A Review of Bayesian Perspectives on Sample Size Derivation for Confirmatory Trials.

ABSTRACT: Sample size derivation is a crucial element of planning any confirmatory trial. The required sample size is typically derived based on constraints on the maximal acceptable Type I error rate and minimal desired power. Power depends on the unknown true effect and tends to be calculated either for the smallest relevant effect or a likely point alternative. The former might be problematic if the minimal relevant effect is close to the null, thus requiring an excessively large sample size, while the latter is dubious since it does not account for the a priori uncertainty about the likely alternative effect. A Bayesian perspective on sample size derivation for a frequentist trial can reconcile arguments about the relative a priori plausibility of alternative effects with ideas based on the rele

SUBMITTER: Kunzmann K 

PROVIDER: S-EPMC7612172 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature