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Bayesiansk inferens×Sekventiell / Gruppsekventiell studiedesign×
ÄmnesområdeStatistikFörsöksplanering
FamiljBayesian methodsHypothesis test
Ursprungsår17631979
UpphovspersonThomas Bayes; Pierre-Simon LaplaceO'Brien & Fleming; Pocock; Lan & DeMets
TypProbabilistic inference paradigmAdaptive stopping trial design
UrsprungskällaBayes, T. (1763). An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society of London, 53, 370–418. link ↗O'Brien, P.C. & Fleming, T.R. (1979). A Multiple Testing Procedure for Clinical Trials. Biometrics, 35(3), 549–556. DOI ↗
AliasBayes inference, Bayesian statistics, Bayesian updating, posterior inferencegroup sequential design, adaptive stopping design, Ardışık Deneme Tasarımı (Sequential / Group Sequential)
Närliggande33
SammanfattningBayesian inference is a statistical paradigm in which probability represents degrees of belief rather than long-run frequencies. It encodes prior knowledge about parameters in a prior distribution, combines that prior with the likelihood of observed data via Bayes' theorem, and produces a posterior distribution that quantifies updated uncertainty. The foundational theorem was published posthumously by Thomas Bayes in 1763 and subsequently systematized by Pierre-Simon Laplace in his 1812 Théorie analytique des probabilités.Sequential and group sequential trial designs allow a study to be stopped early — or continued — based on interim analyses conducted as data accumulate. The core framework was formalised by O'Brien and Fleming in 1979 and extended by Lan and DeMets's alpha-spending approach, and it controls the overall Type I error rate across all planned looks by pre-specifying both efficacy and futility boundaries before enrolment begins.
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ScholarGateJämför metoder: Bayesian Inference · Sequential Design. Hämtad 2026-06-17 från https://scholargate.app/sv/compare