Child custody issues and co‐occurrence of intimate partner violence and child maltreatment: controversies and points of agreement amongst practitioners

The situation of families undergoing separation in a context of co‐occurrence of intimate partner violence (IPV) and child maltreatment raises certain issues related to child custody. The results presented in this paper were collected and analysed within the framework of a qualitative study aiming to identify the principal points of agreement and the main controversies amongst practitioners in several different types of organizations. Focus groups were held with a total of 43 practitioners from six different settings concerned with child custody in cases of co‐occurrence of IPV and child maltreatment. Although they agreed on the importance of ensuring the safety of victims of violence, their views diverged on three points: (1) the importance of preserving the father–child relationship; (2) collaboration between voluntary organizations and semi‐voluntary or legal agencies; and (3) consideration of cultural differences.     

It Takes Two to Fight in School,Too: A Social Relations Model of the Psychometric Properties and Relative Variance of Dyadic Aggression and Victimization in Middle School

Aggressive behavior has been well studied in terms of interindividual differences among aggressors and victims, but has been understudied, especially within naturalistic contexts, in terms of aggressor–victim relationships. The social relations model (SRM) is a powerful conceptual and analytic tool for studying dyadic phenomena, and we describe the use of multivariate SRM to study aggression. Boys and girls (N = 210) in middle schools (sixth and seventh grades) completed a newly created dyadic aggression and victimization inventory (DAVI). Results support the reliability and validity of the DAVI in assessing inter‐individual and inter‐dyadic differences in aggression and victimization. Occurrences of aggression were accounted for primarily by inter‐dyadic variability, indicating the importance of considering aggressor–victim relationships. We discuss the implications of this relationship focus for future research and intervention efforts.     

The exponential distribution analog of the Grubbs–Weaver method

Abstract

Grubbs and Weaver (1947 Grubbs, F. E., and C. L. Weaver. 1947. The best unbiased estimate of population standard deviation based on group ranges. Journal of the American Statistical Association 42 (238):224–41. doi: 10.2307/2280652.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) suggest a minimum-variance unbiased estimator for the population standard deviation of a normal random variable, where a random sample is drawn and a weighted sum of the ranges of subsamples is calculated. The optimal choice involves using as many subsamples of size eight as possible. They verified their results numerically for samples of size up to 100, and conjectured that their “rule of eights” is valid for all sample sizes. Here we examine the analogous problem where the underlying distribution is exponential and find that a “rule of fours” yields optimality and prove the result rigorously.     

20 years of Bologna - a story of success,a story of failure

The Bologna Process is a unique harmonisation process taking place outside the policy-making framework of the European Union. It aims at enhancing the comparability and compatibility of higher education structures and degrees across Europe, as well as to institutionalise quality assurance mechanisms. The aim of this article is to provide a condensed, up-to-date overview of the Bologna Process with regard to structural characteristics, before embedding it into a discussion on processes on voluntary policy convergence and to which extent we should be able to find this kind of policy harmonisation in the realm of the Bologna Process. Related to this are questions why this, in principle, completely voluntary process of policy harmonisation, has appealed to so many countries and why they might or might not feel committed to the implementation of its policies and tools.     

Con Job: An Estimate of Ex‐Felon Voter Turnout Using Document‐Based Data*

Objective. Ex‐felon voter turnout was estimated for the first time using government records rather than statistical models. Statistical models have estimated that 25–35 percent of eligible ex‐felons would vote in federal elections. Methods. Six‐hundred‐sixty recently released ex‐felons in Erie County, NY, who would have been legally eligible to register and vote in 2004 or 2005, were compared with data from the Erie County Board of Elections to determine whether they registered and voted in either 2004 or 2005. Results. Five percent this population of ex‐felons voted in either 2004 or 2005. Conclusions. Single‐digit turnout among ex‐felons raises questions about the assumptions underlying statistical estimates, and it also suggests that elections would have to be very close for ex‐felons to have an impact on the results.     

Inference in Semi‐Parametric Dynamic Models for Repeated Count Data

This paper deals with a longitudinal semi‐parametric regression model in a generalised linear model setup for repeated count data collected from a large number of independent individuals. To accommodate the longitudinal correlations, we consider a dynamic model for repeated counts which has decaying auto‐correlations as the time lag increases between the repeated responses. The semi‐parametric regression function involved in the model contains a specified regression function in some suitable time‐dependent covariates and a non‐parametric function in some other time‐dependent covariates. As far as the inference is concerned, because the non‐parametric function is of secondary interest, we estimate this function consistently using the independence assumption‐based well‐known quasi‐likelihood approach. Next, the proposed longitudinal correlation structure and the estimate of the non‐parametric function are used to develop a semi‐parametric generalised quasi‐likelihood approach for consistent and efficient estimation of the regression effects in the parametric regression function. The finite sample performance of the proposed estimation approach is examined through an intensive simulation study based on both large and small samples. Both balanced and unbalanced cluster sizes are incorporated in the simulation study. The asymptotic performances of the estimators are given. The estimation methodology is illustrated by reanalysing the well‐known health care utilisation data consisting of counts of yearly visits to a physician by 180 individuals for four years and several important primary and secondary covariates.