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.     

地区信息化水平的综合评价

本文从信息化的发展入手,阐述了信息化建设及各地区信息化水平评价的重要性,采用多元统计中的主成分分析和主成分回归法,设计一个综合指标用以评估各类地区的信息化水平及其在全国所处的位置,指导各地区的信息化建设。     

Choice of the primary analysis in longitudinal clinical trials

Missing data, and the bias they can cause, are an almost ever‐present concern in clinical trials. The last observation carried forward (LOCF) approach has been frequently utilized to handle missing data in clinical trials, and is often specified in conjunction with analysis of variance (LOCF ANOVA) for the primary analysis. Considerable advances in statistical methodology, and in our ability to implement these methods, have been made in recent years. Likelihood‐based, mixed‐effects model approaches implemented under the missing at random (MAR) framework are now easy to implement, and are commonly used to analyse clinical trial data. Furthermore, such approaches are more robust to the biases from missing data, and provide better control of Type I and Type II errors than LOCF ANOVA. Empirical research and analytic proof have demonstrated that the behaviour of LOCF is uncertain, and in many situations it has not been conservative. Using LOCF as a composite measure of safety, tolerability and efficacy can lead to erroneous conclusions regarding the effectiveness of a drug. This approach also violates the fundamental basis of statistics as it involves testing an outcome that is not a physical parameter of the population, but rather a quantity that can be influenced by investigator behaviour, trial design, etc. Practice should shift away from using LOCF ANOVA as the primary analysis and focus on likelihood‐based, mixed‐effects model approaches developed under the MAR framework, with missing not at random methods used to assess robustness of the primary analysis. Copyright © 2004 John Wiley & Sons, Ltd.     

Public Perceptions about Food Safety in the United States and Japan1

Abstract Consumer concerns over pesticide residues and food additives have been growing in industrialized societies, including the United States and Japan. However, little comparative research has been carried out to determine which household characteristics may be significantly associated with these heightened concerns, and whether or not the same factors are useful for understanding variation in these worries in more than one society. This paper examines food safety attitudes in Seattle, Washington, and Kobe, Japan, and discovers that while the absolute level of expressed concern is higher in Kobe, the predictive power of household characteristics in explaining attitudinal differences within countries is similar. Implications for rural areas and future research on family structures in capitalist societies are discussed.     

Erroneous perceptions and arousal among regular and occasional video poker players

This study investigated the relationship between the level of arousal (Heart Rate) and the number of erroneous perceptions among video poker players. Twelve regular and twelve occasional gamblers participated in a gambling session conducted in a natural environment. It was hypothesised that 1) a significant positive correlation would be observed between arousal and the number of erroneous verbalizations, 2) regular players would show a higher level of arousal than occasional players, and 3) they would emit more erroneous verbalizations. Results showed that hypotheses one and three were confirmed. Theoretical and practical implications of these results for the psychology of gambling are discussed.This study was supported by a grant from Loto-Québec.     

司法现代化在我国农村的困境及出路

司法现代化在农村正遭遇着种种困境,这有其深刻的历史背景和现实基础。实现农村的司法现代化,一方面要对传统法律文化进行认真彻底的反思,肃清沿袭至今的消极影响;另一方面则应从制度上保障司法的公正性,在司法领域树立法律的权威。     

数学分析中基本概念的教学

通过导数、数列极限、函数的连续性和函数项级数不一致收敛等概念的教学 ,阐明了数学分析中基本概念教学的重要性     

A simple procedure for the selection of significant effects

Summary.  Given a large number of test statistics, a small proportion of which represent departures from the relevant null hypothesis, a simple rule is given for choosing those statistics that are indicative of departure. It is based on fitting by moments a mixture model to the set of test statistics and then deriving an estimated likelihood ratio. Simulation suggests that the procedure has good properties when the departure from an overall null hypothesis is not too small.     

Using computers to develop concept models of social situations

Concept modeling is presented as a way to describe and understand social situations. Concepts are developed from field data and supported by sets of exemplars drawn from the data which illustrate the various concepts. The computer is considered an essential tool for conducting this type of qualitative data analysis and displaying the resulting concept models. Two sample concept models are presented along with a discussion of how concept models can be related to teaching and learning, as well as to the nonlinear presentation of research results. Assessment of concept models is then considered. Three types of assessment are suggested: empirical, qualitative and quantitative.