Classifying At‐Risk High School Youth: The Influence of Exposure to Community Violence and Protective Factors on Academic and Health Outcomes

Using cluster analysis, 789 predominately Latino and African American high school youth were classified into varying academic at‐risk profiles using self‐reported levels of academic confidence, motivation to attend school, perceived family support, connections with teachers and peers, and exposure to violence. Six clusters emerged, 5 of which were identified as “at‐risk.” The clusters were examined in relation to academic stress, health status, grades, and school retention. Exposure to violence was one distinguishing feature of youth identified as most vulnerable, vulnerable, and resilient; however, youth identified as resilient recorded better academic outcomes.     

Gay Affirmative Practice: A Model for Social Work Practice with Gay,Lesbian, and Bisexual Youth

Gay affirmative practice has recently been introduced into the social work literature as a culturally sensitive model for working with gay, lesbian, and bisexual (GLB) adults, however, this model has rarely been applied to practice with GLB youth. In this article, the authors review the literature to present the main tenets of gay affirmative practice, outline the challenges that GLB youth face, and delineate the environmental and individual strengths that can be enhanced to promote well-being. The authors then apply the gay affirmative practice model to GLB youth, offering concrete information about the specific knowledge, attitudes, and skills that social workers should acquire to better serve the unique, yet diverse, needs of GLB youth.     

Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.     

A simple estimator for a shared frailty regression model

Summary. We propose a simple estimation procedure for a proportional hazards frailty regression model for clustered survival data in which the dependence is generated by a positive stable distribution. Inferences for the frailty parameter can be obtained by using output from Cox regression analyses. The computational burden is substantially less than that of the other approaches to estimation. The large sample behaviour of the estimator is studied and simulations show that the approximations are appropriate for use with realistic sample sizes. The methods are motivated by studies of familial associations in the natural history of diseases. Their practical utility is illustrated with sib pair data from Beaver Dam, Wisconsin.     

在应对入世后我国农业面临的挑战中分析测试技术和科学仪器担负的重任

本文概叙了入世后中国农业面临的农产品品质 安全性及价格的三重冲击和应采取的应对措施 着重分析了农产品安全问题和食品安全保障体系的构建 论述了分析测试技术和科学仪器的七项重任