Examples of the use of an equivalence theorem in constructing optimum experimental designs for random-effects nonlinear regression models

The problem considered is that of finding an optimum measurement schedule to estimate population parameters in a nonlinear model when the patient effects are random. The paper presents examples of the use of sensitivity functions, derived from the General Equivalence Theorem for D-optimality, in the construction of optimum population designs for such schedules. With independent observations, the theorem applies to the potential inclusion of a single observation. However, in population designs the observations are correlated and the theorem applies to the inclusion of an additional measurement schedule. In one example, three groups of patients of differing size are subject to distinct schedules. Numerical, as opposed to analytical, calculation of the sensitivity function is advocated. The required covariances of the observations are found by simulation.     

Non-ignorable missing covariate data in survival analysis: a case-study of an International Breast Cancer Study Group trial

Summary.  Non-ignorable missing data, a serious problem in both clinical trials and observational studies, can lead to biased inferences. Quality-of-life measures have become increasingly popular in clinical trials. However, these measures are often incompletely observed, and investigators may suspect that missing quality-of-life data are likely to be non-ignorable. Although several recent references have addressed missing covariates in survival analysis, they all required the assumption that missingness is at random or that all covariates are discrete. We present a method for estimating the parameters in the Cox proportional hazards model when missing covariates may be non-ignorable and continuous or discrete. Our method is useful in reducing the bias and improving efficiency in the presence of missing data. The methodology clearly specifies assumptions about the missing data mechanism and, through sensitivity analysis, helps investigators to understand the potential effect of missing data on study results.     

Statistical and Combinatorial Aspects of Comparative Genomics*

Abstract. This document presents a survey of the statistical and combinatorial aspects of four areas of comparative genomics: gene order based measures of evolutionary distances between species, construction of phylogenetic trees, detection of horizontal transfer of genes, and detection of ancient whole genome duplications.     

On Optimality of Bayesian Wavelet Estimators

Abstract.  We investigate the asymptotic optimality of several Bayesian wavelet estimators, namely, posterior mean, posterior median and Bayes Factor, where the prior imposed on wavelet coefficients is a mixture of a mass function at zero and a Gaussian density. We show that in terms of the mean squared error, for the properly chosen hyperparameters of the prior, all the three resulting Bayesian wavelet estimators achieve optimal minimax rates within any prescribed Besov space     for p  ≥ 2. For 1 ≤  p  < 2, the Bayes Factor is still optimal for (2 s +2)/(2 s +1) ≤  p  < 2 and always outperforms the posterior mean and the posterior median that can achieve only the best possible rates for linear estimators in this case.     

Assessing goodness-of-fit of categorical regression models based on case-control data

Demonstrated equivalence between a categorical regression model based on case‐control data and an I‐sample semiparametric selection bias model leads to a new goodness‐of‐fit test. The proposed test statistic is an extension of an existing Kolmogorov–Smirnov‐type statistic and is the weighted average of the absolute differences between two estimated distribution functions in each response category. The paper establishes an optimal property for the maximum semiparametric likelihood estimator of the parameters in the I‐sample semiparametric selection bias model. It also presents a bootstrap procedure, some simulation results and an analysis of two real datasets.     

谭献词学理论的继承与创新

谭献是晚清一位词学大家 ,在继承常州派张惠言、周济词学理论的基础上 ,根据自己创作和整理词集的经验和心得 ,提出了新的词学观点 ,进一步完善了常州派词论 ,对中国词学理论有杰出的贡献。谭献的词论主要有 :一、继承常州词派的观点 ,继续推尊词体。二、在词的创作方面 ,提倡比兴柔厚。三、在词的鉴赏批评上 ,提出“作者之用心未必然 ,读者之用心何必不然”的著名观点。     

提高我国文化软实力的意义与对策

文化软实力是综合国力和国际竞争力的重要组成部分,我国要在激烈的国际竞争中赢得主动,就必须使国家文化软实力有一个大的提高。为此,要构建社会主义核心价值体系,努力提高国民综合素质;加强文化交流与传播,提高中华文化的渗透力;推进文化创新和文化体制改革,充分发掘中华传统文化的优势;在公共文化服务体系建设中,加强基层文化建设,以城市社区文化建设和农村文化建设为落点;建立产品丰富、门类齐全、结构合理、运行规范的文化市场体系,运用高新技术创新文化生产方式,培育新的文化业态,加快构建传输快捷、覆盖广泛的文化传播体系。     

绿色供应链管理动力/压力影响模型实证研究

文章借鉴国外文献及国内环保专家的意见设计问卷进行调研,通过因子分析识别出中国制造企业绿色供应链管理的压力/动力和实践的主要因子.对因子进行相关分析和回归分析,根据数据结合国内外相关情况探讨动力/压力是如何影响绿色供应链管理实践,提出中国制造企业绿色供应链管理的动力/压力影响模型.     

统计执法的博弈分析

针对目前中国统计数据失真相当严重并引起社会各界普遍关注的现象，运用博弈论作为分析工具，引入重复博弈研究了统计执法中数据报方与查方的利益冲突关系，从统计执法的角度揭示了统计数据失真的主要原因，并提出了相应的五项对策。     

五项执政能力建设对高校研究生党组织工作的启示

十六届四中全会提出的加强党的五项执政能力建设,对于高校的党建工作和人才培养具有重要的指导意义.树立以五项执政能力教育为核心的党员全面发展观,是做好新时期研究生基层党建工作、促进研究生党员的全面发展、为国家输送更多的高素质人才的迫切需要.