TY - JOUR AB - Crossover designs are an extremely useful tool to investigators, and group sequential methods have proven highly proficient at improving the efficiency of parallel group trials. Yet, group sequential methods and crossover designs have rarely been paired together. One possible explanation for this could be the absence of a formal proof of how to strongly control the familywise error rate in the case when multiple comparisons will be made. Here, we provide this proof, valid for any number of initial experimental treatments and any number of stages, when results are analyzed using a linear mixed model. We then establish formulae for the expected sample size and expected number of observations of such a trial, given any choice of stopping boundaries. Finally, utilizing the four-treatment, four-period TOMADO trial as an example, we demonstrate that group sequential methods in this setting could have reduced the trials expected number of observations under the global null hypothesis by over 33%. AU - Grayling, Michael J AU - Wason, James MS AU - Mander, Adrian P DA - 2018/04/03 DO - 10.1080/07474946.2018.1466528 EP - 203 IS - 2 J1 - Sequential Anal JA - Sequential Anal JF - Sequential Analysis JO - Sequential Analysis KW - Clinical trial KW - Crossover KW - Familywise error rate KW - Group sequential KW - Linear mixed model L2 - https://www.tandfonline.com/doi/full/10.1080/07474946.2018.1466528 PB - Taylor & Francis PY - 2018 SN - 1532-4176 SP - 174 T1 - Group sequential crossover trial designs with strong control of the familywise error rate TI - Group sequential crossover trial designs with strong control of the familywise error rate U1 - 30393467[pmid] U2 - PMC6199128[pmcid] UR - https://doi.org/10.1080/07474946.2018.1466528 VL - 37 Y1 - 2018/04/03 ER -