论文检索

时间安排不平衡的纵向数据分析AI 解读

Summary The paper considers modelling, estimating and diagnostically verifying the response process generating longitudinal data, with emphasis on association between repeated meas-ures from unbalanced longitudinal designs. Our model is based on separate specifications of the moments for the mean, standard deviation and correlation, with different components possibly sharing common parameters. We propose a general class of correlation structures that comprise random effects,…

单调缺失纵向数据分析中的模式混合模型与选择模型AI 解读

Summary We examine three pattern–mixture models for making inference about parameters of the distribution of an outcome of interest Y that is to be measured at the end of a longitudinal study when this outcome is missing in some subjects. We show that these pattern–mixture models also have an interpretation as selection models. Because these models make unverifiable assumptions, we recommend that inference about the distribution of Y be repeated under a range of plausible…

存在信息性退出的纵向二元响应回归模型AI 解读

SUMMARY This paper reviews both likelihood-based and non-likelihood (generalized estimating equations) regression models for longitudinal binary responses when there are drop-outs. Throughout, it is assumed that the regression parameters for the marginal expectations of the binary responses are of primary scientific interest. The association or time dependence between the responses is largely regarded as a nuisance characteristic of the data. The performance of the methods…

纵向二元响应的似然分析方法AI 解读

In this paper, we discuss a likelihood-based method for analysing correlated binary responses based on a multivariate model. It is related to the pseudo-maximum likelihood approach suggested recently by Zhao & Prentice (1990). Their parameterization results in a simple pairwise model, in which the association between responses is modelled in terms of correlations, while the present paper uses conditional log odds-ratios. With this approach, higher-order associations can be…

纵向二元响应的似然分析方法AI 解读

In this paper, we discuss a likelihood-based method for analysing correlated binary responses based on a multivariate model. It is related to the pseudo-maximum likelihood approach suggested recently by Zhao & Prentice (1990). Their parameterization results in a simple pairwise model, in which the association between responses is modelled in terms of correlations, while the present paper uses conditional log odds-ratios. With this approach, higher-order associations can be…