Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.     

A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.     

Inference for the measurement of poverty in the presence of a stochastic weighting variable

Empirical applications of poverty measurement often have to deal with a stochastic weighting variable such as household size. Within the framework of a bivariate distribution function defined over income and weight, I derive the limiting distributions of the decomposable poverty measures and of the ordinates of stochastic dominance curves. The poverty line is allowed to depend on the income distribution. It is shown how the results can be used to test hypotheses concerning changes in poverty. The inference procedures are briefly illustrated using Belgian data. An erratum to this article can be found at     

话语含义的判别和听力理解

语义层面上语用含义的话语理解是大学英语教学的难点之所在。为加强薄弱环节,须从“会话含义”和“关联”理论出发,揭示话语中交际意图传递的规律和特征,并结合实例分析听力理解过程中可能出现的信息推理障碍及原因。     

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.     

经贸院系英语教学模式探讨

分析目前我国英语教学与研究的误区。提出经贸院系学生应达到的英语水平目标；探讨经贸院系英语教学可采取六种教学模式。     

翻译:意识形态的建构、解构、重建与解读

翻译不仅是语言之间信息转换的文化活动,而且是一系列复杂的思维活动。意识形态以不同的语言形式隐藏在语篇之中,以各种隐蔽方式潜移默化地影响着作者写作、译者翻译以及读者解读文本。本文拟以批评语言学为主要方法论,强调翻译中语言分析和社会分析相结合的重要性,同时主张翻译研究应以语篇为单位,特别注意考察作者、译者、读者在翻译过程中的三元关系及其在意识形态的建构、解构、重建和解读过程中的作用,以便弄清翻译的本质并有效地解释那些"不忠"的现象。     

三螺旋创新模式的理论探讨

基于非线性网状创新模型提出的“三螺旋场”和“三螺旋循环”概念进一步推进了三螺旋创新模式的理论研究。三螺旋场概念旨在解释在大学、产业和政府三股螺旋之间存在的相对独立和彼此作用的本质，说明三螺旋的生成原理、静态表现和动态演化特征。三螺旋的生成原理在于创新过程的非线性本质和多主体特征，静态表现为“内核外场模型”，而动态演化过程则在于纵向进化和横向循环。发生在三股螺旋之间的三螺旋循环揭示了在大学、产业和政府之间以人员、信息和产品流动为特征的相互作用和运行机制。     

濮城油田沙二上1砂组末端扇沉积体系研究

曲流河、辫状河、网状河和若干三角洲的沉积模式目前已成为对比和解释古河流岩石层序的标准框架。但是，近来的野外资料和钻井资料证明，应该把末端扇模式加入上述沉积模式表中。末端扇的作用、地貌、有关的沉积物及沉积学特征相比河流体系及三角洲体系差距较大。通过大量的岩芯观察和描述，结合测井资料、区域地质资料及各项分析鉴定资料等进行综合分析，对东濮凹陷濮城油田沙二上亚段1砂组的沉积特征与沉积相进行了较全面的分析，认为该地区主要为末端扇沉积体系，在对末端扇的岩性、沉积相序、沉积微相特征分析的基础上，研究了末端扇的识别标志并建立了末端扇的沉积模式。