The time‐dependent “cure‐death” model investigating two equally important endpoints simultaneously in trials treating high‐risk patients with resistant pathogens

A variety of primary endpoints are used in clinical trials treating patients with severe infectious diseases, and existing guidelines do not provide a consistent recommendation. We propose to study simultaneously two primary endpoints, cure and death, in a comprehensive multistate cure‐death model as starting point for a treatment comparison. This technique enables us to study the temporal dynamic of the patient‐relevant probability to be cured and alive. We describe and compare traditional and innovative methods suitable for a treatment comparison based on this model. Traditional analyses using risk differences focus on one prespecified timepoint only. A restricted logrank‐based test of treatment effect is sensitive to ordered categories of responses and integrates information on duration of response. The pseudo‐value regression provides a direct regression model for examination of treatment effect via difference in transition probabilities. Applied to a topical real data example and simulation scenarios, we demonstrate advantages and limitations and provide an insight into how these methods can handle different kinds of treatment imbalances. The cure‐death model provides a suitable framework to gain a better understanding of how a new treatment influences the time‐dynamic cure and death process. This might help the future planning of randomised clinical trials, sample size calculations, and data analyses.     

Nonparametric density deconvolution by weighted kernel estimators

Nonparametric density estimation in the presence of measurement error is considered. The usual kernel deconvolution estimator seeks to account for the contamination in the data by employing a modified kernel. In this paper a new approach based on a weighted kernel density estimator is proposed. Theoretical motivation is provided by the existence of a weight vector that perfectly counteracts the bias in density estimation without generating an excessive increase in variance. In practice a data driven method of weight selection is required. Our strategy is to minimize the discrepancy between a standard kernel estimate from the contaminated data on the one hand, and the convolution of the weighted deconvolution estimate with the measurement error density on the other hand. We consider a direct implementation of this approach, in which the weights are optimized subject to sum and non-negativity constraints, and a regularized version in which the objective function includes a ridge-type penalty. Numerical tests suggest that the weighted kernel estimation can lead to tangible improvements in performance over the usual kernel deconvolution estimator. Furthermore, weighted kernel estimates are free from the problem of negative estimation in the tails that can occur when using modified kernels. The weighted kernel approach generalizes to the case of multivariate deconvolution density estimation in a very straightforward manner.     

On pseudo-values for regression analysis in competing risks models

For regression on state and transition probabilities in multi-state models Andersen et al. (Biometrika 90:15–27, 2003) propose a technique based on jackknife pseudo-values. In this article we analyze the pseudo-values suggested for competing risks models and prove some conjectures regarding their asymptotics (Klein and Andersen, Biometrics 61:223–229, 2005). The key is a second order von Mises expansion of the Aalen-Johansen estimator which yields an appropriate representation of the pseudo-values. The method is illustrated with data from a clinical study on total joint replacement. In the application we consider for comparison the estimates obtained with the Fine and Gray approach (J Am Stat Assoc 94:496–509, 1999) and also time-dependent solutions of pseudo-value regression equations.     

Comment: there may be compositional effects,but they do not work that way*

This analysis joins the debate on how declines in marriage have shifted the composition of the unmarried and married populations in the United States, and how compositional shifts have affected nonmarital birth rates. Gray, Stockard, and Stone (2006) presented one model for compositional effects that Ermisch (2009) challenged with alternative statistical tests. I propose an alternative model for compositional shifts based not on theory but on observed marriage and fertility patterns. The results from this alternative model are consistent with Ermisch’s findings yet support Gray et al.’s general case that compositional effects have had an important infiuence on nonmarital birth rates.     

The effect of number of siblings on adult mortality: Evidence from Swedish registers for cohorts born between 1938 and 1972

Demographic research has paid much attention to the impact of childhood conditions on adult mortality. We focus on one of the key aspects of early life conditions, sibling group size, and examine the causal effect of growing up in a large family on mortality. While previous studies have focused on low- or middle-income countries, we examine whether growing up in a large family is a disadvantage in Sweden, a context where most parents have adequate resources, which are complemented by a generous welfare state. We used Swedish register data and frailty models, examining all-cause and cause-specific mortality between the ages of 40 and 74 for the 1938–72 cohorts, and also a quasi-experimental approach that exploited multiple births as a source of exogenous variation in the number of siblings. Overall our results do not indicate that growing up in a large family has a detrimental effect on longevity in Sweden.     

Gambling,Risk-Taking,and Antisocial Behavior: A Replication Study Supporting the Generality of Deviance

Research suggests that high frequency gambling is a component of the “generality of deviance”, which describes the observation that various forms of risky and antisocial behavior tend to co-occur among individuals. Furthermore, risky and antisocial behaviors have been associated with such personality traits as low self-control, and impulsivity, and sensation-seeking. We conducted a replication (and extension) of two previous studies examining whether high frequency gambling is part of the generality of deviance using a large and diverse community sample (n = 328). This study was conducted as a response to calls for more replication studies in the behavioral and psychological sciences (recent systematic efforts suggest that a significant proportion of psychology studies do not replicate). The results of the present study largely replicate those previously found, and in many cases, we observed stronger associations among measures of gambling, risk-taking, and antisocial behavior in this diverse sample. Together, this study provides evidence for the generality of deviance inclusive of gambling (and, some evidence for the replicability of research relating to gambling and individual differences).     

Patterns of pollinator turnover and increasing diversity associated with urban habitats

The role of urban expansion on bee diversity is poorly understood, but it may play an important role in restructuring pollinator diversity observed in rural regions at the urban perimeter. We studied bee communities in two habitats essential for pollinators (residential gardens and semi-natural areas) at 42 sites situated at the edge of greater Montreal, Canada. Bee species richness, abundance and functional diversity all increased with urbanization in both habitat types, but gardens and semi-natural areas supported distinct bee communities with unique responses to urbanization in terms of species turnover. Compared to semi-natural sites, residential gardens supported bees that foraged from a greater number but a lower proportion of available plant species. Bees did not discriminate between exotic and indigenous plant species in either gardens or semi-natural sites and were attracted to flowers in either habitat irrespective of their origins. Protecting semi-natural ruderal areas and providing residential garden habitats for pollinators are both effective means of promoting regional bee diversity in urbanizing regions.     

Minority Stress,Emotion Regulation,and the Parenting of Sexual-Minority Youth

ABSTRACT

Despite increasing societal acceptance of sexual-minority individuals, there are still gay, lesbian, and bisexual (GLB) adolescents who experience negative mental health outcomes. Minority stress theory posits that stigma-related stress associated with sexual-minority status drives increased risk among GLB individuals. Furthermore, recent evidence suggests that minority stress impacts emotion regulation (ER), identified as a particularly important risk factor for sexual-minority youth (SMY). Current research has identified some aspects of parenting contribute to GLB youth's mental health. We review the literature in these areas, and also integrate research from the broader developmental field on families and emotion socialization in order to identify the need for studies of parenting that go beyond existing data on parental acceptance and supportiveness of youth's sexual orientation. Limitations of the current literature and directions for future research are discussed, with specific focus on implications for interventions with SMY and their families.