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.     

The potential of integrated modelling in conservation biology: A case study of the black‐footed albatross (Phoebastria nigripes)

Conservation biology aims at assessing the status of a population, based on information which is often incomplete. Integrated population modelling based on state‐space models appears to be a powerful and relevant way of combining into a single likelihood several types of information such as capture‐recapture data and population surveys. In this paper, the authors describe the principles of integrated population modelling and they evaluate its performance for conservation biology based on a case study, that of the black‐footed albatross, a northern Pacific albatross species suspected to be impacted by longline fishing     

Empirical Non-Parametric Control Charts: Estimation Effects and Corrections

Owing to the extreme quantiles involved, standard control charts are very sensitive to the effects of parameter estimation and non-normality. More general parametric charts have been devised to deal with the latter complication and corrections have been derived to compensate for the estimation step, both under normal and parametric models. The resulting procedures offer a satisfactory solution over a broad range of underlying distributions. However, situations do occur where even such a large model is inadequate and nothing remains but to consider non- parametric charts. In principle, these form ideal solutions, but the problem is that huge sample sizes are required for the estimation step. Otherwise the resulting stochastic error is so large that the chart is very unstable, a disadvantage that seems to outweigh the advantage of avoiding the model error from the parametric case. Here we analyse under what conditions non-parametric charts actually become feasible alternatives for their parametric counterparts. In particular, corrected versions are suggested for which a possible change point is reached at sample sizes that are markedly less huge (but still larger than the customary range). These corrections serve to control the behaviour during in-control (markedly wrong outcomes of the estimates only occur sufficiently rarely). The price for this protection will clearly be some loss of detection power during out-of-control. A change point comes in view as soon as this loss can be made sufficiently small.     

Parent‐Adolescent Communication About Sex: Retrospective Reports by Latino College Students

Latina female (n= 97) and Latino male (n= 69) college students (M age = 21.4 years) completed self‐report surveys regarding family of origin experiences, including sexual communication with parents while growing up. Latino parents of this comparatively highly educated sample tended to use direct rather than indirect strategies for communicating about sexuality with their children. Young women reported higher levels of sexual communication with mothers while growing up than did young men, and respondents reported less communication with fathers than mothers. Among young women, sexual communication with mother was positively associated with non‐Mexican origin and negatively associated with having older brothers living at home. In contrast, maternal education was positively associated with mother‐son communication about sex. Paternal education and the absence of older brothers positively predicted communication with both sons and daughters. The analyses provide novel information regarding sexual communication in Latino families and suggest directions for future research.     

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.     

《孟子》中的单音节形容词研究

文章主要从量的角度对《孟子》中的单音节形容词的句法功能进行研究,通过与现代汉语形容词的特征比较,结果发现单音节形容词作谓语(不带宾语),单音节形容词作宾语,单音节形容词带宾语以及单音节形容词作定语是《孟子》中的单音节形容词的重要特征。     

第二次世界大战对世界格局产生的影响

第二次世界大战以雅尔塔体系为基础形成了以美苏两大国为首的世界政治格局,对战后世界政治、经济和国际关系产生了深刻影响。随着两极格局的终结,世界又朝着多极化趋势发展。     

Marginal and association regression models for longitudinal binary data with drop‐outs: A likelihood‐based approach

Longitudinal data often contain missing observations, and it is in general difficult to justify particular missing data mechanisms, whether random or not, that may be hard to distinguish. The authors describe a likelihood‐based approach to estimating both the mean response and association parameters for longitudinal binary data with drop‐outs. They specify marginal and dependence structures as regression models which link the responses to the covariates. They illustrate their approach using a data set from the Waterloo Smoking Prevention Project They also report the results of simulation studies carried out to assess the performance of their technique under various circumstances.     

非拓扑孤子模型的相变特征与袋常数的温度依赖性

本文计算了在有限温度和密度下非拓扑孤子模型的有效势;得到了袋常数对温度和化学势的依赖关系;分析了禁闭解除相变的特征.结果表明:该模型的禁闭解除相变为一级;相变特征的分析表明有退禁闭相与禁闭相的两相共存.     

Potential exposures and risks from beryllium-containing products.

Beryllium is the strongest of the lightweight metals. Used primarily in military applications prior to the end of the Cold War, beryllium is finding new applications in many commercial products, including computers, telecommunication equipment, and consumer and automotive electronics. The use of beryllium in nondefense consumer applications is of concern because beryllium is toxic. Inhalation of beryllium dust or vapor causes a chronic lung disease in some individuals at concentrations as low as 0.01 microg/m3 in air. As beryllium enters wider commerce, it is prudent to ask what risks this might present to the general public and to workers downstream of the beryllium materials industry. We address this question by evaluating the potential for beryllium exposure from the manufacturing, use, recycle, and disposal of beryllium-containing products. Combining a market study with a qualitative exposure analysis, we determine which beryllium applications and life cycle phases have the largest exposure potential. Our analysis suggests that use and maintenance of the most common types of beryllium-containing products do not result in any obvious exposures of concern, and that maintenance activities result in greater exposures than product use. Product disposal has potential to present significant individual risks, but uncertainties concerning current and future routes of product disposal make it difficult to be definitive. Overall, additional exposure and dose-response data are needed to evaluate both the health significance of many exposure scenarios, and the adequacy of existing regulations to protect workers and the public. Although public exposures to beryllium and public awareness and concern regarding beryllium risks are currently low, beryllium risks have psychometric qualities that may lead to rapidly heightened public concern.