Demographic Comparison of American Individuals in Polyamorous and Monogamous Relationships

Research on polyamorous relationships has increased substantially over the past decade. This work has documented how polyamory is practiced and why individuals might pursue such arrangements. However, there is a lack of a systematic investigation of who is in polyamorous relationships and how they might differ from individuals in monogamous relationships. The present study is one of the first to address this by comparing the demographic backgrounds of individuals in polyamorous (N = 2,428) and monogamous (N = 539) relationships in the United States. Compared to participants in monogamous relationships, those in polyamorous relationships were more likely to report minority sexual identities. Despite similar age distributions, individuals in polyamorous relationships were more likely to report being in a civil union, being divorced, and earning less than $40,000 per year compared to individuals in monogamous relationships. People in polyamorous relationships were also more likely to select “other” options for most demographic characteristics, suggesting that they tend to choose less traditional response options in general. The current research highlights several demographic differences that need to be considered and potentially controlled for in future comparisons of polyamorous and monogamous relationships.     

THE DUALITY DIAGRAM IN DATA ANALYSIS: EXAMPLES OF MODERN APPLICATIONS

Today's data-heavy research environment requires the integration of different sources of information into structured datasets that can not be analyzed as simple matrices. We introduce an old technique, known in the European data analyses circles as the Duality Diagram Approach, put to new uses through the use of a variety of metrics and ways of combining different diagrams together. This issue of the Annals of Applied Statistics contains contemporary examples of how this approach provides solutions to hard problems in data integration. We present here the genesis of the technique and how it can be seen as a precursor of the modern kernel based approaches.     

The Mediating Effect of Resilience Between Social Support for Exercise and Resident Satisfaction in Assisted Living

This study examined whether residents' level of resilience mediated the relationship between social support for exercise from staff and resident satisfaction in assisted living. This was a secondary data analysis using baseline data from a function-focused care intervention study including 171 residents from four assisted living facilities. Using structural equation modeling, we found that mood and social support for exercise from staff were the only variables associated with resilience. Mood, gender, cognition, and social support for exercise from staff directly influenced resident satisfaction and explained 31% of the variance in the model. Implications for future research and practice are discussed.     

Using relative utility curves to evaluate risk prediction

Summary.  Because many medical decisions are based on risk prediction models that are constructed from medical history and results of tests, the evaluation of these prediction models is important. This paper makes five contributions to this evaluation: the relative utility curve which gauges the potential for better prediction in terms of utilities, without the need for a reference level for one utility, while providing a sensitivity analysis for misspecification of utilities, the relevant region, which is the set of values of prediction performance that are consistent with the recommended treatment status in the absence of prediction, the test threshold, which is the minimum number of tests that would be traded for a true positive prediction in order for the expected utility to be non-negative, the evaluation of two-stage predictions that reduce test costs and connections between various measures of performance of prediction. An application involving the risk of cardiovascular disease is discussed.     

Corporate Reputation and Women on the Board

In this paper, we investigate the determinants of corporate reputation, derived from the assessments of managers and market analysts, of a sample of large UK firms. Along with the influences of a variety of firm attributes, we find a reputational effect associated with a female presence at board level. This effect varies across sectors and demonstrates the influence of a firm's stakeholder environment in determining whether a female presence on the board enhances or harms the reputation of the firm. The pattern that emerges indicates that the presence of women on the board is favourably viewed in only those sectors that operate close to final consumers. We argue that the nature of this effect reflects an imperative for equality of representation that highlights the need to reflect gender diversity among customers.     

Bayesian Nonparametric Hidden Markov Models with application to the analysis of copy-number-variation in mammalian genomes

We consider the development of Bayesian Nonparametric methods for product partition models such as Hidden Markov Models and change point models. Our approach uses a Mixture of Dirichlet Process (MDP) model for the unknown sampling distribution (likelihood) for the observations arising in each state and a computationally efficient data augmentation scheme to aid inference. The method uses novel MCMC methodology which combines recent retrospective sampling methods with the use of slice sampler variables. The methodology is computationally efficient, both in terms of MCMC mixing properties, and robustness to the length of the time series being investigated. Moreover, the method is easy to implement requiring little or no user-interaction. We apply our methodology to the analysis of genomic copy number variation.