医疗需求与中国医疗费用增长——基于城乡老年医疗支出差异的视角

在人口老龄化和老年医疗支出城乡差异凸显的背景下,中国医疗费用增长部分源于合理的健康需求。利用中国营养与健康调查1991—2011年的八轮数据,构造出生组跟踪样本,分别考察城乡居民医疗支出的年龄效应,估算城乡老年医疗需求导致的费用上涨,可以发现:城市居民的人均医疗支出随年龄显著增加,但农村居民的人均医疗支出随年龄增长的趋势并不明显。而忽略出生组效应,会低估城乡老年医疗支出的差距。城乡老年医疗支出差距缩小,将导致医疗费用在2010—2030年年均实际增长约5.2%。在控制医疗总费用上涨的同时,医疗保险制度需根据老年医疗需求,调整医疗资源配置结构。     

Testing equality of two normal covariance matrices with monotone missing data

Abstract

The problem of testing equality of two multivariate normal covariance matrices is considered. Assuming that the incomplete data are of monotone pattern, a quantity similar to the Likelihood Ratio Test Statistic is proposed. A satisfactory approximation to the distribution of the quantity is derived. Hypothesis testing based on the approximate distribution is outlined. The merits of the test are investigated using Monte Carlo simulation. Monte Carlo studies indicate that the test is very satisfactory even for moderately small samples. The proposed methods are illustrated using an example.     

高含水期油藏层间压力结构差异量化方法研究

由于长期注水开发和层间非均质性影响，高含水期油藏各小层层间压力结构差异严重，掌握差异状况是合理调整的重要依据。针对现场分层测压资料少，单层压力资料获取困难的情况，应用渗流力学原理建立了高含水期地层层间压力结构差异量化数学模型，模型的关键参数可以通过生产数据计算获得。枣园油田的实例验证表明，高含水油藏层间压力存在明显差异，该方法能够确定各小层的压力差异状况。量化计算结果和实测资料相接近，有利于认清开发矛盾，为合理调整提供技术依据。     

领导干部党性修养评价机制研究

建立健全领导干部党性修养评价机制,是加强党的执政能力建设,建设高素质执政骨干队伍的客观需要。坚定的政治信念、牢固的党纪意识、严谨的自律能力、优秀的道德品质和勤勉的工作作风是评价领导干部党性修养的主要内容。要明确评价领导干部党性修养的指导思想、评价主体和评价原则,要建立健全领导干部党性修养的评价指标体系,不断探索科学的评价领导干部党性修养的方式方法。     

基于评价理论的APEC领导人宣言分析

2005年到2014年的APEC领导人宣言中的评价资源以借言为主，正面评价突出，其中鉴赏资源丰富，语势较强，立场分明。这些既体现出对话的和谐，又表明了领导人的决心和信心。2014年的领导人宣言的特点是亚太国家成果众多且认可度更高，特别鼓励区域内，以及政府与私营企业的战略性合作。     

支书和他的村庄——基于生命历程理论视角

在详细梳理西村张书记生命历程的基础上,利用生命历程理论的分析范式,将张书记的个人生命历程置于广阔的社会背景下进行研究,探讨了宏观社会背景、社会力量对张书记个人生命历程发展的影响,同时也阐述和强调了张书记个人主观能动性的发挥对自己生命轨迹和整个村庄经济收入、产业结构调整、农业技术推广、村民日常生活等带来的深刻变化。     

休闲活动与大学生心理健康

大学生对休闲活动认知有误区。参与休闲活动自觉性差、层次低、能力不够强。应积极引导、改变观念、提升层次、注重技能养成,丰富休闲方式,从而促进广大学生投身于休闲活动之中,达到心身健康教育与培养目的。     

丹巴土司制度发展历史考证

丹巴位于“藏彝走廊”的核心区域，其对汉藏民族关系、中央政权与边疆地区的稳定均具有重要影响。自忽必烈时期开始丹巴即开始实行土司制度直至新中国成立，研究丹巴的土司制度发展历史对梳理“藏彝走廊”民族关系及社会发展历史具有重要作用。本文对丹巴土司制度的发展历史进行了考证，并对其境内的四个土司的管辖范围、权力地位进行了梳理，以期对该地区历史发展研究提供一些参考与借鉴。     

Reducing sample size needed for cox-proportional hazards model analysis using more efficient sampling method

Abstract

In general, survival data are time-to-event data, such as time to death, time to appearance of a tumor, or time to recurrence of a disease. Models for survival data have frequently been based on the proportional hazards model, proposed by Cox. The Cox model has intensive application in the field of social, medical, behavioral and public health sciences. In this paper we propose a more efficient sampling method of recruiting subjects for survival analysis. We propose using a Moving Extreme Ranked Set Sampling (MERSS) scheme with ranking based on an easy-to-evaluate baseline auxiliary variable known to be associated with survival time. This paper demonstrates that this approach provides a more powerful testing procedure as well as a more efficient estimate of hazard ratio than that based on simple random sampling (SRS). Theoretical derivation and simulation studies are provided. The Iowa 65+ Rural study data are used to illustrate the methods developed in this paper.     

A New Methodology for Before–After Safety Assessment Using Survival Analysis and Longitudinal Data

The widely used empirical Bayes (EB) and full Bayes (FB) methods for before–after safety assessment are sometimes limited because of the extensive data needs from additional reference sites. To address this issue, this study proposes a novel before–after safety evaluation methodology based on survival analysis and longitudinal data as an alternative to the EB/FB method. A Bayesian survival analysis (SARE) model with a random effect term to address the unobserved heterogeneity across sites is developed. The proposed survival analysis method is validated through a simulation study before its application. Subsequently, the SARE model is developed in a case study to evaluate the safety effectiveness of a recent red‐light‐running photo enforcement program in New Jersey. As demonstrated in the simulation and the case study, the survival analysis can provide valid estimates using only data from treated sites, and thus its results will not be affected by the selection of defective or insufficient reference sites. In addition, the proposed approach can take into account the censored data generated due to the transition from the before period to the after period, which has not been previously explored in the literature. Using individual crashes as units of analysis, survival analysis can incorporate longitudinal covariates such as the traffic volume and weather variation, and thus can explicitly account for the potential temporal heterogeneity.