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Since its introduction, social support theory has received generally consistent empirical support. Tests of social support theory have, however, mostly been cross-sectional and restricted to U.S. and Western European analyses. Measures of social support have tended to be inconsistent across studies and narrowly operationalized. The present project offers a longitudinal test of Cullen's (1994) social support theory using a more broadly defined measure of social support that is comparable across both Eastern and Western European countries. Using data gathered by Eurostat, this study applies 'hybrid' regression panel analysis to test the effects of social support on homicide rates across European regions for 2000, 2005 and 2009. Results provide evidence for an effect of social support on homicide between Western and Eastern European regions and within those regions over time. The analyses also indicate that social support moderates the effect of economic deprivation on homicide across Western European regions, though not Eastern European regions. Adapted from the source document.

This research examines the differential effects of structural conditions on race‐specific victim and offender homicide rates in large U.S. cities in 1990. While structural theories of race relations and criminological explanations are reviewed, particular attention is given to those structural theories that highlight racial competition, economic and labor market opportunity, and racial segregation as essential for an examination of racially disaggregated homicide offending. The effects of these and other structural conditions are estimated for four racially distinct homicide offending models—black intraracial, white intraracial, black interracial, and white interracial homicides. The results suggest that the structural conditions that lead to race‐specific victim and offender homicide rates differ significantly among the four models. Economic deprivation and local opportunity structures are found to influence significantly the rates of intraracial homicide offending, while racial inequality contributes solely to black interracial homicide rates. In addition, our findings indicate that blacks and whites face different economic and social realities related to economic deprivation and social isolation. The differential impact of these structural conditions and other labor market factors are discussed.

Rubin (1977) developed a method for estimating, in a subjective sense, the effect of nonignorable nonresponse in sample surveys. Based on Bayesian techniques, this method produces a subjective probability interval for the statistic, such as the mean of a response variable, that would have been calculated if all nonrespondents had responded. Demographic and socioeconomic background information that is recorded for both respondents and nonrespondents plays an important role in sharpening the subjective interval - through the adjustment of a regression equation that uses this information. In this article, Rubin's method-sometimes called the mixture modeling approach to drawing inferences from self-selected samples-is reviewed and applied to real survey and experimental data on community standards for sexually explicit material in which respondents were asked to judge the material's appeal to prurient interest and patent offensiveness (two of the three legal criteria for a determination of obscenity). A critically important substantive issue in this context is whether or not the sample self-selection processes governing the willingness of individuals to participate in the experiment have so truncated the frequency distributions of participant judgments about obscenity that they are grossly biased and inaccurate. It is shown how the mixture modeling approach sheds light on the possible extent of such biases.

There has been increasing effort devoted to examining the linkages between urban disadvantage and race-specifi c violence in the sociological literature. Much of this literature has either focused on identifying the consequences of urban disadvantage on different racial groups, particularly as it relates to offending rates, or documenting the impact of labor market factors on intra-racial and inter-racial violence. While this literature advances our understanding of the interconnections between race, economic disadvantage and violence in the urban context, our exploration into this literature has only begun. In this paper, we outline the contributions of the racial stratifi cation literature to the study of urban violence and argue that this literature plays an essential role in moving the study of race and urban violence forward. We offer ways (avenues) to incorporate the racial competition and exploitation literature into the study of violence within and between racial groups. In doing so, we emphasize the importance of "process" by delineating the interconnections between labor market exploitation, competition, and violence.

Draws on official suicide & census data to examine the effects of religion & divorce on suicide rates for 294 metropolitan areas in 1980. The role of Catholic church membership has both direct & indirect effects on suicide rates; the indirect effects are mediated through the divorce rate. In contrast, Protestant church membership is not related statistically to suicide. Although total church membership is negatively related to suicide, denominational effects remain important. 3 Tables, 56 References. Adapted from the source document.

Previous methodological research has shown that hidden heterogeneity in hazard rate regression models—in the form of systematic differences between sample members in the risk or hazard of making a transition due to unobserved variables not accounted for by the measured covariates—can produce biased parameter estimates and erroneous inferences. However, few empirical applications of hazard regression do more than pay lip service to the complications of hidden heterogeneity. In part, this is due to the relative inaccessibility of the mathematical apparatus of continuous-time hazard regression methodology with flexible nonparametric specifications on the hidden heterogeneity. This article presents new methods for incorporating nonparametric specifications of hidden heterogeneity into hazard regressions by developing discrete-time Poisson rate/complementary log-log hazard regression models with nonparametric hidden heterogeneity that are analogous to the continuous-time models of Heckman and Singer. Maximum-likelihood estimators and associated hypothesis tests are described. An empirical application to data on criminal careers, which illustrates the utility of models that explicitly incorporate hidden heterogeneity, is presented.

Specifications and moment properties of the univariate Poisson and negative binomial distributions are briefly reviewed and illustrated. Properties and limitations of the corresponding poisson and negative binomial (gamma mixtures of Poissons) regression models are described. It is shown how a misspecification of the mixing distribution of a mixed Poisson model to accommodate hidden heterogeneity ascribable to unobserved variables—although not affecting the consistency of maximum likelihood estimators of the Poisson mean rate parameter or its regression parameterization—can lead to inflated t ratios of regression coefficients and associated incorrect inferences. Then the recently developed semiparametric maximum likelihood estimator for regression models composed of arbitrary mixtures of Poisson processes is specified and further developed. It is concluded that the semiparametric mixed Poisson regression model adds considerable flexibility to Poisson-family regression models and provides opportunities for interpretation of empirical patterns not available in the conventional approaches.

This article examines and compares the advantages of employing logistic and hazards regression techniques in assessing both the overall impact of a treatment program and the extent to which the impact varies among different client subgroups. Data gathered from the North Carolina Court Counselors' Intensive Protective Supervision Project provides a context for the application of these statistical techniques to assess this program's effectiveness. This experimental project was designed topnovide intensive supervision for status offenders who are placed under the protective supervision of the juvenile courts in North Carolina. It is found that, although intensive supervision had the desired impact of reducing the probability of delinquent offenses during the early (first year and a half) phase of the project, this effect deteriorated over the full three and a half years of the experiment. In addition, the hazards regression analysis shows that youths under intensive supervtsion failed (recidivated with status or delinquent offenses) at a more rapid rate than those under regular supervision. Implications are drawn for the management and effectiveness of intensive supervision programs.

Recently, the state of North Carolina has supported a randomized experimental project designed to provide intensive supervision services for undisciplined youths (status offenders or youths referred to the courts for runaway, truant, or ungovernable behaviors) placed under the protective supervision of the juvenile courts. As compared to regular procedures for juvenile court protective supervision of status offenders, the Intensive Protective Supervision Project (IPSP) involves more extensive and proactive contact between the court counselor, the status offender, and the status offender's family. The essential idea of the IPSP is that through the intensive supervision and provision of professional services to status offenders it may be possible to decrease the rate of occurrence of additional status offenses and the likelihood that the youths will commit more serious delinquent offenses. Results from a statistical and field-based evalu ation of the IPSP experiment suggest that the project is quite successful in achieving its goals for those undisciplined youths who have not previously been charged with delinquent offenses.