Predicting Attitudes Toward Lesbian and Gay Parent Families Among Portuguese Students from Helping Professions

The authors' goal was to characterize predictors of attitudes toward lesbian and gay parent families (LGPF), held by students enrolled in psychology, social work, medicine, nursing, elementary, and preschool education programs in Portugal. The authors examined the predictive value of students' (n = 600) sociodemographic characteristics when assessing their attitudes toward LGPF. Participant's gender, interpersonal contact with lesbians and gay men, gender role attitudes had indirect effects on attitudes toward LGPF, through attitudes toward lesbians and gay men. Understanding characteristics associated with attitudes toward LGPF may inform decisions in terms of the education and training of helping professionals.     

How Does Occupational Access for Older Workers Differ by Education?

To assess the employment opportunities of older job-changers in the years prior to retirement, this study examines the how the breadth of occupations in which they find employment narrows as they age past their prime working years and how this differs by gender and educational attainment. The results indicate that workers who change jobs in their early 50s find employment in a reasonably similar set of occupations as prime-age workers, with opportunities narrowing at older ages. They also indicate that job opportunities broadened significantly for better-educated older workers since the late 1990s. While job opportunities now narrow significantly for less-educated men in their late 50s, this narrowing primarily occurs in the early 60s for women and better-educated men. In contrast to previous research, the study finds that employer policies that emphasize hiring from within are less important barriers to the hiring of older job-seekers. The study also finds that the narrowing of job opportunities is associated with a general decline in job quality as measured by median occupational earnings, a decline associated with differences in occupational skill requirements and the underlying economic environment. These results suggest that older hiring is not as limited to a select few occupations as it had been in previous decades, and that policy reforms aimed at increasing opportunities and improving labor market fluidity might best be served if they focused on less-educated men.     

The eigenstructure of block-structured correlation matrices and its implications for principal component analysis

Block-structured correlation matrices are correlation matrices in which the p variables are subdivided into homogeneous groups, with equal correlations for variables within each group, and equal correlations between any given pair of variables from different groups. Block-structured correlation matrices arise as approximations for certain data sets’ true correlation matrices. A block structure in a correlation matrix entails a certain number of properties regarding its eigendecomposition and, therefore, a principal component analysis of the underlying data. This paper explores these properties, both from an algebraic and a geometric perspective, and discusses their robustness. Suggestions are also made regarding the choice of variables to be subjected to a principal component analysis, when in the presence of (approximately) block-structured variables.     

Block and Basu bivariate lifetime distribution in the presence of cure fraction

This paper presents estimates for the parameters included in the Block and Basu bivariate lifetime distributions in the presence of covariates and cure fraction, applied to analyze survival data when some individuals may never experience the event of interest and two lifetimes are associated with each unit. A Bayesian procedure is used to get point and confidence intervals for the unknown parameters. Posterior summaries of interest are obtained using standard Markov Chain Monte Carlo methods in rjags package for R software. An illustration of the proposed methodology is given for a Diabetic Retinopathy Study data set.     

A Bayesian model for estimating the malaria transition probabilities considering individuals lost to follow-up

It is known that patients may cease participating in a longitudinal study and become lost to follow-up. The objective of this article is to present a Bayesian model to estimate the malaria transition probabilities considering individuals lost to follow-up. We consider a homogeneous population, and it is assumed that the considered period of time is small enough to avoid two or more transitions from one state of health to another. The proposed model is based on a Gibbs sampling algorithm that uses information of lost to follow-up at the end of the longitudinal study. To simulate the unknown number of individuals with positive and negative states of malaria at the end of the study and lost to follow-up, two latent variables were introduced in the model. We used a real data set and a simulated data to illustrate the application of the methodology. The proposed model showed a good fit to these data sets, and the algorithm did not show problems of convergence or lack of identifiability. We conclude that the proposed model is a good alternative to estimate probabilities of transitions from one state of health to the other in studies with low adherence to follow-up.     

A study of the relationship between protective behaviors and drinking consequences among undergraduate college students

The authors identified the number, type, and frequency of protective behaviors that undergraduate college students who consume alcohol use to prevent alcohol-related consequences. Their hypothesis was that students who engage in more types of protective behaviors with greater frequency would be less likely to experience alcohol-related consequences. Participants consisted of a randomly selected sample of 1,355 undergraduates aged 18 years and older at a large public university. Students completed a mailed questionnaire on alcohol and health behaviors in spring 2002. The findings (after adjustment for covariates) indicated that self-protective behaviors are inversely associated with alcohol-related problems for women but not for men. The influences of gender and racial and ethnic differences are considered in relation to prevention and intervention programs aimed at reducing alcohol-related consequences on college campuses.     

Differences in African American and White college students' drinking behaviors: consequences, harm reduction strategies, and health information sources

The authors explored the differences between African American and White college students' drinking behaviors and their attitudes toward consequences, harm-reduction strategies, and health information sources. They collected data from a randomly selected sample of 1,110 students in a large public university to examine the effects of a high-risk drinking prevention intervention. In the current analysis, they compared African American and White students on indicators of high-risk drinking, drinking consequences, harm-reduction strategies, the sources that students typically used for health information, and the believability of those sources. The African American students scored lower on drinking measures than the White students did, reported fewer negative consequences, and more regularly employed drinking-reduction strategies, with one exception--choosing a designated driver. Both African and White respondents reported that their parents were their most frequent and usual sources of health-related information and said that parents and health professionals were the most credible sources.     

Residual Kriging for Functional Spatial Prediction of Salinity Curves

Recently, several methodologies to perform geostatistical analysis of functional data have been proposed. All of them assume that the spatial functional process considered is stationary. However, in practice, we often have nonstationary functional data because there exists an explicit spatial trend in the mean. Here, we propose a methodology to extend kriging predictors for functional data to the case where the mean function is not constant through the region of interest. We consider an approach based on the classical residual kriging method used in univariate geostatistics. We propose a three steps procedure. Initially, a functional regression model is used to detrend the mean. Then we apply kriging methods for functional data to the regression residuals to predict a residual curve at a non-data location. Finally, the prediction curve is obtained as the sum of the trend and the residual prediction. We apply the methodology to salinity data corresponding to 21 salinity curves recorded at the Ciénaga Grande de Santa Marta estuary, located in the Caribbean coast of Colombia. A cross-validation analysis was carried out to track the performance of the proposed methodology.