Responding to teen dating violence: Perspectives from mothers who have been abused and seeking services in domestic violence shelters

ABSTRACT

Teen dating violence (TDV) is a significant public health problem, but we know little about how mothers who have been abused respond to TDV. This article analyzes qualitative data from three focus groups conducted with 17 mothers who had experienced abuse. Mothers responded to four hypothetical scenarios of their child reporting TDV to them. Mothers reported that their approach to children’s reports of TDV would entail engaging in varying levels of authoritarianism, considering the gender of the child, and exercising caution in their responses. In response to the scenarios, mothers stated that they would ask questions, educate their teens, contact the perpetrator and/or parents, share their own experiences, and call for outside help. The study’s findings may assist prevention educators working with mothers who experienced abuse in responding to their children’s disclosures of incidents of TDV.     

Joint GEEs for multivariate correlated data with incomplete binary outcomes

This study considers a fully-parametric but uncongenial multiple imputation (MI) inference to jointly analyze incomplete binary response variables observed in a correlated data settings. Multiple imputation model is specified as a fully-parametric model based on a multivariate extension of mixed-effects models. Dichotomized imputed datasets are then analyzed using joint GEE models where covariates are associated with the marginal mean of responses with response-specific regression coefficients and a Kronecker product is accommodated for cluster-specific correlation structure for a given response variable and correlation structure between multiple response variables. The validity of the proposed MI-based JGEE (MI-JGEE) approach is assessed through a Monte Carlo simulation study under different scenarios. The simulation results, which are evaluated in terms of bias, mean-squared error, and coverage rate, show that MI-JGEE has promising inferential properties even when the underlying multiple imputation is misspecified. Finally, Adolescent Alcohol Prevention Trial data are used for illustration.     

Marginal models for the association structure of hierarchical binary responses

Clustered binary responses are often found in ecological studies. Data analysis may include modeling the marginal probability response. However, when the association is the main scientific focus, modeling the correlation structure between pairs of responses is the key part of the analysis. Second-order generalized estimating equations (GEE) are established in the literature. Some of them are more efficient in computational terms, especially facing large clusters. Alternating logistic regression (ALR) and orthogonalized residual (ORTH) GEE methods are presented and compared in this paper. Simulation results show a slightly superiority of ALR over ORTH. Marginal probabilities and odds ratios are also estimated and compared in a real ecological study involving a three-level hierarchical clustering. ALR and ORTH models are useful for modeling complex association structure with large cluster sizes.     

Optimum designs for parameter estimation in a mixture experiment with two correlated responses

In this paper, we investigate a mixture problem with two responses, which are functions of the mixing proportions, and are correlated with known dispersion matrix. We obtain D- and A-optimal designs for estimating the parameters of the response functions, when none or some of the regression coefficients of the two functions are the same. It is shown that when no prior knowledge about the regression coefficients is available, the D-optimal design is independent of the dispersion matrix, while the A-optimal design depends on it, provided the response functions are of different degree. On the other hand, when some of the regression coefficients are known to be the same for both the functions, the D-optimal design depends on the dispersion matrix when the two response functions are not of the same degree.     

The demography of words: The global decline in non-numeric fertility preferences, 1993–2011

This paper examines the decline in non-numeric responses to questions about fertility preferences among women in the developing world. These types of response—such as ‘don’t know’ or ‘it’s up to God’—have often been interpreted through the lens of fertility transition theory as an indication that reproduction has not yet entered women’s ‘calculus of conscious choice’. However, this has yet to be investigated cross-nationally and over time. Using 19?years of data from 32 countries, we find that non-numeric fertility preferences decline most substantially in the early stages of a country’s fertility transition. Using country-specific and multilevel models, we explore the individual- and contextual-level characteristics associated with women’s likelihood of providing a non-numeric response to questions about their fertility preferences. Non-numeric fertility preferences are influenced by a host of social factors, with educational attainment and knowledge of contraception being the most robust and consistent predictors.     

Unruly bodies at conference

Academic conferences embody a set of prescribed regulative practices. This article considers some of the tensions that arise when these normative expectations are disrupted by unruly bodies. As scholars of disability studies we lament the lack of understanding within an ableist society that is resistant to change. In this article, however, I invite us to explore closer to home to consider how unruly bodies might enable reflection on how disability is created even within our own ‘expert’ environments. It is argued here that new ways of conceptualising and accommodating behaviour at conference are required if these are to exemplify the inclusive and welcoming spaces desired by us all.     

Inference in Targeted Group‐Sequential Covariate‐Adjusted Randomized Clinical Trials

This article is devoted to the construction and asymptotic study of adaptive, group‐sequential, covariate‐adjusted randomized clinical trials analysed through the prism of the semiparametric methodology of targeted maximum likelihood estimation. We show how to build, as the data accrue group‐sequentially, a sampling design that targets a user‐supplied optimal covariate‐adjusted design. We also show how to carry out sound statistical inference based on such an adaptive sampling scheme (therefore extending some results known in the independent and identically distributed setting only so far), and how group‐sequential testing applies on top of it. The procedure is robust (i.e. consistent even if the working model is mis‐specified). A simulation study confirms the theoretical results and validates the conjecture that the procedure may also be efficient.     

Sequential confidence intervals for the number of cells in a multinomial population

A two-sided sequential confidence interval is suggested for the number of equally probable cells in a given multinomial population with prescribed width and confidence coefficient. We establish large-sample properties of the fixed-width confidence interval procedure using a normal approximation, and some comparisons are made. In addition, a simulation study is carried out in order to investigate the finite sample behaviour of the suggested sequential interval estimation procedure.     

On Calculations Involving the Maximum Cell Frequency

We describe a method of computing the cumulative distribution function of the maximum and minimum cell frequencies in sampling distributions commonly encountered in the analysis of categorical data.The procedure is efficient for exact or approximate calculation in both homogeneous and non-homogeneous cases, is non-recursive, and does not require Dirichlet integrals.Some related statistical problems are also discussed.     

A two-sample parametric group sequential procedure for monitoring clinical trials

A group sequential procedure is presented which allows for staggered entry of patients, random loss to followup, and utilizes the flexible boundary approach of Lan and DeMets. The proposed procedure assumes that response times are nearly exponentially distributed. An example as well as simulation studies comparing the performance of the proposed procedure with the group sequential logrank are also presented.