On a new goodness‐of‐fit process for families of copulas

A goodness‐of‐fit procedure is proposed for parametric families of copulas. The new test statistics are functionals of an empirical process based on the theoretical and sample versions of Spearman's dependence function. Conditions under which this empirical process converges weakly are seen to hold for many families including the Gaussian, Frank, and generalized Farlie–Gumbel–Morgenstern systems of distributions, as well as the models with singular components described by Durante [Durante ( 2007 ) Comptes Rendus Mathématique. Académie des Sciences. Paris, 344, 195–198]. Thanks to a parametric bootstrap method that allows to compute valid P‐values, it is shown empirically that tests based on Cramér–von Mises distances keep their size under the null hypothesis. Simulations attesting the power of the newly proposed tests, comparisons with competing procedures and complete analyses of real hydrological and financial data sets are presented. The Canadian Journal of Statistics 37: 80‐101; 2009 © 2009 Statistical Society of Canada     

Using the EM algorithm for Bayesian variable selection in logistic regression models with related covariates

We develop a Bayesian variable selection method for logistic regression models that can simultaneously accommodate qualitative covariates and interaction terms under various heredity constraints. We use expectation-maximization variable selection (EMVS) with a deterministic annealing variant as the platform for our method, due to its proven flexibility and efficiency. We propose a variance adjustment of the priors for the coefficients of qualitative covariates, which controls false-positive rates, and a flexible parameterization for interaction terms, which accommodates user-specified heredity constraints. This method can handle all pairwise interaction terms as well as a subset of specific interactions. Using simulation, we show that this method selects associated covariates better than the grouped LASSO and the LASSO with heredity constraints in various exploratory research scenarios encountered in epidemiological studies. We apply our method to identify genetic and non-genetic risk factors associated with smoking experimentation in a cohort of Mexican-heritage adolescents.     

A network epidemic model for online community commissioning data

A statistical model assuming a preferential attachment network, which is generated by adding nodes sequentially according to a few simple rules, usually describes real-life networks better than a model assuming, for example, a Bernoulli random graph, in which any two nodes have the same probability of being connected, does. Therefore, to study the propagation of “infection” across a social network, we propose a network epidemic model by combining a stochastic epidemic model and a preferential attachment model. A simulation study based on the subsequent Markov Chain Monte Carlo algorithm reveals an identifiability issue with the model parameters. Finally, the network epidemic model is applied to a set of online commissioning data.     

Updating beliefs with imperfect signals: Experimental evidence

We conduct an experiment on individual choice under risk in which we study belief updating when an agent receives a signal that restricts the number of possible states of the world. Subjects observe a sample drawn from an urn and form initial beliefs about the urn??s composition. We then elicit how beliefs are modified after subjects receive a signal that restricts the set of the possible urns from which the observed sample could have been drawn. We find that this type of signal increases the frequency of correct assessments and that prediction accuracy is higher for lower levels of risk. We also show that prediction accuracy is higher after invalidating signals (i.e. signals that contradict the initial belief). This pattern is explained by the lower level of risk associated with invalidating signals. Finally, we find evidence for a lack of persistence of choices under high risk.     

Trajectories of team and individual sports participation in childhood and links with internalizing problems

The purpose of this 5-year longitudinal study is to identify trajectories of team and individual sports participation in childhood, and to compare these trajectories on different types of internalizing problems. Parents reported their children's annual sports participation from the ages of 6–10 (n = 785) and teachers reported internalizing problems (depression, anxiety, social withdrawal) at the beginning and at the end of this period. The study used latent class growth analyses to identify two trajectories of team sports and two trajectories of individual sports participation were identified: (1) high participation, and (2) low participation. Considering baseline level of internalizing problems and gender, children in the high participation team sports trajectory show significantly fewer depression, anxiety, and social withdrawal behaviors at age 10 than those in the low participation team sports trajectory. No differences between individual sports trajectories were observed. Comparison with joint trajectory groups partially confirmed these results but also showed that sustained participation in multiple individual sports could also be linked to decreased anxiety. Our findings suggest that participation in team sports should be encouraged to promote certain aspects of children's mental health.     

Neighbourhood Life,Social Capital and Perceptions of Safety in the Western Suburbs of Adelaide

In this paper we report on a South Australian study of perceptions of safety and aspects of neighbourhood life including social capital which involved the analysis of 2400 self‐completed questionnaires. A path analysis found that perceptions of safety were directly associated with gender, age, perceptions of neighbourhood pollution and neighbourhood trust, and indirectly associated with age, neighbourhood pollution and neighbourhood connections. We conclude with a discussion of the implications of the findings for public policy.