Opposite Trends in the Regulation of Pornography? Policy Differentiation and Policy Convergence Across 26 Countries Between 1960 and 2010

In recent decades, the regulation of pornography has been confronted with challenges emerging from cultural change, economic interests, and technological progress. As a result, the respective regulatory frameworks have changed substantially in many countries. These changes have been accompanied by fierce political struggles and societal value conflicts. However, there are few comparative studies on the reactions of national governments to these problems. In this article, we present new empirical data on the regulation of pornography in 26 countries between 1960 and 2010. To assess regulatory change, we rely on a new measurement approach that considers the extent to which governments intervene into individual freedoms and the degree to which noncompliance with these rules is actually sanctioned. Our analysis reveals a trend toward more permissive styles of pornography regulation. However, this trend is accompanied by growing regulatory specialization and a convergence toward more interventionist regimes for special types of pornography.     

A generalized analytic solution to the win ratio to analyze a composite endpoint considering the clinical importance order among components

A composite endpoint consists of multiple endpoints combined in one outcome. It is frequently used as the primary endpoint in randomized clinical trials. There are two main disadvantages associated with the use of composite endpoints: a) in conventional analyses, all components are treated equally important; and b) in time‐to‐event analyses, the first event considered may not be the most important component. Recently Pocock et al. (2012) introduced the win ratio method to address these disadvantages. This method has two alternative approaches: the matched pair approach and the unmatched pair approach. In the unmatched pair approach, the confidence interval is constructed based on bootstrap resampling, and the hypothesis testing is based on the non‐parametric method by Finkelstein and Schoenfeld (1999). Luo et al. (2015) developed a close‐form variance estimator of the win ratio for the unmatched pair approach, based on a composite endpoint with two components and a specific algorithm determining winners, losers and ties. We extend the unmatched pair approach to provide a generalized analytical solution to both hypothesis testing and confidence interval construction for the win ratio, based on its logarithmic asymptotic distribution. This asymptotic distribution is derived via U‐statistics following Wei and Johnson (1985). We perform simulations assessing the confidence intervals constructed based on our approach versus those per the bootstrap resampling and per Luo et al. We have also applied our approach to a liver transplant Phase III study. This application and the simulation studies show that the win ratio can be a better statistical measure than the odds ratio when the importance order among components matters; and the method per our approach and that by Luo et al., although derived based on large sample theory, are not limited to a large sample, but are also good for relatively small sample sizes. Different from Pocock et al. and Luo et al., our approach is a generalized analytical method, which is valid for any algorithm determining winners, losers and ties. Copyright © 2016 John Wiley & Sons, Ltd.     

Considering the shareholder perspective: value-based management systems and stock market performance

We empirically study the use of value-based management systems in listed German firms and examine implications for firms’ stock market performance. Using a novel, hand-collected data set covering 1,083 firm years from 2002 to 2008, we find that value-based management systems become increasingly common. Specifically, in 2008 42% of our sample firms have implemented such a system. In the empirical analysis, we find that firms implementing value-based management systems earn both statistically significant and economically substantial abnormal stock market returns measured within a 2-year adoption phase. These excess returns are not jeopardized by poor post-adoption returns. In the analysis, we carefully control for risk and account for endogeneity concerns. Overall, our findings support the view that shareholders consider the adoption of a value-based management system as a credible signal that management will focus on shareholder interests and that such systems actually increase shareholder value.     

Practices of Dual Earner Couples Successfully Balancing Work and Family

Researchers have long explored conflict and strain in dual-career couples. Recently, the focus has begun to shift toward documenting the adaptive strategies of dual-earner couples in balancing family and work. The current study investigates workplace practices perceived as supportive in balancing work and family. Respondents were middle-class, dual-earner couples (N=47) who described themselves as successful in balancing family and work. These supportive practices include: flexible work scheduling, non-traditional work hours, professional/job autonomy, working from home, supportive supervisors, supportive colleagues and supervisees, and the ability to set firm boundaries around work. Additionally, many participants describe their efforts to actively secure employment at workplaces that offered family–friendly alternatives, and describe the tradeoffs they are willing to make.     

A model company

HUGIN Expert is a small company writing software that can be used to create expert systems, using probability in the guise of graphical models. Steffen Lauritzen describes his part in the genesis and development of the company.     

High dimensional multivariate mixed models for binary questionnaire data

Summary.  Questionnaires that are used to measure the effect of an intervention often consist of different sets of items, each set possibly measuring another concept. Mixed models with set-specific random effects are a flexible tool to model the different sets of items jointly. However, computational problems typically arise as the number of sets increases. This is especially true when the random-effects distribution cannot be integrated out analytically, as with mixed models for binary data. A pairwise modelling strategy, in which all possible bivariate mixed models are fitted and where inference follows from pseudolikelihood theory, has been proposed as a solution. This approach has been applied to assess the effect of physical activity on psychocognitive functioning, the latter measured by a battery of questionnaires.