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Preventing and Treating Missing Data in Longitudinal Clinical Trials by Craig Mallinckrodt

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9 Analyses of Incomplete Data

9.1 Introduction

Describing an analysis requires specifying the method of estimation, the model (which parameters are to be estimated), and choice of data. Choice of data in this context refers to whether or not follow-up data are included, whether or not missing data are imputed, and whether or not observed data are weighted by the inverse probability of being missing.

In this chapter, methods, models, and choice of data are combined to illustrate some of the commonly used analyses for incomplete longitudinal clinical trial data. These analyses are illustrated using small, hypothetical data sets that allow insight into how the methods work when applied to incomplete data. Two data sets are used. The first is a data ...

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