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多变量纵向二元数据的转移模型AI 解读

In many settings with longitudinal binary data, interest lies in modeling covariate effects on transition probabilities of an underlying stochastic process. When data from two or more processes are available, the scientific focus may be on the degree to which changes in one process are associated with changes in another process. Analysis based on independent Markov models permits separate examination of covariate effects on the transition probabilities for each process, but…

聚类不完整纵向数据的边际分析方法AI 解读

Inverse probability–weighted generalized estimating equations are commonly used to deal with incomplete longitudinal data arising from a missing-at-random mechanism when the marginal means are of primary interest. In many cases, however, the repeated measurements themselves may arise in clusters, which leads to both a cross-sectional and a longitudinal correlation structure. In some applications, the degree of these types of correlation may become of scientific interest.…