On inference for Kendall's τ within a longitudinal data setting

Kendall's τ is a non-parametric measure of correlation based on ranks and is used in a wide range of research disciplines. Although methods are available for making inference about Kendall's τ, none has been extended to modeling multiple Kendall's τs arising in longitudinal data analysis. Compounding this problem is the pervasive issue of missing data in such study designs. In this article, we develop a novel approach to provide inference about Kendall's τ within a longitudinal study setting under both complete and missing data. The proposed approach is illustrated with simulated data and applied to an HIV prevention study.     

基于《论语》视角的高校基层管理人员自我价值感的提升

高校基层管理人员自我价值感的状况,直接地影响着这个群体潜能的发挥和工作绩效的提高。目前,对部分高校基层管理人员来说,工作的事务性、程序性和职位与职称晋升的障碍使自我价值感降低。运用《论语》中的相关心灵策略,树立远大的职业理想,正确客观地认识自己,培育从容的平和心态,可一定程度上提高自我价值感。     

Mean estimation with data missing at random for functional covariables

In a missing-data setting, we want to estimate the mean of a scalar outcome, based on a sample in which an explanatory variable is observed for every subject while responses are missing by happenstance for some of them. We consider two kinds of estimates of the mean response when the explanatory variable is functional. One is based on the average of the predicted values and the second one is a functional adaptation of the Horvitz–Thompson estimator. We show that the infinite dimensionality of the problem does not affect the rates of convergence by stating that the estimates are root-n consistent, under missing at random (MAR) assumption. These asymptotic features are completed by simulated experiments illustrating the easiness of implementation and the good behaviour on finite sample sizes of the method. This is the first paper emphasizing that the insensitiveness of averaged estimates, well known in multivariate non-parametric statistics, remains true for an infinite-dimensional covariable. In this sense, this work opens the way for various other results of this kind in functional data analysis.     

世纪之交的拉美左派评析

世纪之交,拉美左派运动正在走向一个新的发展阶段,这不仅有利于拉美地区政治经济的发展,而且对整个国际关系会产生深远的影响。因此,要在新的时代背景下,从历史的角度,客观地认识拉美左翼的崛起和它进一步发展的必然性。     

Empirical likelihood confidence bands for distribution functions with missing responses

Distribution function estimation plays a significant role of foundation in statistics since the population distribution is always involved in statistical inference and is usually unknown. In this paper, we consider the estimation of the distribution function of a response variable Y with missing responses in the regression problems. It is proved that the augmented inverse probability weighted estimator converges weakly to a zero mean Gaussian process. A augmented inverse probability weighted empirical log-likelihood function is also defined. It is shown that the empirical log-likelihood converges weakly to the square of a Gaussian process with mean zero and variance one. We apply these results to the construction of Gaussian process approximation based confidence bands and empirical likelihood based confidence bands of the distribution function of Y. A simulation is conducted to evaluate the confidence bands.     

出生性别比综合治理:有所为,有所不为

从1980年我国出生性别比越过正常值域至今,党和各级政府制订了种种措施进行综合治理,但取得的成效甚微。这一时期我国治理工作的特点有:重视禁止性法律法规的制定,但与之相配套的规章制度比较缺乏;重视目标任务的提出,但落实目标的措施比较缺乏;部门性、专项性规章制度较多,综合性规章制度比较缺乏。今后一段时期内综合治理工作,可以按照避实就虚、避难就易的原则,在大力发展社会经济、建立健全社会养老制度、相关法律法规的制定与完善、加大对两非行为的打击力度等方面有所作为;而在人口生育政策的调整、传统文化的改变等方面有所不为。     

“江郎才尽”新解

“颠覆阅读”的“难以为继”，在文学史上的印证就是“江郎才尽”。对“江郎才尽”，文学史上有多种解释，此处认为，江淹是以“颠覆阅读”的手段来使自己的诗歌达到一种独特性，故意用一种怪诞或隐晦的文风，用一种奇哨怪仄的意境或修辞手段，来实现自己诗歌的新鲜感甚或冲击力，以震撼人们视觉、听觉，但这种文风难以为继，文学史告诉我们，“颠覆阅读”也是需要创新的。     

提高深圳出生人口素质的理论与思考

本文通过全面回顾深圳市在提高出生人口素质，预防出生缺陷方面的机构设置、工作方法，分析了深圳提高出生人口素质面临的挑战．并从政策分析的角度提出了提高出生人口素质的政策建议。     

Risk-Reducing Legal Documents: Controlling Personal Health and Financial Resources

Every adult can eliminate the risk of losing control of personal health decisions and financial resources by having a last will and testament, health proxy, power of attorney, and living trust. Yet evidence suggests that less than a majority of adult Americans have these documents. We surveyed 900 adult Americans (25 plus years old) to determine what factors predict the possession of these risk-reducing documents. In total, 46% had a living will and testament, 32% a durable power of attorney, 30% a health proxy, and 18% a living trust. Events that prompt people with wealth to secure these documents, such as increasing age, getting married, having children, and experiencing a life-threatening event were the strongest predictors of having a will. These were also among the strongest predictors of having a health proxy, along with a personal history of being proactive, and a family history that fostered trust of attorneys. Affluence, age, and education were the strongest predictors of having a living trust, and the strongest correlate of having a durable power of attorney was having faced a life-threatening event, positive experiences with attorneys, and higher educational achievement.     

Failure Probability Under Parameter Uncertainty

In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location‐scale families (including the log‐normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications.