A Comparison of Some Methods for the Selection of a Common Eigenvector Model for the Covariance Matrices of Two Groups

Two new nonparametric common principal component model selection procedures based on bootstrap distributions of the vector correlations of all combinations of the eigenvectors from two groups are proposed. The performance of these methods is compared in a simulation study to the two parametric methods previously suggested by Flury in 1988, as well as modified versions of two nonparametric methods proposed by Klingenberg in 1996 and then by Klingenberg and McIntyre in 1998. The proposed bootstrap vector correlation distribution (BVD) method is shown to outperform all of the existing methods in most of the simulated situations considered.     

A New Quantile Function with Applications to Reliability Analysis

In this article, we propose a new class of distributions defined by a quantile function, which nests several distributions as its members. The quantile function proposed here is the sum of the quantile functions of the generalized Pareto and Weibull distributions. Various distributional properties and reliability characteristics of the class are discussed. The estimation of the parameters of the model using L-moments is studied. Finally, we apply the model to a real life dataset.     

Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence

Most existing reduced-form macroeconomic multivariate time series models employ elliptical disturbances, so that the forecast densities produced are symmetric. In this article, we use a copula model with asymmetric margins to produce forecast densities with the scope for severe departures from symmetry. Empirical and skew t distributions are employed for the margins, and a high-dimensional Gaussian copula is used to jointly capture cross-sectional and (multivariate) serial dependence. The copula parameter matrix is given by the correlation matrix of a latent stationary and Markov vector autoregression (VAR). We show that the likelihood can be evaluated efficiently using the unique partial correlations, and estimate the copula using Bayesian methods. We examine the forecasting performance of the model for four U.S. macroeconomic variables between 1975:Q1 and 2011:Q2 using quarterly real-time data. We find that the point and density forecasts from the copula model are competitive with those from a Bayesian VAR. During the recent recession the forecast densities exhibit substantial asymmetry, avoiding some of the pitfalls of the symmetric forecast densities from the Bayesian VAR. We show that the asymmetries in the predictive distributions of GDP growth and inflation are similar to those found in the probabilistic forecasts from the Survey of Professional Forecasters. Last, we find that unlike the linear VAR model, our fitted Gaussian copula models exhibit nonlinear dependencies between some macroeconomic variables. This article has online supplementary material.     

Differences by gender, ethnicity, and acculturation in the efficacy of the keepin' it REAL model prevention program

This study examined whether the efficacy of keepin' it REAL, a model program for substance use prevention in schools, was moderated by gender, ethnicity, and acculturation. Gender differences in program efficacy may arise through boys' higher risk of drug use, inadequate attention to girls' developmental issues, or cultural factors like polarized gender expectations. Data came from a randomized trial in 35 Phoenix, Arizona, middle schools involving 4,622 mostly Latino 7th graders. Using multi-level mixed models and multiple imputation missing techniques, results for the total sample showed no gender differences in program effects on recent substance use, but the program was more effective in fostering boys' than girls' anti-drug norms. Subgroup analyses demonstrated several more beneficial program effects for boys than girls (less alcohol and cigarette use and stronger anti-drug norms), but only among less acculturated Latinos. There were no gender differences in program effects among more acculturated Latinos, nor among non-Latino whites.     

Home study methods for evaluating prospective resource families: history, current challenges, and promising approaches

Every state requires a home study before the placement of foster children for adoption. This article examines the history of home studies, presents results from expert interviews on the changing processes and purposes of home studies, and explores current challenges for the field. The article also introduces the Structured Analysis Family Evaluation (SAFE), a uniform home study format that encourages consistent family evaluations across workers, agencies, and jurisdictions. The article clarifies how SAFE may address challenges facing foster care and adoption practice.     

Assessing lesbian and gay prospective foster and adoptive families: a focus on the home study process

Foster care and adoption by gay men and lesbians is not a new phenomenon. Children and youth have always been placed by states and public agencies in homes with gay and lesbian parents. Some gay men and lesbians have fostered or adopted children independently from private agencies or have made private adoption arrangements with individual birthmothers, while others have fostered or adopted through the public system. Drawing on research literature, practice wisdom from 31 years of child welfare experiences, and case examples, this article offers child welfare professionals guidelines for competent assessment with prospective foster or adoptive parents who identify as lesbian or gay.     

Semi-structured interview protocol for constructing logic models

This paper details a semi-structured interview protocol that evaluators can use to develop a logic model of a program's services and outcomes. The protocol presents a series of questions, which evaluators can ask of specific program informants, that are designed to: (1) identify key informants basic background and contextual information, (2) generate logic model elements, (3) model program inputs, activities, outputs, and outcomes, (4) build a rational theory, (5) develop a program theory, (6) prioritize logic model elements, and (7) build a graphical or tabular logic model. The paper will also provide an example of how this approach was used to develop a logic model for a youth mentoring program. It is our hope and belief that with this interview protocol, novice evaluators will be able to generate comprehensive logic models like seasoned professional evaluators.     

Gambling Behavior of Student-Athletes and a Student Cohort: What are the Odds?

This study investigated the prevalence of gambling, gambling related NCAA violations, and disordered gambling in student-athletes (n = 736) with a comparison cohort of students (n = 1,071) at four universities. Student-athletes reported similar rates of gambling frequency, use of a bookmaker, and disordered gambling as students. After accounting for demographic differences, student-athletes were less likely to engage in sports wagering than students. Several risk factors for disordered gambling were identified, including being male and reporting at least one parent with a history of gambling problems. These findings suggest that problems associated with gambling are a university-wide issue with student-athletes meriting additional attention because of implications for the integrity of intercollegiate sports. Improved prevention and intervention efforts for collegiate gambling are recommended.