Rank-Based Analysis of Unbalanced Repeated Measures Data

Abstract

In this article, we have developed a rank (intra-subject) based analysis of clinical trials with unbalanced repeated measures data. We assume that the errors within each patient are exchangeable and continuous random variables. This rank-based inference is valid when the unbalanced data are missing either completely at random or by design. A drop in dispersion test is developed for general linear hypotheses. A numerical example is given to illustrate the procedure.