Gambling Disorder Due to Brazilian Animal Game (“Jogo do bicho”): Gambling Behavior and Psychopathology

Gambling is currently widespread across the globe and despite legally restricted, it is significantly common in Brazil. A traditional and common form of gambling in Brazil is the Brazilian animal game (BAG)—“Jogo do bicho” in Portuguese. In 2013, BAG activities collected approximately 19 billion Brazilian reais—equivalent to more than 8 billon American dollars, a figure almost 60 % higher than legal lotteries. Although a common form of gambling, the gambling behavior and psychopathology of gambling disorder (GD) associated with BAG has never been systematically studied. The aim of this study is to conduct, the first research approaching GD due to BAG. We assessed 897 participants of whom 63 subjects (7.0 %) presented with GD due to BAG and 834 with GD associated with other forms of gambling. After comparing these two groups, major differences were found in demographics, gambling behavior elements and psychopathological variables. This research reinforces the need for further research on BAG and the need for specific approaches in GD. The particularities of BAG may affect treatment strategies as, for example, suggest some adaptations in social and psychotherapeutic approaches. We also highlight the need to acknowledge the “hidden” BAG as a potential addictive game.     

Legal Corruption and Dissatisfaction with Democracy in the European Union

We aim to clarify a puzzling paradox: while shares of highly educated and non-religious individuals—who generally hold less prejudice—have increased in the Netherlands, levels of prejudice against ethnic minorities have yet risen over time. To solve the paradox, we use cross-sectional data from 1985 to 2011 in counterfactual analyses. In these analyses we simulate that levels of ethnic prejudice within categories of education, church membership, and church attendance are kept constant at the 1985 level and a new simulated trend in prejudice is estimated for the 1985–2011 period. Our findings show that changing levels of prejudice within categories of education are partly responsible for the trend. We conclude that the increasing share of highly educated individuals has not resulted in a decline of prejudice in the Netherlands over time, because all Dutch have become more prejudiced over the years and in particular the higher educated.     

Bidirectional relations among empathy‐related traits,prosocial moral reasoning,and prosocial behaviors

This study examined the longitudinal links among empathic concern, perspective taking, prosocial moral reasoning, and prosocial behaviors. Four hundred and seventeen adolescents (225 girls; M_age = 14.70 years) from public schools in Spain completed measures of those constructs in three successive years. Path analyses showed support for the notion that empathic concern and prosocial moral reasoning accounted for the relations between perspective taking in earlier adolescence and later altruistic and public forms of helping. Moreover, there was support for a reverse causal model such that empathic concern and prosocial moral reasoning mediated the relations between altruistic (but not public) helping behaviors in earlier adolescence and later perspective taking. The implications for cognitive developmental and social cognitive theories of prosocial development were discussed.     

A class of residuals for outlier identification in zero adjusted regression models

Zero adjusted regression models are used to fit variables that are discrete at zero and continuous at some interval of the positive real numbers. Diagnostic analysis in these models is usually performed using the randomized quantile residual, which is useful for checking the overall adequacy of a zero adjusted regression model. However, it may fail to identify some outliers. In this work, we introduce a class of residuals for outlier identification in zero adjusted regression models. Monte Carlo simulation studies and two applications suggest that one of the residuals of the class introduced here has good properties and detects outliers that are not identified by the randomized quantile residual.     

The Role of Child Emotional Responsiveness and Maternal Negative Emotion Expression in Children's Coping Strategy Use

This study examined the additive and interactive effects of children's trait vicarious emotional responsiveness and maternal negative emotion expression on children's use of coping strategies. Ninety‐five children (mean age = 5.87 years) and their mothers and teachers participated in the study. The mothers reported on their own negative emotion expression and the children's empathic concern and personal distress tendencies. The mothers and teachers reported on the children's use of avoidant, support‐seeking, and aggressive‐venting coping strategies. Empathic concern was positively associated with the children's use of support seeking and negatively associated with the children's use of aggressive venting, whereas personal distress showed the opposite pattern of associations. Maternal negative emotion expression moderated some associations between the children's emotional responsiveness and coping. These findings support the hypothesis that children's tendencies to experience empathic concern or personal distress indicate functionally distinct styles of emotional arousal that may have broader consequences for socially competent behavior in response to normative stressors.     

One or more rates of ageing? The extended gamma-Gompertz model (EGG)

Statistical Methods & Applications - Hidden heterogeneity poses serious challenges to survival analysis because the observed (aggregate) and the unobservable (individual) hazard functions may...     

Bayesian mismeasurement t-models for censored responses

This paper aims at introducing a Bayesian robust error-in-variable regression model in which the dependent variable is censored. We extend previous works by assuming a multivariate t distribution for jointly modelling the behaviour of the errors and the latent explanatory variable. Inference is done under the Bayesian paradigm. We use a data augmentation approach and develop a Markov chain Monte Carlo algorithm to sample from the posterior distributions. We run a Monte Carlo study to evaluate the efficiency of the posterior estimators in different settings. We compare the proposed model to three other models previously discussed in the literature. As a by-product we also provide a Bayesian analysis of the t-tobit model. We fit all four models to analyse the 2001 Medical Expenditure Panel Survey data.     

On the superposition of overlapping Poisson processes and nonparametric estimation of their intensity function

It is shown that, when measuring time in the Total Time on Test scale, the superposition of overlapping realizations of a nonhomogeneous Poisson process is also a Poisson process and is sufficient for inferential purposes. Hence, many nonparametric procedures which are available when only one realization is observed can be easily extended for the overlapping realizations setup. These include, for instance, the constrained maximum likelihood estimator of a monotonic intensity and bootstrap confidence bands based on Kernel estimates of the intensity. The kernel estimate proposed here performs the smoothing in the Total Time on Test scale and it is shown to behave approximately as a usual kernel estimate but with a variable bandwidth which is inversely proportional to the number of realizations at-risk. Likewise, bootstrap samples can be obtained from the single realization of the superimposed process. The methods are illustrated using a real data set consisting of the failure histories of 40 electrical power transformers.     

Space‐time cluster identification in point processes

The authors propose a new type of scan statistic to test for the presence of space‐time clusters in point processes data, when the goal is to identify and evaluate the statistical significance of localized clusters. Their method is based only on point patterns for cases; it does not require any specific knowledge of the underlying population. The authors propose to scan the three‐dimensional space with a score test statistic under the null hypothesis that the underlying point process is an inhomogeneous Poisson point process with space and time separable intensity. The alternative is that there are one or more localized space‐time clusters. Their method has been implemented in a computationally efficient way so that it can be applied routinely. They illustrate their method with space‐time crime data from Belo Horizonte, a Brazilian city, in addition to presenting a Monte Carlo study to analyze the power of their new test.