Applications of quadrivariate exponential distribution to a three-unit warm standby system with dependent structure

Two-unit warm standby systems have been elaborately dealt within the literature. However, the study of standby systems with more than two units, though very relevant in state-of-the-art practical situations, has received little attention because of mathematical intricacies involved in analyzing them. Also, such systems have been studied assuming: (i) the lifetime or repair time of the units to be exponential, or (ii) the lifetime and repair time to be independent. The present contribution is an improvement in the state-of-the-art in the sense that three-unit warm standby system with dependent structure is shown to be capable of comprehensive analysis.     

The psychometric and empirical properties of measures of risk preferences

We examine the psychometric and empirical properties of some commonly used survey-based measures of risk preferences in a population-based sample of 11,000 twins. Using a model that provides a general framework for making inferences about the component of measured risk attitudes that is not due to measurement error, we show that measurement-error adjustment leads to substantially larger estimates of the predictive power of risk attitudes, of the size of the gender gap, and of the magnitude of the sibling correlation. Risk attitudes are predictive of investment decisions, entrepreneurship, and drinking and smoking behaviors; are robustly associated with cognitive ability and personality; and our estimates are often larger than those in the literature. Our results highlight the importance of adjusting for measurement error across a wide range of empirical settings.     

Model averaging for treatment effect estimation in subgroups

In many clinical trials, biological, pharmacological, or clinical information is used to define candidate subgroups of patients that might have a differential treatment effect. Once the trial results are available, interest will focus on subgroups with an increased treatment effect. Estimating a treatment effect for these groups, together with an adequate uncertainty statement is challenging, owing to the resulting “random high” / selection bias. In this paper, we will investigate Bayesian model averaging to address this problem. The general motivation for the use of model averaging is to realize that subgroup selection can be viewed as model selection, so that methods to deal with model selection uncertainty, such as model averaging, can be used also in this setting. Simulations are used to evaluate the performance of the proposed approach. We illustrate it on an example early‐phase clinical trial.     

Effects of parental absence on child labor and school attendance in the Philippines

This paper uses longitudinal data from the Philippines to analyze determinants of children’s time allocation. The estimation method takes into account both the simultaneity of time use decisions, by allowing for correlation of residuals across time uses, and unobservable family heterogeneity, through the inclusion of household fixed effects. Importantly, this improved estimation method leads to different results than when applying the methods previously used in the literature. Girls suffer significantly from the absence of their mother with a reduction in time spent in school that is equivalent to dropping out completely. This effect is substantially larger when controlling for household unobservables than when not. Boys increase time spent working on market related activities in response to an absent father, although this time appears to come out of leisure rather than school or doing household chores. Land ownership substantially increase the time boys spend on school activities, whereas renting land reduces the time girls spend on school. Finally, there does not appear to be a substantial trade-off between time spent on school and work, either in the market or at home.     

Maternal Conflict Behavior Profiles and Child Social Skills

The current study examined associations between mothers’ behavioral profiles during mother‐child conflict interactions and their children's social skills. This person‐centered approach classified 181 mothers according to their levels of emotional responsiveness, intrusiveness, negativity, and engagement facilitation behaviors during an eight‐minute conflict discussion task with their child. Three distinct classes of mothers were identified using latent profile analysis: sensitive/engaged, moderately sensitive/engaged, and insensitive/disengaged. An analysis of covariance indicated that children of mothers in the sensitive/engaged group had significantly higher social skills than children of mothers in the moderately sensitive/engaged and insensitive/disengaged groups. Results suggest that mother‐child conflict interactions may benefit children's social development when mothers facilitate their children's participation in a highly sensitive manner.     

Impacts of urban sprawl on species richness of plants,butterflies, gastropods and birds: not only built-up area matters

Urban growth is a major factor of global environmental change and has important impacts on biodiversity, such as changes in species composition and biotic homogenization. Most previous studies have focused on effects of urban area as a general measure of urbanization, and on few or single taxa. Here, we analyzed the impacts of the different components of urban sprawl (i.e., scattered and widespread urban growth) on species richness of a variety of taxonomic groups covering mosses, vascular plants, gastropods, butterflies, and birds at the habitat and landscape scales. Besides urban area, we considered the average age, imperviousness, and dispersion degree of urban area, along with human population density, to disentangle the effects of the different components of urban sprawl on biodiversity. The study was carried out in the Swiss Plateau that has undergone substantial urban sprawl in recent decades.Vascular plants and birds showed the strongest responses to urban sprawl, especially at the landscape scale, with non-native and ruderal plants proliferating and common generalist birds increasing at the expense of specialist birds as urban sprawl grew. Overall, urban area had the greatest contribution on such impacts, but additional effects of urban dispersion (i.e., increase of non-native plants) and human population density (i.e., increases of ruderal plants and common generalist birds) were found. Our findings support the hypothesis that negative impacts of urban sprawl on biodiversity can be reduced by compacting urban growth while still avoiding the formation of very densely populated areas.     

The Development of Impulse Control and Sensation‐Seeking in Adolescence: Independent or Interdependent Processes?

This study examines whether changes in impulse control and sensation‐seeking across adolescence and early adulthood reflect independent or interdependent developmental processes. Data are drawn from a national longitudinal study (N = 8,270; 49% female; 33% Black, 22% Hispanic, 45% non‐Black, non‐Hispanic). An autoregressive latent trajectory model is used to test whether development in one trait influences development in the other. Although levels of these traits are inversely correlated, we do not find evidence that change over time in either trait is influenced by the prior level of the other. This failure to reject the null hypothesis is consistent with the view that sensation‐seeking and impulse control are the products of distinct neuropsychological systems that develop independently of one another.     

Deriving Behavior Model Parameters from Survey Data: Self‐Protective Behavior Adoption During the 2009–2010 Influenza A(H1N1) Pandemic

In this paper, we demonstrate how public opinion surveys can be designed to collect information pertinent to computational behavior modeling, and we present the results of a public opinion and behavior survey conducted during the 2009–2010 H1N1 influenza pandemic. The results are used to parameterize the Health Belief Model of individual health‐protective decision making. Survey subjects were asked questions about their perceptions of the then‐circulating influenza and attitudes towards two personal protective behaviors: vaccination and avoidance of crowds. We empirically address two important issues in applying the Health Belief Model of behavior to computational infectious disease simulation: (1) the factors dynamically influencing the states of the Health Belief Model variables and (2) the appropriateness of the Health Belief Model in describing self‐protective behavior in the context of pandemic influenza.