Predictors of Problem Gambling in the U.S.

In this article we examine data from a national U.S. adult survey of gambling to determine correlates of problem gambling and discuss them in light of theories of the etiology of problem gambling. These include theories that focus on personality traits, irrational beliefs, anti-social tendencies, neighborhood influences and availability of gambling. Results show that males, persons in the 31–40 age range, blacks, and the least educated had the highest average problem gambling symptoms. Adults who lived in disadvantaged neighborhoods also had the most problem gambling symptoms. Those who attended religious services most often had the fewest problem gambling symptoms, regardless of religious denomination. Respondents who reported that it was most convenient for them to gamble had the highest average problem gambling symptoms, compared to those for whom gambling was less convenient. Likewise, adults with the personality traits of impulsiveness and depression had more problem gambling symptoms than those less impulsive or depressed. Respondents who had friends who approve of gambling had more problem gambling symptoms than those whose friends did not approve of gambling. The results for the demographic variables as well as for impulsiveness and religious attendance are consistent with an anti-social/impulsivist pathway to problem gambling. The results for depression are consistent with an emotionally vulnerable pathway to problem gambling.     

Elevated phosphorus: dynamics during four years of green roof development

Green roofs are emerging engineered ecosystems that provide multiple benefits, but many are constructed with nutrient-rich substrate and have been found to leach out high levels of phosphorus (P) in runoff. It is unclear, however, how long green roofs act as sources of P or what mechanisms are responsible for these net losses. We measured P concentrations in runoff water over 4 years from a 1–5 year old extensive green roof in Cincinnati, OH, USA, produced a model to predict runoff P levels into the future, and validated predictions using runoff from 2 nearby extensive green roofs. P concentrations in runoff from the focal green roof were on par with heavily fertilized agroecosystems and displayed strong seasonal dynamics and a rapid decline over the 4-year study. Runoff measurements and changes in substrate P content over a 2-year period were used to estimate a mass balance for green roof P. P loss from the substrate was substantial (4.55 ± 2.3 g P/m²/yr), but only a small portion of the loss was attributable to leaching of P in runoff (0.19–0.65 g P/m²/yr). Missing P may be attributed to a combination of plant uptake and altered P form and binding strength, but further research is needed to precisely identify the mechanisms of P depletion. Our results also suggest that these and similar extensive green roofs are likely to act as environmentally significant sources of P for 10 or more years following roof installation, highlighting the need for reductions in initial substrate P content.     

Parent–child gender matching and child psychological adjustment after divorce

The present study aimed to determine whether a parent–child gender match would influence child psychological adjustment after divorce. Participants included 69 parents (36 mothers) in active family law litigation to resolve issues related to postdissolution of marriage or time-sharing matters. Participants provided demographic information and completed the Child Behavior Checklist (CBCL; Achenbach, 1991 Achenbach, T. M. (1991). Manual for the child behavior checklist/4–18 and 1991 profile. Burlington, VT: Department of Psychiatry, University of Vermont. [Google Scholar]) to assess their perceptions of their child’s internalizing and externalizing behavior problems. Results demonstrated that internalizing and externalizing behaviors were not affected by whether children spent more time with the same gender parent, opposite gender parent, or split their time equally between both. Comparisons and contradictions between the results in this study and existing research are discussed, as well as practical implications.     

A Land of Milk and Honey? Breastfeeding and Identity in Lesbian Families

ABSTRACT

This article explores the relationship between breastfeeding and identity in lesbian-identified families based on a pilot study of qualitative interviews and a short survey of six lesbian families in Canada and the United States. Although breastfeeding is assumed to be “natural” and a biological function, we problematize the practice as both gendered and heteronormative. In our research we found that breastfeeding has a complex role to play within the construction of one's identity as a mother, of one's gender, and of one's sexual orientation. These women's experiences offer interesting insights into the nebulous boundaries of biology and the ways in which assumptions about what is “natural” are actually social and cultural constructions.     

A new Bayesian wavelet thresholding estimator of nonparametric regression

The methods of estimation of nonparametric regression function are quite common in statistical application. In this paper, the new Bayesian wavelet thresholding estimation is considered. The new mixture prior distributions for the estimation of nonparametric regression function by applying wavelet transformation are investigated. The reversible jump algorithm to obtain the appropriate prior distributions and value of thresholding is used. The performance of the proposed estimator is assessed with simulated data from well-known test functions by comparing the convergence rate of the proposed estimator with respect to another by evaluating the average mean square error and standard deviations. Finally by applying the developed method, density function of galaxy data is estimated.     

Marginal models for the association structure of hierarchical binary responses

Clustered binary responses are often found in ecological studies. Data analysis may include modeling the marginal probability response. However, when the association is the main scientific focus, modeling the correlation structure between pairs of responses is the key part of the analysis. Second-order generalized estimating equations (GEE) are established in the literature. Some of them are more efficient in computational terms, especially facing large clusters. Alternating logistic regression (ALR) and orthogonalized residual (ORTH) GEE methods are presented and compared in this paper. Simulation results show a slightly superiority of ALR over ORTH. Marginal probabilities and odds ratios are also estimated and compared in a real ecological study involving a three-level hierarchical clustering. ALR and ORTH models are useful for modeling complex association structure with large cluster sizes.     

Model selection criteria in beta regression with varying dispersion

We address the issue of model selection in beta regressions with varying dispersion. The model consists of two submodels, namely: for the mean and for the dispersion. Our focus is on the selection of the covariates for each submodel. Our Monte Carlo evidence reveals that the joint selection of covariates for the two submodels is not accurate in finite samples. We introduce two new model selection criteria that explicitly account for varying dispersion and propose a fast two step model selection scheme which is considerably more accurate and is computationally less costly than usual joint model selection. Monte Carlo evidence is presented and discussed. We also present the results of an empirical application.     

Saddlepoint p-values for group of linear rank tests

Many nonparametric tests in one sample problem, matched pairs, and competingrisks under censoring have the same underlying permutation distribution. This article proposes a saddlepoint approximation to the exact p-values of these tests instead of the asymptotic approximations. The performance of the saddlepoint approximation is assessed by using simulation studies that show the superiority of the saddlepoint methods over the asymptotic approximations in several settings. The use of the saddlepoint to approximate the p-values of class of two sample tests under complete randomized design is also discussed.     

Ignorability conditions for frequentist non parametric analysis of conditional distributions with incomplete data

Rubin (1976 Rubin, D.B. (1976). Inference and missing data. Biometrika 63(3):581–592.[Crossref], [Web of Science ®] , [Google Scholar]) derived general conditions under which inferences that ignore missing data are valid. These conditions are sufficient but not generally necessary, and therefore may be relaxed in some special cases. We consider here the case of frequentist estimation of a conditional cdf subject to missing outcomes. We partition a set of data into outcome, conditioning, and latent variables, all of which potentially affect the probability of a missing response. We describe sufficient conditions under which a complete-case estimate of the conditional cdf of the outcome given the conditioning variable is unbiased. We use simulations on a renal transplant data set (Dienemann et al.) to illustrate the implications of these results.