面板数据的贝叶斯Elastic Net分位数回归方法及其应用研究

本文首次将Elastic Net这种用于高度相关变量的惩罚方法用于面板数据的贝叶斯分位数回归,并基于非对称Laplace先验分布推导所有参数的后验分布,进而构建Gibbs抽样。为了验证模型的有效性,本文将面板数据的贝叶斯Elastic Net分位数回归方法(BQR. EN)与面板数据的贝叶斯分位数回归方法(BQR)、面板数据的贝叶斯Lasso分位数回归方法(BLQR)、面板数据的贝叶斯自适应Lasso分位数回归方法(BALQR)进行了多种情形下的全方位比较,结果表明BQR. EN方法适用于具有高度相关性、数据维度很高和尖峰厚尾分布特征的数据。进一步地,本文就BQR. EN方法在不同扰动项假设、不同样本量的情形展开模拟比较,验证了新方法的稳健性和小样本特性。最后,本文选取互联网金融类上市公司经济增加值(EVA)作为实证研究对象,检验新方法在实际问题中的参数估计与变量选择能力,实证结果符合预期。     

食管癌患者健康相关生命质量研究

目的:探讨食管癌患者的健康相关生命质量现状及影响因素?方法:采用一般资料问卷?欧洲五维度健康评定量表(EQ-5D量表),对209例食管癌患者进行问卷调查,采用单因素分析和多因素分析探讨食管癌患者健康相关生命质量的影响因素? 结果:食管癌患者行动?自我照顾?日常活动?疼痛/不适?焦虑/抑郁五个维度存在问题的比例分别为18.2%?12.0%?22.0%?38.3%?25.4%;自评健康得分(VAS评分)为(75.20 ± 11.00)分;综合健康指数得分(Index得分)为(0.84 ± 0.22)分?患者的性别?家庭年收入?文化程度是VAS评分的主要影响因素;患者的年龄?治疗方式?肿瘤分期?医保类型是Index得分的主要影响因素?结论:实施心理干预?早诊早治?大病医疗保险有助于提高食管癌患者健康相关生命质量?     

A visualization method measuring the performance of biomarkers for guiding treatment decisions

Biomarkers that predict efficacy and safety for a given drug therapy become increasingly important for treatment strategy and drug evaluation in personalized medicine. Methodology for appropriately identifying and validating such biomarkers is critically needed, although it is very challenging to develop, especially in trials of terminal diseases with survival endpoints. The marker‐by‐treatment predictiveness curve serves this need by visualizing the treatment effect on survival as a function of biomarker for each treatment. In this article, we propose the weighted predictiveness curve (WPC). Based on the nature of the data, it generates predictiveness curves by utilizing either parametric or nonparametric approaches. Especially for nonparametric predictiveness curves, by incorporating local assessment techniques, it requires minimum model assumptions and provides great flexibility to visualize the marker‐by‐treatment relationship. WPC can be used to compare biomarkers and identify the one with the highest potential impact. Equally important, by simultaneously viewing several treatment‐specific predictiveness curves across the biomarker range, WPC can also guide the biomarker‐based treatment regimens. Simulations representing various scenarios are employed to evaluate the performance of WPC. Application on a well‐known liver cirrhosis trial sheds new light on the data and leads to discovery of novel patterns of treatment biomarker interactions. Copyright © 2015 John Wiley & Sons, Ltd.     

油气田边远地区天然气资源的综合利用研究

油气田边远地区天然气资源包括油田放空天然气(主要是油田伴生气)和低产气井天然气,它们均因气量小,就地无用户和远离输气管网等原因长期未得到开发利用,不仅极大地浪费了资源,而且严重地污染了油田地区的大气。综述了国内外可用于油气田边远地区天然气资源开发利用的净化技术和综合利用技术,认为利用这部分天然气资源应依据气质、气量和市场需求选用合理的净化技术及利用技术,最后对吐哈油田边远地区天然气资源的综合利用进行了研究。     

Lassoing the Determinants of Retirement

This article uses Danish register data to explain the retirement decision of workers in 1990 and 1998. Many variables might be conjectured to influence this decision such as demographic, socioeconomic, financial, and health related variables as well as all the same factors for the spouse in case the individual is married. In total, we have access to 399 individual specific variables that all could potentially impact the retirement decision. We use variants of the least absolute shrinkage and selection operator (Lasso) and the adaptive Lasso applied to logistic regression in order to uncover determinants of the retirement decision. To the best of our knowledge, this is the first application of these estimators in microeconometrics to a problem of this type and scale. Furthermore, we investigate whether the factors influencing the retirement decision are stable over time, gender, and marital status. It is found that this is the case for core variables such as age, income, wealth, and general health. We also point out the most important differences between these groups and explain why these might be present.     

Power analysis for clustered non-continuous responses in multicenter trials

Power analysis for multi-center randomized control trials is quite difficult to perform for non-continuous responses when site differences are modeled by random effects using the generalized linear mixed-effects model (GLMM). First, it is not possible to construct power functions analytically, because of the extreme complexity of the sampling distribution of parameter estimates. Second, Monte Carlo (MC) simulation, a popular option for estimating power for complex models, does not work within the current context because of a lack of methods and software packages that would provide reliable estimates for fitting such GLMMs. For example, even statistical packages from software giants like SAS do not provide reliable estimates at the time of writing. Another major limitation of MC simulation is the lengthy running time, especially for complex models such as GLMM, especially when estimating power for multiple scenarios of interest. We present a new approach to address such limitations. The proposed approach defines a marginal model to approximate the GLMM and estimates power without relying on MC simulation. The approach is illustrated with both real and simulated data, with the simulation study demonstrating good performance of the method.     

基于扎根理论的茅山江南名山形象认知分析

江南名山是中国名山文化的重要组成部分,其形象的开发和利用为古代文人和知识分子所主导,是当前完善名山风景建设的关键因素,而诗词文本则是江南名山形象构建的见证。本文以江南名山茅山为研究案例,结合元代刘大彬所著《茅山志·金薤篇》中记载的茅山相关诗词及网络搜集的补充诗词为文本材料,运用扎根理论对文本内容进行三级编码,归纳形成包括山地、生物、天象、气象资源等在内的十五个初始范畴和自然资源、文化特征、审美活动、行为互动、建筑设施五个主范畴,进而利用文本分析软件ROST CM6进行词频分析、社会网络与语义网络分析、情感意象分析。分析发现诗词文本中自然资源构成了茅山风景区核心景观资源。情感意象分析发现,中性情感比重最大,"归隐"频次最高,反映出诗人普遍以茅山寄托隐居志向,积极情感多表达诗人对自然资源的由衷喜爱。最后构建江南名山形象塑造过程的模型,认为永嘉之乱后江南名山得到了发展,优越的自然条件作为风景要素,是形象认知的起点和自然供给力。宗教文化的发展进一步推动了山岳诗文的创作,二者构成重要的文化供给力。隐居和游观活动的兴盛则是江南名山文化吸引力的重要体现。总结得出了茅山江南名山形象,为后续江南名山形象认知的研究打下基础。     

人力资源能力建设与我国创新型国家的建立

建设创新型国家,关键是创新人才的培养和广泛参与,这需要通过人力资源能力建设来推动该目标的实现。在20世纪90年代的10年里,中国人力资源能力建设大幅度提高,但仍面临若干问题,为适应中国加快创新型国家建设的需要,需要借鉴发达国家在人力资源能力建设方面的经验,强化人力资源能力建设过程中的关键点。     

晚清民国时期蔗糖业视野下的广西城镇经济网络

晚清民国时期,广西蔗糖业经历了繁荣、衰落再发展的轨迹,通过商人的经营活动促进了城镇经济网络和蔗糖业的楔合,蔗糖业的发展推动了城镇经济网络的发展。蔗糖业和城镇经济网络的楔合促进了民族经济融合。