Marginal Methods for Incomplete Longitudinal Data Arising in Clusters
聚类不完整纵向数据的边际分析方法
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.…