Crossover designs for clinical trials.
I discuss three-period crossover designs for an efficient comparison of two test treatments with special application to clinical trials which often have many practical limitations. In this paper I specify a subset of three-period crossover designs so that the investigators are not left with the problematic two-period two-sequence design, should the trials be terminated after the second period. I show that there is a dramatic reduction in variability for estimating the direct and residual treatment effects in three-period designs compared to two-period designs. I also show that the universally optimal design with ABB and BAA sequences is unsuitable when a complex form of residual effects is suspected, such as the second-order residual effects or treatment by period interactions. The design with ABB, BAA, AAB, and BBA sequences is relatively robust to these uncertain model assumptions. I also discuss missing data problems and conclude that, even with a large proportion of missing values, the three-period design is far more efficient than the two-period design.
Carriere
K C
KC
Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada.
D000704:Analysis of Variance; D005260:Female; D006801:Humans; D008297:Male; D011237:Predictive Value of Tests; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012107:Research Design