🤖 AI Summary
This study addresses the common issue in randomized controlled trials where sample size determination for co-primary endpoints often results in imbalanced marginal statistical power across endpoints. To resolve this long-standing challenge, the authors propose a novel and systematic approach to sample size calculation grounded in multiple hypothesis testing theory. By strategically leveraging the degrees of freedom inherent in multiplicity adjustments, the method ensures equal marginal power for all co-primary endpoints. The proposed strategy demonstrates superior design properties and operating characteristics compared to existing ad hoc rules, offering a practical and efficient solution for balanced power allocation in trials with co-primary endpoints.
📝 Abstract
The choice of sample size in the context of co-primary endpoints for a randomised trial is discussed. Current guidance can leave endpoints with unequal marginal power. A method is provided to achieve equal marginal power by using the flexibility provided in multiple testing procedures. A comparison is made to several choices of rule to determine the sample size, in terms of the study design and its operating characteristics.