Correlation Coefficient Revisited

Elementary approaches to prove basic properties of the correlation coefficient are of pedagogical interest. Besides posing another proof, this article gives variations of the proofs already existing in the statistical literature     

Complete convergence for arrays of rowwise negatively superadditive-dependent random variables and its applications

In this paper, the Rosenthal-type maximal inequalities and Kolmogorov-type exponential inequality for negatively superadditive-dependent (NSD) random variables are presented. By using these inequalities, we study the complete convergence for arrays of rowwise NSD random variables. As applications, the Baum–Katz-type result for arrays of rowwise NSD random variables and the complete consistency for the estimator of nonparametric regression model based on NSD errors are obtained. Our results extend and improve the corresponding ones of Chen et al. [On complete convergence for arrays of rowwise negatively associated random variables. Theory Probab Appl. 2007;52(2):393–397] for arrays of rowwise negatively associated random variables to the case of arrays of rowwise NSD random variables.     

Case–control genome-wide joint association study using semiparametric empirical model and approximate Bayes factor

We propose a semiparametric approach for the analysis of case–control genome-wide association study. Parametric components are used to model both the conditional distribution of the case status given the covariates and the distribution of genotype counts, whereas the distribution of the covariates are modelled nonparametrically. This yields a direct and joint modelling of the case status, covariates and genotype counts, and gives a better understanding of the disease mechanism and results in more reliable conclusions. Side information, such as the disease prevalence, can be conveniently incorporated into the model by an empirical likelihood approach and leads to more efficient estimates and a powerful test in the detection of disease-associated SNPs. Profiling is used to eliminate a nuisance nonparametric component, and the resulting profile empirical likelihood estimates are shown to be consistent and asymptotically normal. For the hypothesis test on disease association, we apply the approximate Bayes factor (ABF) which is computationally simple and most desirable in genome-wide association studies where hundreds of thousands to a million genetic markers are tested. We treat the approximate Bayes factor as a hybrid Bayes factor which replaces the full data by the maximum likelihood estimates of the parameters of interest in the full model and derive it under a general setting. The deviation from Hardy–Weinberg Equilibrium (HWE) is also taken into account and the ABF for HWE using cases is shown to provide evidence of association between a disease and a genetic marker. Simulation studies and an application are further provided to illustrate the utility of the proposed methodology.     

Causal inference for recurrent events data with all-or-none compliance

ABSTRACT

In this article, causal inference in randomized studies with recurrent events data and all-or-none compliance is considered. We use the counting process to analyze the recurrent events data and propose a causal proportional intensity model. The maximum likelihood approach is adopted to estimate the parameters of the proposed causal model. To overcome the computational difficulties created by the mixture structure of the problem, we develop an expectation-maximization (EM) algorithm. The resulting estimators are shown to be consistent and asymptotically normal. We further estimate the complier average causal effect (CACE), which is defined as the difference of the average numbers of recurrence between treatment and control groups within the complier class. The corresponding inferential procedures are established. Some simulation studies are conducted to assess the finite sample performance of the proposed approach.     

Bayesian estimation of multidimensional item response theory model using gibbs sampling

We propose Bayesian parameter estimation in a multidimensional item response theory model using the Gibbs sampling algorithm. We apply this approach to dichotomous responses to a questionnaire on sleep quality. The analysis helps determine the underlying dimensions.     

Approximating discrete multivariate distributions prom known moments

To approximate the joint distribution of the two-colony stepping-stone model, a finite mixture approach is proposed for constructing discrete multi-variate distributions. This approach generahzes the classic method of linear combinations of independent variables. The stepping-stone model is approximated through matching known moments. Numerical examples from entomology are given. Comparisons are made with the work by Wehrly et al (1993).     

20世纪以来藏族部落纠纷解决方式研究述论

20世纪初至80年代末的很长一段时期,藏族部落纠纷解决研究多以对史料的挖掘、评述(国内)和田野深耕(国外)为主.进入社会转型期,藏族传统方式与司法的关系愈趋微妙、复杂,给藏牧区的纠纷解决实践带来诸多新的问题.正因此,学者逐渐转向藏族部落传统解纷方式在当代的表达之争.进入21世纪,更多的学者加入了这一行列,并取得了许多有价值的研究成果,同时也反映出一些问题与不足.本文拟对国内外的主要调查研究成果加以综述,并就某些问题提出自己的看法,以期为进一步的分析研究奠定基础.     

文化视野下的汉语民族性特点

汉语的民族性特点是在与其他民族语长期接触和融合过程中形成的.文章立足于中西文化和中华文化广阔视域,从语词类聚、句法组织、修辞方式、表达习惯等角度对汉语的民族性特点进行了全面描写,同时结合民族历史、政治制度、社会背景、价值观念、认知心理等诸因素,给予了发生学解释.     

如何定义“大国”？

 摘　　要:本文通过对各种关于“大国”定义的总结和分析，根据经济学原理给出了关于经济学意义的“大国”的定义。并分析了这种定义的优势，以及在该定义下进一步研究“大国”问题的方向     

关于改进我国现行科技统计年报设计问题的探讨

一、改进我国现行科技统计年报制度的必要性　　（一）我国现行统计年报制度中存在的问题科技统计是指对科技活动的投入、活动、产出等方面进行统计,是统计活动的一个重要组成部分。我国于１９８６年建立了科技统计的年报制度,经过十几年的运行,该制度取得了很大的成绩,但也暴露出一些问题。（１）现行科技统计指标的统计口径狭小,不能反映我国科技活动的实际。从国际上看,最主要科技统计指标是Ｒ＆Ｄ活动的指标。Ｒ＆Ｄ活动的特点是新颖性和创新性,但实际上Ｒ＆Ｄ活动与生产活动之间还有许多科技活动,显然这些活动不属于Ｒ＆Ｄ活动…