Problem drinking patterns among African Americans: the impacts of reports of discrimination, perceptions of prejudice, and "risky" coping strategies

This research builds on a series of recent studies that have reported independent effects of personal experiences of racial discrimination on poor mental health outcomes. We suggest that for one mental health outcome, problem drinking, discrimination experiences have an impact not only via abridged socioeconomic attainment and the frustrations associated with institutionally limited opportunity structures, but also by directly increasing the likelihood of problem drinking. Moreover, we argue that personal experiences with discrimination help to foster a set of beliefs about the utility of drinking as a means of reducing stress that in the alcohol literature is referred to as "escapist" drinking. Escapist drinking is proposed as an intervening mechanism that is associated with a higher probability of alcohol-related mental health problems. Using data from the 1999-2000 National Survey of Black Workers, we find that, independent of socioeconomic attainment, personal reports of discriminatory experiences have direct influences on problem drinking. Consistent with our hypotheses, we also find that the effects of personal reports of discrimination are at least partially mediated by the endorsement of beliefs that drinking provides an effective coping mechanism. We conclude that racial impacts on mental health outcomes reflect more than the "simple" effects of constrained socioeconomic attainment.     

On admissible estimation for parametric functions in linear models

This paper deals with the linear model Ey∈K, Cov y∈V. The question is investigated when a parametric function (a,y) is an admissible or inadmissible estimator of some parametric function (p,Ey). It is also discussed when a linear mapping C:K→K has the property that (a,cy) is an admissible estimator of ((Ey),a) for all a∈K. Finall the question is raised how inadmissible estimators (a,y) can be replaced by admissible estimators superior to (a,y).     

Bayesian Forecasting via Deterministic Model

Rational decision making requires that the total uncertainty about a variate of interest (a predictand) be quantified in terms of a probability distribution, conditional on all available information and knowledge. Suppose the state-of-knowledge is embodied in a deterministic model, which is imperfect and outputs only an estimate of the predictand. Fundamentals are presented of two Bayesian methods for producing a probabilistic forecast via any deterministic model. The Bayesian Processor of Forecast (BPF) quantifies the total uncertainty in terms of a posterior distribution, conditional on model output. The Bayesian Forecasting System (BFS) decomposes the total uncertainty into input uncertainty and model uncertainty, which are characterized independently and then integrated into a predictive distribution. The BFS is compared with Monte Carlo simulation and ensemble forecasting technique, none of which can alone produce a probabilistic forecast that quantifies the total uncertainty, but each can serve as a component of the BFS.     

确保从研究到开发界面的有效管理 --R&D个体的知识转移管理

在技术密集型公司中一个重要的问题是构建无隔层创新流程(seamlessinnovationprocesses).这里无发明(not-invented-here,NIH)综合症和其它的障碍严重影响着研究和开发之间知识和技术的有效转移.由于存在着保守型结构、过时的转移设备以及下游职能定位模糊等原因,知识转移经常失败.从研究到开发产生障碍的原因主要有以下几方面:职能分割、地理位置、专业偏好和文化背景等.首先,我们在25家公司做了100多次的半结构性访谈;然后,我们在技术密集型产业做深入的案例研究.改进从研究到开发的界面总是围绕着R&D个体展开.我们通过对ABB、Hitachi、IBM、Kao、Unisys以及xerox等公司的案例分析,得出了一些成功的实践经验.我们得出这样的结论:从研究到开发界面的有效管理通过对管理R&D个体的知识转移获得.     

Alternative sensitivity analyses for regression estimates of treatment effects to unobserved confounding in binary and survival data

Statistical Methods & Applications - Estimates of treatment effects in non-experimental studies are subject to bias owing to unobserved confounding. It is desirable to assess the sensitivity of...