Patient's dropout often occurs in clinical trials with multiple scheduled visits, which results in a great challenge in the analysis of incomplete data. As the first step, one has to define a relevant treatment effect parameter, which is not straightforward in the presence of dropout. We discuss and compare two different treatment effect parameters that are adopted in most analyses of clinical data: the study-end treatment effect and the last-observed treatment effect. Some related issues, such as the estimability of causal parameters, the dependence of study parameters on the dropout patterns, and the use of the last observation carry forward, are also discussed.
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Shao et al. (2006) studied this question.