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dc.contributor.authorZheng, Haiyan
dc.contributor.authorJaki, Thomas
dc.contributor.authorWason, James MS
dc.date.accessioned2022-03-31T18:01:03Z
dc.date.available2022-03-31T18:01:03Z
dc.date.issued2022-03-06
dc.date.submitted2021-03-08
dc.identifier.issn0006-341X
dc.identifier.otherbiom13649
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/335607
dc.description.abstractThis 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 circumstances that compare two normal means, proportions, or event times. When nuisance parameters (such as variance) in the new experiment are unknown, a prior distribution can further be specified based on preexperimental data. Exact solutions are available based on most of the criteria considered for Bayesian sample size determination, while a search procedure is described in cases for which there are no closed-form expressions. We illustrate the application of our sample size formulae in the design of clinical trials, where pretrial information is available to be leveraged. Hypothetical data examples, motivated by a rare-disease trial with an elicited expert prior opinion, and a comprehensive performance evaluation of the proposed methodology are presented.
dc.languageen
dc.publisherWiley
dc.subjectBIOMETRIC METHODOLOGY
dc.subjectBayesian experimental designs
dc.subjecthistorical data
dc.subjectrare‐disease trials
dc.subjectrobustness
dc.subjectsample size
dc.titleBayesian sample size determination using commensurate priors to leverage preexperimental data.
dc.typeArticle
dc.date.updated2022-03-31T18:01:03Z
prism.publicationNameBiometrics
dc.identifier.doi10.17863/CAM.83038
dcterms.dateAccepted2022-02-23
rioxxterms.versionofrecord10.1111/biom.13649
rioxxterms.versionAO
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidZheng, Haiyan [0000-0002-3385-2117]
dc.contributor.orcidWason, James MS [0000-0002-4691-126X]
dc.identifier.eissn1541-0420
dc.publisher.urlhttp://dx.doi.org/10.1111/biom.13649
pubs.funder-project-idNIHR Academy (SRF-2015-08-001)
pubs.funder-project-idMedical Research Council (MC_UU_00002/14)
cam.issuedOnline2022-03-06


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