我国消费、投资、净出口与经济增长

 消费、投资与出口通常并称为拉动经济增长的三驾马车,对经济增长产生重要作用。同时,经济增长也影响着它们的规模。针对这种情况,本文通过建立联立方程模型以及脉冲响应函数,对我国经济1978-2006年的历史数据进行实证分析,揭示我国改革开放以来它们之间的关系。     

A re-evaluation of random-effects meta-analysis

Summary.  Meta-analysis in the presence of unexplained heterogeneity is frequently undertaken by using a random-effects model, in which the effects underlying different studies are assumed to be drawn from a normal distribution. Here we discuss the justification and interpretation of such models, by addressing in turn the aims of estimation, prediction and hypothesis testing. A particular issue that we consider is the distinction between inference on the mean of the random-effects distribution and inference on the whole distribution. We suggest that random-effects meta-analyses as currently conducted often fail to provide the key results, and we investigate the extent to which distribution-free, classical and Bayesian approaches can provide satisfactory methods. We conclude that the Bayesian approach has the advantage of naturally allowing for full uncertainty, especially for prediction. However, it is not without problems, including computational intensity and sensitivity to a priori judgements. We propose a simple prediction interval for classical meta-analysis and offer extensions to standard practice of Bayesian meta-analysis, making use of an example of studies of 'set shifting' ability in people with eating disorders.     

国外政策性金融的几点借鉴

鉴于国外发展政策性金融的有益经验,文章从四个方面提供了完善我国政策性金融机构的思路:政策性金融的适应性、政策性金融的可持续性、政策性金融的资金来源以及政策性金融的经营原则。     

论经济人的理性冲突及行为目标

基于经济人假设的传统经济理论认为人们具有完全理性能力,但现实中行为人的决策理性程度.经常处于完全理性与有限理性两种情境的转换之中.从研究范式和最终行为目标两个视角来看,完全理性情境下人们遵循最优化原则追求决策收益的最大化;而有限理性情境下则遵循决策收益和过程的满意原则.基于经济人的行为心理及认知能力来分析,追求主观幸福感最大化才是人类经济行为的最终唯一目标.建立于行为经济人基础上的经济发展理论与实践.才是一个国家和地区以人为本、和谐发展的必然要求.     

On the use of quasi-likelihood for estimation in hidden-Markov random fields

This paper illustrates the use of quasi-likelihood methods of inference for hidden Markov random fields. These are simple to use and can be employed under circumstances where only the model form and its covariance structure are specified. In particular they can be used to derive the same estimating equations as the E-M algorithm or change of measure methods, which make full distributional assumptions.     

Housing interventions for homeless,pregnant/parenting women with addictions: a systematic review

Family homelessness is a growing problem in North America with most of these families headed by single women. Homeless women also experience high rates of pregnancy and addiction (drugs and alcohol). Housing interventions have been identified as key to addressing the complex needs of pregnant/early parenting, homeless women with addictions. The aim of this systematic review is to determine what housing models and programs for this population yield the best outcomes. We systematically searched 10 databases and retrieved eight articles describing four distinct studies that met the inclusion criteria for this review. Overall, improved outcomes were found for all intervention groups with the most recent and rigorous studies favoring models combining Housing First and case management. However, methodological limitations, study quality, and varied outcomes made comparison across studies difficult. Further research must be done in this area using standardized outcomes and rigorous designs to develop evidence-based best practice guidelines to address the unique needs of this population.     

The time‐dependent “cure‐death” model investigating two equally important endpoints simultaneously in trials treating high‐risk patients with resistant pathogens

A variety of primary endpoints are used in clinical trials treating patients with severe infectious diseases, and existing guidelines do not provide a consistent recommendation. We propose to study simultaneously two primary endpoints, cure and death, in a comprehensive multistate cure‐death model as starting point for a treatment comparison. This technique enables us to study the temporal dynamic of the patient‐relevant probability to be cured and alive. We describe and compare traditional and innovative methods suitable for a treatment comparison based on this model. Traditional analyses using risk differences focus on one prespecified timepoint only. A restricted logrank‐based test of treatment effect is sensitive to ordered categories of responses and integrates information on duration of response. The pseudo‐value regression provides a direct regression model for examination of treatment effect via difference in transition probabilities. Applied to a topical real data example and simulation scenarios, we demonstrate advantages and limitations and provide an insight into how these methods can handle different kinds of treatment imbalances. The cure‐death model provides a suitable framework to gain a better understanding of how a new treatment influences the time‐dynamic cure and death process. This might help the future planning of randomised clinical trials, sample size calculations, and data analyses.