Multiple imputation of missing data with ante-dependence covariance structure

A controlled clinical trial was conducted to investigate the efficacy effect of a chemical compound in the treatment of Premenstrual Dysphoric Disorder (PMDD). The data from the trial showed a non-monotone pattern of missing data and an ante-dependence covariance structure. A new analytical method for imputing the missing data with the ante-dependence covariance is proposed. The PMDD data are analysed by the non-imputation method and two imputation methods: the proposed method and the MCMC method.     

中等收入者论

中等收入者指一个国家的中等富裕群体。为确保社会经济健康、协调、持续发展 ,必须努力提高低收入者素质 ,降低转化门槛 ,扩大中等收入者比重。     

疫情防控期间高校线上教学的效果调查与分析

突发的疫情使得线上教学在所有高校全面铺开。为了了解这次“应急线上教学”的教学效果,上海理工大学教师发展中心对全校师生从线上教学的评价、线上线下教学体验对比、线上教学带给师生的改变等方面进行了线上教学效果的问卷调查。研究对专项调查的数据进行了深入分析,得出了线上与线下学习效果基本等效、线上线下教学各具优势、线上教学带来深刻改变的调查结果,提出了线上教学存在的主要问题,并给出了相应提升线上教学效果的建议。     

Linear Increments with Non‐monotone Missing Data and Measurement Error

Linear increments (LI) are used to analyse repeated outcome data with missing values. Previously, two LI methods have been proposed, one allowing non‐monotone missingness but not independent measurement error and one allowing independent measurement error but only monotone missingness. In both, it was suggested that the expected increment could depend on current outcome. We show that LI can allow non‐monotone missingness and either independent measurement error of unknown variance or dependence of expected increment on current outcome but not both. A popular alternative to LI is a multivariate normal model ignoring the missingness pattern. This gives consistent estimation when data are normally distributed and missing at random (MAR). We clarify the relation between MAR and the assumptions of LI and show that for continuous outcomes multivariate normal estimators are also consistent under (non‐MAR and non‐normal) assumptions not much stronger than those of LI. Moreover, when missingness is non‐monotone, they are typically more efficient.     

民事责任归责问题的理论思考

民事责任的归责是指民事行为人违反法定义务或约定义务后,依什么为根据来使行为人承担强制性的不利后果。民事责任的归责基础是民事违约行为或违法行为对他人的权利或利益造成了损害。民事责任的归责基础和归责要素是两个既有区别又有联系的概念。由行为、损害、过错、因果关系、主体的特殊角色的不同组合构成了民事责任归责要素的内容。确定民事责任的归责原则需考虑以下规则:合理性规则、公正性规则、可操作性规则和逻辑性规则。     

从《夏伯阳》看苏联早期电影对中国电影的影响

《夏伯阳》上映后对中国社会、中国当代文化,尤其是电影史和电影制作的影响,可以以1949年为界,大致划分为两个时期。在后一个时期,《夏伯阳》的影响甚至直接反映在中国国产电影的制作中。而近年来大陆影视的演进发展,多少都表现出试图突破以往艺术创作窠臼的努力,这种中苏文化上的内在与外在关联值得关注和反思。     

Missing item imputation for quality-of-life instruments with application to asthma quality-of-life questionnaires

There has been increasing use of quality-of-life (QoL) instruments in drug development. Missing item values often occur in QoL data. A common approach to solve this problem is to impute the missing values before scoring. Several imputation procedures, such as imputing with the most correlated item and imputing with a row/column model or an item response model, have been proposed. We examine these procedures using data from two clinical trials, in which the original asthma quality-of-life questionnaire (AQLQ) and the miniAQLQ were used. We propose two modifications to existing procedures: truncating the imputed values to eliminate outliers and using the proportional odds model as the item response model for imputation. We also propose a novel imputation method based on a semi-parametric beta regression so that the imputed value is always in the correct range and illustrate how this approach can easily be implemented in commonly used statistical software. To compare these approaches, we deleted 5% of item values in the data according to three different missingness mechanisms, imputed them using these approaches and compared the imputed values with the true values. Our comparison showed that the row/column-model-based imputation with truncation generally performed better, whereas our new approach had better performance under a number scenarios.     

On estimating the distribution of data envelopment analysis efficiency scores: an application to nursing homes’ care planning process

Data envelopment analysis (DEA) is a deterministic econometric model for calculating efficiency by using data from an observed set of decision-making units (DMUs). We propose a method for calculating the distribution of efficiency scores. Our framework relies on estimating data from an unobserved set of DMUs. The model provides posterior predictive data for the unobserved DMUs to augment the frontier in the DEA that provides a posterior predictive distribution for the efficiency scores. We explore the method on a multiple-input and multiple-output DEA model. The data for the example are from a comprehensive examination of how nursing homes complete a standardized mandatory assessment of residents.     

A fresh approach for intercession of nonresponse in multivariate longitudinal designs

The occurrence of nonresponse is very much plebeian in surveys, which troubles the analysis, and hence, an inappropriate inference is left out. To counterbalance the sour effects of the incompleteness, fresh imputation techniques have been proposed with the aid of multi-auxiliary variates for the estimation of population mean on successive waves. Properties of the proposed estimators have been elaborated, and they have been compared with the work of Priyanka et al. (2015). Detailed simulation study is carried out to substantiate the empirical and theoretical results. Several possible cases have been addressed in which nonresponse can occur.     

Control‐based imputation for sensitivity analyses in informative censoring for recurrent event data

In clinical trials, missing data commonly arise through nonadherence to the randomized treatment or to study procedure. For trials in which recurrent event endpoints are of interests, conventional analyses using the proportional intensity model or the count model assume that the data are missing at random, which cannot be tested using the observed data alone. Thus, sensitivity analyses are recommended. We implement the control‐based multiple imputation as sensitivity analyses for the recurrent event data. We model the recurrent event using a piecewise exponential proportional intensity model with frailty and sample the parameters from the posterior distribution. We impute the number of events after dropped out and correct the variance estimation using a bootstrap procedure. We apply the method to an application of sitagliptin study.