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.     

从人道主义向自然主义迈进的福克纳——读《我弥留之际》

美国南方流派的代表作家威廉·福克纳是一位实验性的作家,在他的文学生涯中,他做过多种尝试,他的早期长篇小说《我弥留之际》是其中非常重要的一次。这部作品的创作思想显示福克纳在上世纪30年代从人道主义向自然主义迈进。     

我国期货市场的法规探讨

本文阐述了期货市场法律规范的基本原则和主要功能，介绍了我国期货市场的近期发展与法规现状，并对我国期贷市场法律规范的基本原则与体系设置作了探讨。     

逆向物流及其整合分析

逆向物流是物流管理的一个新的领域,已经引起理论界和企业界越来越多的关注。逆向物流可以降低企业成本,提高顾客满意度,并最终提升企业的竞争力,这对我国企业实践具有重要意义。     

如何在英语教学中实施素质教育

素质教育主要是指文化素质教育、思想品德教育、心理素质教育和生理素质教育。英语教学中的素质教育主要是从以下三个方面得以体现的：(1)提高教师自身素质是实施素质教育的基本保证。(2)建立科学合理的测试评估体系是实施素质教育的重要保证。(3)改进教学方法是实施素质教育的必要条件。     

Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models

Outlier detection algorithms are intimately connected with robust statistics that down‐weight some observations to zero. We define a number of outlier detection algorithms related to the Huber‐skip and least trimmed squares estimators, including the one‐step Huber‐skip estimator and the forward search. Next, we review a recently developed asymptotic theory of these. Finally, we analyse the gauge, the fraction of wrongly detected outliers, for a number of outlier detection algorithms and establish an asymptotic normal and a Poisson theory for the gauge.     

中国服务业显性比较优势测算——基于前向联系增加值出口

基于"前向联系增加值出口"方法,测算了1995-2011年中国服务业细分产业层面及按要素密集度特征分类层面的显性比较优势指数(RCA_F),并同基于"总出口"1的比较优势指数(RCA)进行了比较。研究发现,中国在全球价值链分工中,比较优势集中在资本密集型服务业领域,且实现了比较劣势向比较优势的转变;劳动、知识密集型服务业及健康教育公共服务均尚未取得比较优势,但是有迹象表明三个领域的比较劣势有改善的趋势。与基于前向联系增加值出口核算结果相比,基于总出口核算结果"高估"了劳动密集型产业的比较优势,其中对建筑业和零售贸易两个部门的估计偏差最大;同时,在资本、知识密集型两个领域存在不同程度的"低估"现象。     

Affine LIBOR models driven by real-valued affine processes

The class of affine LIBOR models is appealing since it satisfies three central requirements of interest rate modeling. It is arbitrage-free, interest rates are nonnegative, and caplet and swaption prices can be calculated analytically. In order to guarantee nonnegative interest rates affine LIBOR models are driven by nonnegative affine processes, a restriction that makes it hard to produce volatility smiles. We modify the affine LIBOR models in such a way that real-valued affine processes can be used without destroying the nonnegativity of interest rates. Numerical examples show that in this class of models, pronounced volatility smiles are possible.     

无套利分析在非完美条件下远期合约定价中的运用

无套利分析方法是现代金融理论的基石之一,已成为金融衍生品定价的一种重要方法,传统的金融工程教科书很少涉及非完美条件下远期合约的定价问题。在介绍无套利分析方法的基础上,通过现金流复制技术,研究了三种非完美条件下远期合约的定价问题。     

论西部大开发中穆斯林优良传统的弘扬

中国有近 2 0 0 0万穆斯林 ,其中大部分在西部地区 ,如何为西部大开发做出自己的贡献 ,是一个值得研究的课题。文章认为 ,广大穆斯林应该充分弘扬伊斯兰的优良传统 ,为西部大发展创造一个良好的环境。而弘扬穆斯林的优良传统 ,就必须正确认识宗教与社会主义相适应和中华民族多元一体的基本内涵