Designing Efficient Multicenter Trials With a Maximin Strategy

For two-treatment multicenter trials with a continuous outcome, designs are presented that minimize the number of subjects required or the research budget, when aiming for a desired power level. These designs optimize both the allocation ratio of participants between treatment and control condition within each center, and the balance between the number of centers and the number of participants per center. Because optimal designs rely on prior knowledge of variance parameters from the analysis model, which are unknown during the design stage, maximin designs are introduced. These designs guarantee a pre-specified power level across plausible ranges of the unknown parameters and maximize power under worst-case parameter values. The present study extends the existing literature on multicenter designs by deriving maximin designs not only for the case where the number of centers and the sample size per center can be optimized, but also when either the number of centers or the sample size per center is fixed due to practical constraints. An empirical example illustrates sample size calculation for such designs and potential budget savings. Additionally, an interactive R Shiny app has been developed to simplify sample size calculations for maximin multicenter trials.