Gender disparity in the C-suite: Do male and female CEOs differ in how they reached the top?

Through a comparison of the life and career trajectories of thirty male and thirty female CEOs of large organizations, this study offers insights into the genesis of gender disparity in corporate leadership positions, discusses the implications for leadership development, and puts forward a model explaining the disparity in CEO roles. We found gendered patterns in the accumulation of career relevant experiences stretching back to birth into working lives that created significant and cumulative limitations upon the ability of women to access CEO roles and the types of CEO appointments available to them. Limited access to career relevant experiences in childhood, adolescence and in organizations lead to on-going limitations in capital accumulation throughout women's careers. Implications of our findings for both theory and practice are discussed.     

A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC

Statistical Methods & Applications - In this paper is presented the zero-modified poisson difference and present possible applications of them in the analysis of paired count data. The...     

Heterogeneity in treatment effects across diverse populations

Differences in patient characteristics, including age, sex, and race influence the safety and effectiveness of drugs, biologic products, and medical devices. Here we provide a summary of the topics discussed during the opening panel at the 2018 Johns Hopkins Center for Excellence in Regulatory Science and Innovation symposium on Assessing and Communicating Heterogeneity of Treatment Effects for Patient Subpopulations: Challenges and Opportunities. The goal of this session was to provide a brief overview of FDA-regulated therapeutics, including drugs, biologics and medical devices, and some of the major sources of heterogeneity of treatment effects (HTE) related to patient demographics, such as age, sex and race. The panel discussed the US Food and Drug Administration's role in reviewing and regulating drugs, devices, and biologic products and the challenges associated with ensuring that diverse patient populations benefit from these therapeutics. Ultimately, ensuring diverse demographic inclusion in clinical trials, and designing basic and clinical research studies to account for the intended patient population's age, sex, race, and genetic factors among other characteristics, will lead to better, safer therapies for diverse patient populations.     

Classes of protection in urban forest fragments are effectiveless in structuring butterfly assemblages: landscape and forest structure are far better predictors

Urbanization is a major cause of biodiversity loss and disconnection between people and nature. For this reason, the creation and maintenance of green areas as part of the urban landscape is a common practice in cities around the world. These green areas are generally a result of particular public policies regarding how these areas can be accessed, maintained, and how they are connected to other natural fragments in the city. In an effort to investigate aspects of the ecology of such green areas of the city of Curitiba, southern Brazil, the present study measured distinct parameters of the structure of butterfly assemblages from 19 forest fragments of distinct classes of protection, testing the influence of different policies (protection category) on butterfly assemblages. Comparatively, we also tested the predictive power of landscape variables (at distinct scales) and fragment quality (e.g. diameter at breast height, density of vegetation) using Generalized Linear Models (GLMs). Overall, 14,596 individuals belonging to 412 butterfly species were recorded, but values of species diversity and composition are very heterogeneous, indicating that the protection categories do not significantly interfere with the structure of the butterfly assemblages. More important than the protection category is the forest fragment quality and landscape connectivity. Our models showed that degraded fragments tend to present a specific butterfly composition, whereas the more urbanized landscape have poor butterfly species richness. These results reinforce the importance of implementing public policies that prioritize the conservation of the quality of forest fragments in every class of protection, as well as the conservation of forest fragments throughout the urban landscape.

     

Misestimating Betting Behavior: The Role of Negative Asymmetries in Emotional Self Prediction

This paper addresses the role of negative asymmetries in emotional self-prediction by looking at the extent to which individuals misestimate their own betting behavior in sequential gambles. In a series of three experimental studies, we demonstrate that losses lead to higher than planned bets whereas bets are on average carried over after gains. Such asymmetric deviations from the plan emerge (1) when monetary and non-monetary incentives are used, and (2) when participants face fair and unfair gambles. The asymmetry is based on people’s inability to predict how much the negative emotions generated by a bad experience (e.g. the loss) will influence them to put more effort (e.g. bet more) than planned in an attempt to re-establish a homeostatic state in the prospect of a good experience (e.g. winning).     

Robust Bayesian model selection for variable clustering with the Gaussian graphical model

Statistics and Computing - Variable clustering is important for explanatory analysis. However, only few dedicated methods for variable clustering with the Gaussian graphical model have been...     

Methods to assess measurement error in questionnaires of sedentary behavior

Sedentary behavior has already been associated with mortality, cardiovascular disease, and cancer. Questionnaires are an affordable tool for measuring sedentary behavior in large epidemiological studies. Here, we introduce and evaluate two statistical methods for quantifying measurement error in questionnaires. Accurate estimates are needed for assessing questionnaire quality. The two methods would be applied to validation studies that measure a sedentary behavior by both questionnaire and accelerometer on multiple days. The first method fits a reduced model by assuming the accelerometer is without error, while the second method fits a more complete model that allows both measures to have error. Because accelerometers tend to be highly accurate, we show that ignoring the accelerometer's measurement error, can result in more accurate estimates of measurement error in some scenarios. In this article, we derive asymptotic approximations for the mean-squared error of the estimated parameters from both methods, evaluate their dependence on study design and behavior characteristics, and offer an R package so investigators can make an informed choice between the two methods. We demonstrate the difference between the two methods in a recent validation study comparing previous day recalls to an accelerometer-based ActivPal.