalent outcomes of mental health and social behavior in the context of crowding stress. It tests the hypothesis that gender will influence the exhibition of stress outcomes resulting from exposure to high-density living environments, with women displaying internalized responses and men responding with externalized styles. Expanding on the types of gender-appropriate disorders examined in this area of research, I selected depression, aggression, and withdrawal as gender-specific disorders based on theory and prior research. Multilevel analyses of data from a survey of Toronto residents indicate that, while the effects of household density are conditioned by gender, support for the existence of gender-equivalent outcomes is mixed. While women living in crowded homes are more likely to be depressed, men exposed to high-density living environments do not report increased aggression. However, men report higher levels of withdrawal, and some males respond with both aggression and withdrawal.

Homicides Clearances an Analysis of Arrest Versus Exceptional Outcomes

A number of studies in the homicide clearance literature combine arrest and exceptional clearances into a single category. This study addresses the question of whether these divergent homicide case outcomes are influenced differently by various aspects of the case. Using National Incident-Based Reporting System data on homicides from 1996 to 2002, the authors analyze logistic regression models of cases cleared by arrest and exceptionally cleared. Our results show that although certain factors have similar influences on both arrest and exceptional clearances, victim gender, offender race, weapon use, victim/offender relationship, and circumstances have differing impacts on case outcomes. The findings challenge recent research findings on clearances suggesting that exceptional clearances are almost solely politically motivated, and implications for measuring clearance are discussed.

Beyond the Social Production of Homicide Rates: Extending Social Disorganization Theory to Explain Homicide Case Outcomes

This paper examines the intersection of social disorganization at a community level with responses to crime. In contrast to other works examining the impact of social disorganization on the production of crime rates, we examine the role of social disorganization theory in responses to crime rates (i.e. the arrest and conviction of perpetrators of crime). In an effort to examine these dynamics, we use law enforcement data from Cleveland, Ohio to explore the role of social disorganization in the ability of police and the courts to respond to homicide cases. Such an examination suggests not only how far the law extends in community responses to homicide but also reveals an extension of social disorganization theory beyond its established role in explaining the production of crime rates.

The Impact of Density: The Importance of Nonlinearity and Selection on Flight and Fight Responses

Unlike commonsense notions and the findings from animal research, the literature concerning the effects of density on human social behavior is paralyzed by contradictory findings. This article examines empirically two fundamental issues which could account for this and which are central to the density-crowding debate: (1) whether observed crowding effects are the result of causation or selection and (2) whether individuals are negatively affected by both low and high levels of density. Data from the Toronto Mental Health and Stress study are analyzed using structural equation modeling to investigate these questions. The results support the notion that the effects of density on aggressive and withdrawn behavior are nonlinear in nature. The findings further reveal a self-selection of respondents into particular forms of housing. The implications of these findings for future research on crowding are discussed.

Taking on the Unknown: A Qualitative Comparative Analysis of Unknown Relationship Homicides

Aside from noting the dramatic rise in their numbers, homicides with unknown victim/offender relationships have attracted little research attention. This study uses Qualitative Comparative Analysis and data from the Supplementary Homicide Reports for 1976 through 1998 to examine the nature of unknown relationship homicides and changes in their structure over time. The findings indicate that a large number of unknown relationship cases are contained within a few prevalent homicide situations while also occurring in a diverse array of less common situations. The situational context of unknown homicides exhibits considerable change over time, shifting from the killing of older White males with a variety of weapons to killings involving young Black males with guns. Although unknown and stranger homicides frequently share common structures, they demonstrate notable differences as well, suggesting that unknown relationships cannot automatically be assumed to involve strangers. Implications of the findings for policy and future research are discussed.

Impact of Employment, Family Structure, and Income on NIBRS Offense, Victim, Offender, and Arrest Rates

In some studies of urban crime, offense, arrest, and victimization counts have been used as if they were interchangeable. The National Incident-Based Reporting System (NIBRS), with its provision of offense, victim, offender, and arrest counts lets us avoid this ambiguity and examine the relationship of social and economic factors to specific crime measures. Our basic question in this study was, “Does it matter whether we focus on victims or offenders when we examine and interpret the correlates of violent crime?” Using NIBRS 2002–2004 robbery and murder counts and census 2000 data for 166 cities, we examined the importance of male employment, income, racial composition, and family structure for an “offense known” measure, a victim measure, an offender measure, and two arrest measures of crime. Our results indicate that for race-specific measures even the best murder or robbery victim rate is a poor substitute for an offender rate, and offense-known measures are even poorer measures of offending. The NIBRS offender rate is the most logical and useful offender measure because it provides a direct indication of the age, race, and sex of most offenders whether or not an arrest occurs. However, arrest rates, and modified arrest rates in particular, provide reasonably close approximations of offender rates. In addition, and unexpectedly, we found that race-specific victim and offender counts and rates take much of the mystery out of the frequently used and variously interpreted variable “percent black.”