In the first part of this book (Chapters 3 to 13), emphasis was on the formulation and the fitting of, as well as on inference and diagnostics for linear mixed models in general. Later (Chapters 14 to 22), the problem of missing data was discussed in full detail, with emphasis on how to obtain valid inferences from observed longitudinal data and how to perform sensitivity analyses with respect to assumptions made about the dropout process.
In this chapter, we will reflect on the design of longitudinal studies. In Section 23.2, we will briefly discuss how power calculations can be performed based on linear mixed models. We refer to Mentre, Mallet and Baccar (1997) for a note on D-optimal designs in random-effects regression models, and to Liu and Liang (1997), where sample-size calculations are treated in the context of generalized estimating equations (Liang and Zeger 1986).
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© 2009 Springer Verlag New York, LLC
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(2009). Design Considerations. In: Linear Mixed Models for Longitudinal Data. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0300-6_23
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DOI: https://doi.org/10.1007/978-1-4419-0300-6_23
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