Minority government and marginal members: new issues for political and policy legitimacy in Australia

A steady decline in major party support in Commonwealth nations has resulted in changing parliamentary compositions, including the growing prevalence of minority government. Such situations pose new questions for notions of government legitimacy within Westminster systems. For instance, is negotiation with cross-benchers an example of government illegitimacy? What is the legitimate role of non-ministerial members when the composition of parliament gives them the final say on the enabling legislation for public policy? What is the legitimate response of the public sector regarding policy-making in the context of minority government? In this paper, we reflect on how a ‘marginal member’ concept can provide new insights into such issues and their implications.     

Adolescent Online Gambling in Cyprus: Associated School Performance and Psychopathology

This paper presents results from the study of gambling behaviors in a representative sample of Cypriot high-school students. The aim of the study was to ascertain epidemiology of adolescent online gambling in Cyprus and possible correlates. The sample consisted of 2,684 students (48.5 % boys, 51.5 % girls) from the first grades of junior (Gymnasium) and senior (Lyceum) high school. Our results indicate that gamblers presented with lower school achievement and related expectations while scoring consistently higher on measures of Internet addiction, parental bonding and psychopathology. Discriminant analysis revealed two profiles which explained the most variance in gambling behavior; the first profile that corresponded to more explained variance was the student with higher psychopathology, less prosocial behavior, higher Internet addiction score with higher frequencies of online activities and moderate levels of truancy and lower expectation of school achievement. The second profile was that of a student who reported less psychopathology, more prosocial behavior, less involvement with the Internet in general but skipped classes more and his prospects on finishing high school were even slimmer. These results will be utilized in the design of a comprehensive prevention program in an effort to combat online addictive behaviors.     

Minority Stress and Stress Proliferation Among Same‐Sex and Other Marginalized Couples

Drawing from 2 largely isolated approaches to the study of social stress—stress proliferation and minority stress—the authors theorize about stress and mental health among same‐sex couples. With this integrated stress framework, they hypothesized that couple‐level minority stressors may be experienced by individual partners and jointly by couples as a result of the stigmatized status of their same‐sex relationship—a novel concept. They also consider dyadic minority stress processes, which result from the relational experience of individual‐level minority stressors between partners. Because this framework includes stressors emanating from both status‐based (e.g., sexual minority) and role‐based (e.g., partner) stress domains, it facilitates the study of stress proliferation linking minority stress (e.g., discrimination), more commonly experienced relational stress (e.g., conflict), and mental health. This framework can be applied to the study of stress and health among other marginalized couples, such as interracial/ethnic, interfaith, and age‐discrepant couples.     

Generalized Sobol sensitivity indices for dependent variables: numerical methods

The hierarchically orthogonal functional decomposition of any measurable function η of a random vector X=(X₁,?…?, X_p) consists in decomposing η(X) into a sum of increasing dimension functions depending only on a subvector of X. Even when X₁,?…?, X_p are assumed to be dependent, this decomposition is unique if the components are hierarchically orthogonal. That is, two of the components are orthogonal whenever all the variables involved in one of the summands are a subset of the variables involved in the other. Setting Y=η(X), this decomposition leads to the definition of generalized sensitivity indices able to quantify the uncertainty of Y due to each dependent input in X [Chastaing G, Gamboa F, Prieur C. Generalized Hoeffding–Sobol decomposition for dependent variables – application to sensitivity analysis. Electron J Statist. 2012;6:2420–2448]. In this paper, a numerical method is developed to identify the component functions of the decomposition using the hierarchical orthogonality property. Furthermore, the asymptotic properties of the components estimation is studied, as well as the numerical estimation of the generalized sensitivity indices of a toy model. Lastly, the method is applied to a model arising from a real-world problem.     

Variable selection in partial linear regression with functional covariate

The problem of variable selection is considered in high-dimensional partial linear regression under some model allowing for possibly functional variable. The procedure studied is that of nonconcave-penalized least squares. It is shown the existence of a √n/s_n-consistent estimator for the vector of p_n linear parameters in the model, even when p_n tends to ∞ as the sample size n increases (s_n denotes the number of influential variables). An oracle property is also obtained for the variable selection method, and the nonparametric rate of convergence is stated for the estimator of the nonlinear functional component of the model. Finally, a simulation study illustrates the finite sample size performance of our procedure.     

Evaluation of program success for programs with multiple trials in binary outcomes

A late‐stage clinical development program typically contains multiple trials. Conventionally, the program's success or failure may not be known until the completion of all trials. Nowadays, interim analyses are often used to allow evaluation for early success and/or futility for each individual study by calculating conditional power, predictive power and other indexes. It presents a good opportunity for us to estimate the probability of program success (POPS) for the entire clinical development earlier. The sponsor may abandon the program early if the estimated POPS is very low and therefore permit resource savings and reallocation to other products. We provide a method to calculate probability of success (POS) at an individual study level and also POPS for clinical programs with multiple trials in binary outcomes. Methods for calculating variation and confidence measures of POS and POPS and timing for interim analysis will be discussed and evaluated through simulations. We also illustrate our approaches on historical data retrospectively from a completed clinical program for depression. Copyright © 2015 John Wiley & Sons, Ltd.     

A Bayesian estimate of the concordance correlation coefficient with skewed data

Concordance correlation coefficient (CCC) is one of the most popular scaled indices used to evaluate agreement. Most commonly, it is used under the assumption that data is normally distributed. This assumption, however, does not apply to skewed data sets. While methods for the estimation of the CCC of skewed data sets have been introduced and studied, the Bayesian approach and its comparison with the previous methods has been lacking. In this study, we propose a Bayesian method for the estimation of the CCC of skewed data sets and compare it with the best method previously investigated. The proposed method has certain advantages. It tends to outperform the best method studied before when the variation of the data is mainly from the random subject effect instead of error. Furthermore, it allows for greater flexibility in application by enabling incorporation of missing data, confounding covariates, and replications, which was not considered previously. The superiority of this new approach is demonstrated using simulation as well as real‐life biomarker data sets used in an electroencephalography clinical study. The implementation of the Bayesian method is accessible through the Comprehensive R Archive Network. Copyright © 2015 John Wiley & Sons, Ltd.