Abstract
Cross-over trials have the potential to provide large reductions in sample size compared to their parallel groups counterparts. In this chapter, three different types of cross-over design and their analysis will be described. In the linear models used to analyze cross-over data, the variability due to differences between the subjects in the trial may be modeled as either fixed or random effects, and both will be illustrated. In designs of the incomplete block type, where there are more treatments than periods, the use of random subject effects enables between-subject information on the treatment comparisons to be recovered, and how this may be done will also be illustrated. Finally, if the so-called baseline measurements have been taken at the beginning of each treatment period, these can be used as covariates to reduce the variability of the estimated treatment comparisons. The use of baselines will be illustrated using the incomplete block design.
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Jones, B. (2021). Cross-over Trials. In: Piantadosi, S., Meinert, C.L. (eds) Principles and Practice of Clinical Trials. Springer, Cham. https://doi.org/10.1007/978-3-319-52677-5_243-1
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DOI: https://doi.org/10.1007/978-3-319-52677-5_243-1
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