Bayesian sample size determination using commensurate priors to leverage preexperimental data.

ABSTRACT: This paper develops Bayesian sample size formulae for experiments comparing two groups, where relevant preexperimental information from multiple sources can be incorporated in a robust prior to support both the design and analysis. We use commensurate predictive priors for borrowing of information and further place Gamma mixture priors on the precisions to account for preliminary belief about the pairwise (in)commensurability between parameters that underpin the historical and new experiments. Averaged over the probability space of the new experimental data, appropriate sample sizes are found according to criteria that control certain aspects of the posterior distribution, such as the coverage probability or length of a defined density region. Our Bayesian methodology can be applied to cir

SUBMITTER: Zheng H 

PROVIDER: S-EPMC7614678 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature