title: Exact statistical inference for group sequential trials.
abstract: This paper considers clinical trials comparing two treatments with dichotomous responses where the data are examined periodically for early evidence of treatment difference. The existing group sequential methods for such trials are based on the large-sample normal approximation to the joint distribution of the estimators of treatment difference over interim analyses. We demonstrate through extensive numerical studies that, for small and even moderate-sized trials, these approximate procedures may lead to tests with supranominal size (mainly when unpooled estimators of variance are used) and confidence intervals with under-nominal coverage probability. We then study exact methods for group sequential testing, repeated interval estimation, and interval estimation following sequential testing. The new procedures can accommodate any treatment allocation rules. An example using real data is provided.
authors.affiliation: Department of Biostatistics, University of Washington, Seattle 98195.
authors.forename: D Y
authors.initials: DY
authors.lastname: Lin
authors.forename: L J
authors.initials: LJ
authors.lastname: Wei
authors.forename: D L
authors.initials: DL
authors.lastname: DeMets
mesh_terms: D001699:Biometry; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D006801:Humans; D016013:Likelihood Functions