Profile Likelihood Inferences on the Partially Linear Model with a Diverging Number of Parameters

In this article, we study the profile likelihood estimation and inference on the partially linear model with a diverging number of parameters. Polynomial splines are applied to estimate the nonparametric component and we focus on constructing profile likelihood ratio statistic to examine the testing problem for the parametric component in the partially linear model. Under some regularity conditions, the asymptotic distribution of profile likelihood ratio statistic is proposed when the number of parameters grows with the sample size. Numerical studies confirm our theory.     

SPECIAL ISSUE： RECONSTRUCTING THE GENEALOGY OF CONFUCIANISM： XUN ZI＇S THOUGHT AND HIS HISTORICAL IMAGEIntroduction

Xun Zi （c. 336 BC-238 BC; given name Kuang）, who lived in the State of Zhao （now Handan City, Hebei Province） during the Warring States period, was a great thinker and educator. As the last master of Confucianism in the Pre-Qin period, he established his own system of thought by inheriting and developing that of Confucius and assimilating the achievements of other contemporary philosophers. His scholarly thought had a great influence on later ages. The spread of the Five Classics （The Book of Songs, The Book of Documents, The Book of Rites, The Book of Changes and The Spring and Autumn Annals） in the Hart Dynasty owed almost entirely to his disciples. From the Han to the Tang, people such as Sima Qian, Liu Xiang, Wang Chong, Yan Zhitui, Wei Zheng and Yang Jing put Xun Zi ahead of Mencius, showing that his influence outweighed the latter＇s. Xun Zi＇s philosophy lay at the heart of thinking on state administration in the Han and Tang, two of the most prosperous dynasties in Chinese history.     

Conditional screening for ultra-high dimensional covariates with survival outcomes

Identifying important biomarkers that are predictive for cancer patients’ prognosis is key in gaining better insights into the biological influences on the disease and has become a critical component of precision medicine. The emergence of large-scale biomedical survival studies, which typically involve excessive number of biomarkers, has brought high demand in designing efficient screening tools for selecting predictive biomarkers. The vast amount of biomarkers defies any existing variable selection methods via regularization. The recently developed variable screening methods, though powerful in many practical setting, fail to incorporate prior information on the importance of each biomarker and are less powerful in detecting marginally weak while jointly important signals. We propose a new conditional screening method for survival outcome data by computing the marginal contribution of each biomarker given priorily known biological information. This is based on the premise that some biomarkers are known to be associated with disease outcomes a priori. Our method possesses sure screening properties and a vanishing false selection rate. The utility of the proposal is further confirmed with extensive simulation studies and analysis of a diffuse large B-cell lymphoma dataset. We are pleased to dedicate this work to Jack Kalbfleisch, who has made instrumental contributions to the development of modern methods of analyzing survival data.     

农村人力资本的投资现状及其对就业的影响分析

应用实证分析方法,研究中国农村人力资本的投资现状及其对就业的影响,结果表明:近年来,由于农村人力资本投资主体的经济实力弱,投资收益滞后,接受教育、享受医疗保健的机会不均等,使农村人力资本投资绝对值虽然逐年提高,但增长幅度较小,这影响农村人力资本含量的提高,制约其就业能力的增强.因此,必须在制度安排与政策取向层面上进行创新,加大对农村基础教育的投资,发展农村医疗卫生事业,提高农村人力资本的含量,为农村劳动力的就业奠定基础.     

Ratio index variables or ANCOVA? Fisher's cats revisited

Over 60 years ago Ronald Fisher demonstrated a number of potential pitfalls with statistical analyses using ratio variables. Nonetheless, these pitfalls are largely overlooked in contemporary clinical and epidemiological research, which routinely uses ratio variables in statistical analyses. This article aims to demonstrate how very different findings can be generated as a result of less than perfect correlations among the data used to generate ratio variables. These imperfect correlations result from measurement error and random biological variation. While the former can often be reduced by improvements in measurement, random biological variation is difficult to estimate and eliminate in observational studies. Moreover, wherever the underlying biological relationships among epidemiological variables are unclear, and hence the choice of statistical model is also unclear, the different findings generated by different analytical strategies can lead to contradictory conclusions. Caution is therefore required when interpreting analyses of ratio variables whenever the underlying biological relationships among the variables involved are unspecified or unclear. Copyright © 2009 John Wiley & Sons, Ltd.     

构建山东半岛蓝色旅游经济区的思考

蓝色旅游经济应该包括海洋旅游、海岛旅游、滨海旅游,以及与海洋文化有关的临海陆上旅游。山东半岛在海洋开发政策、海洋资源、海洋经济、滨海旅游、旅游基础设施方面都具备了建设山东半岛蓝色旅游经济区的条件。建设山东半岛蓝色旅游经济区,宏观上要大力发展蓝色旅游经济;中观上要支持蓝色旅游产业板块发展;微观上要打造具有蓝色旅游特色的旅游商品。     

县级政府规模影响因素的实证研究——以四川省为例

以2007年四川省177个县级行政单位为样本,考察县级政府规模与经济发展水平、常住人口数量、管辖区域面积之间的相关关系。研究结果表明,经济发展水平、常住人口数量、管辖区域面积三大因素对县级政府规模存在不同程度的影响,充分考虑这些影响因素,可以为优化并确立合理的政府规模提供有价值的政策建议。     

促进西部地区健身服务业发展的对策思考

通过对西部地区体育健身服务业发展的现状分析,结合地区和民族特色,探索了区域性小康社会体育结构要素的发展变化规律,服务于地区性体育事业的改革与发展,提出全面建设小康社会,积极推动西部地区体育健身服务业快速发展的对策与建议。     

留守与流动儿童登记与调查体系的设计与实施

 本文通过对留守与流动儿童定义分歧的梳理及要素特征分析,明确“留守”与“流动”儿童的概念、内涵与外延;设计以“户籍资料”为基础,分别构建以“教育部门”、“公安部门”为主的留守、流动儿童登记体系,建立关于留守与流动儿童登记的长效机制。针对留守与流动儿童这两类特殊群体,设计研究的调查表,该表由基本信息与综合信息两部分组成,并构建以“登记表信息及户籍信息”为依据,以“统计部门为主”统计调查体系。通过留守与流动儿童登记与调查体系的设计,并加以实施,便于准确地掌握情况、了解问题,为留守与流动儿童的学术研究提供基础的信息资料,为相关部门制定对策提供必要的依据。     

Asymptotic results for fitting marginal hazards models from stratified case-cohort studies with multiple disease outcomes

In stratified case-cohort designs, samplings of case-cohort samples are conducted via a stratified random sampling based on covariate information available on the entire cohort members. In this paper, we extended the work of Kang & Cai (2009) to a generalized stratified case-cohort study design for failure time data with multiple disease outcomes. Under this study design, we developed weighted estimating procedures for model parameters in marginal multiplicative intensity models and for the cumulative baseline hazard function. The asymptotic properties of the estimators are studied using martingales, modern empirical process theory, and results for finite population sampling.