Journal of Quantitative Criminology 

About: Journal of Quantitative Criminology is an academic journal published by Springer Science+Business Media. The journal publishes majorly in the area(s): Poison control & Juvenile delinquency. It has an ISSN identifier of 0748-4518. Over the lifetime, 935 publications have been published receiving 53724 citations.

Poisson-Based Regression Analysis of Aggregate Crime Rates

Abstract: This article introduces the use of regression models based on the Poisson distribution as a tool for resolving common problems in analyzing aggregate crime rates. When the population size of an aggregate unit is small relative to the offense rate, crime rates must be computed from a small number of offenses. Such data are ill-suited to least-squares analysis. Poisson-based regression models of counts of offenses are preferable because they are built on assumptions about error distributions that are consistent with the nature of event counts. A simple elaboration transforms the Poisson model of offense counts to a model of per capita offense rates. To demonstrate the use and advantages of this method, this article presents analyses of juvenile arrest rates for robbery in 264 nonmetropolitan counties in four states. The negative binomial variant of Poisson regression effectively resolved difficulties that arise in ordinary least-squares analyses.

Reassessing the reliability and validity of self-report delinquency measures

Abstract: Several issues related to the reliability and validity of self-report delinquency measures are raised and discussed. These include problems associated with the use of internal consistency as the measure of reliability, the level of reliability or precision required for different types of analyses, problems with the content validity of self-report measures, problems of overreporting and underreporting, problems with the use of official records as a validity check on self-reports, and the lack of any good criterion as a major obstacle in assessing the empirical validity of self-report measures. In the light of these problems, some cautions about the use of self-report measures are made.

The Monetary Value of Saving a High-Risk Youth

Abstract: Programs targeted at high-risk youth are designed to prevent high-school dropout, crime, drug abuse, and other forms of delinquency. Even if shown to be successful in reducing one or more social ill, a key policy question is whether the cost to society from that intervention program exceeds its benefits. Although the costs of intervention programs are often available, the benefits are more illusive. This paper provides estimates of the potential benefits from "saving" a high-risk youth, by estimating the lifetime costs associated with the typical career criminal, drug abuser, and high-school dropout. In the absence of controlled experimental data on the number of career criminals averted, one can ask the reverse question—How many career criminals must be prevented before the program "pays for itself?" Based on a 2% discount rate, the typical career criminal causes $1.3$1.5 million in external costs; a heavy drug user, $370,000 to $970,000; and a high-school dropout, $243,000 to $388,000. Eliminating duplication between crimes committed by individuals who are both heavy drug users and career criminals results in an overall estimate of the "monetary value of saving a high-risk youth" of $1.7 to $2.3 million.

School-Based Prevention of Problem Behaviors: A Meta-Analysis

Abstract: This study examines the features of effective school-based prevention of crime, substance use, dropout/nonattendance, and other conduct problems. It summarizes, using meta-analytic techniques, results from 165 studies of school-based prevention activities that ranged from individual counseling or behavior modification programs through efforts to change the way schools are managed. The results highlight several inadequacies in the existing research for guiding policy and practice, the most notable of which is that many popular school-based prevention approaches have not been well studied to date. The study shows, however, that school-based prevention practices appear to be effective in reducing alcohol and drug use, dropout and nonattendance, and other conduct problems. The size of the average effect for each of the four outcomes was small and there was considerable heterogeneity across studies in the magnitude of effects, even within program type after adjusting for measured method and population differences. Non-cognitive-behavioral counseling, social work, and other therapeutic interventions show consistently negative effects, whereas self-control or social competency promotion instruction that makes use of cognitive-behavioral and behavioral instructional methods show consistently positive effects. Also effective are noninstructional cognitive-behavioral and behavioral methods programs. Environmentally focused interventions appear to be particularly effective for reducing delinquency and drug use.

Is the Magic Still There? The Use of the Heckman Two-Step Correction for Selection Bias in Criminology

Abstract: Issues of selection bias pervade criminological research. Despite their ubiquity, considerable confusion surrounds various approaches for addressing sample selection. The most common approach for dealing with selection bias in criminology remains Heckman’s [(1976) Ann Econ Social Measure 5:475–492] two-step correction. This technique has often been misapplied in criminological research. This paper highlights some common problems with its application, including its use with dichotomous dependent variables, difficulties with calculating the hazard rate, misestimated standard error estimates, and collinearity between the correction term and other regressors in the substantive model of interest. We also discuss the fundamental importance of exclusion restrictions, or theoretically determined variables that affect selection but not the substantive problem of interest. Standard statistical software can readily address some of these common errors, but the real problem with selection bias is substantive, not technical. Any correction for selection bias requires that the researcher understand the source and magnitude of the bias. To illustrate this, we apply a diagnostic technique by Stolzenberg and Relles [(1997) Am Sociol Rev 62:494–507] to help develop intuition about selection bias in the context of criminal sentencing research. Our investigation suggests that while Heckman’s two-step correction can be an appropriate technique for addressing this bias, it is not a magic solution to the problem. Thoughtful consideration is therefore needed before employing this common but overused technique.