Salīdzināt metodes

	Sekvenču analīze (grupveida sekvenču dizains)	Beijesiskā jaudas analīze (apliecinājums)
Nozare	Statistika	Statistika
Saime	Hypothesis test	Hypothesis test
Izcelsmes gads	1977	1986
Autors	P. C. O'Brien & T. R. Fleming; P. C. Pocock	Spiegelhalter & Freedman (1986); O'Hagan, Stevens & Campbell (2005)
Tips	Sequential / adaptive hypothesis test	Bayesian sample size determination
Pirmavots	O'Brien, P.C. & Fleming, T.R. (1979). A Multiple Testing Procedure for Clinical Trials. Biometrics, 35(3), 549–556.	O'Hagan, A., Stevens, J.W. & Campbell, M.J. (2005). Assurance in Clinical Trial Design. Pharmaceutical Statistics, 4(3), 187–201.
Citi nosaukumi	sequential testing, group sequential design, interim analysis, Sıralı Analiz (Sequential Testing / Group Sequential Design)	assurance, bayesian sample size determination, bayesian assurance, Bayesian Güç Analizi (Assurance / Bayesian Sample Size)
Saistītās	5	3
Kopsavilkums	Sequential analysis is a framework for conducting hypothesis tests with pre-planned interim looks at accumulating data, allowing a study to stop early for efficacy or futility while controlling the overall Type I error rate. The group sequential approach was formalised by Pocock (1977) and O'Brien and Fleming (1979), and remains the standard for confirmatory clinical trials and rigorous A/B experiments.	Bayesian power analysis — also called assurance — is a sample size determination method that replaces the frequentist notion of power with a probability-weighted average over a prior distribution on the effect size. First formalised by Spiegelhalter and Freedman (1986) and further developed by O'Hagan, Stevens and Campbell (2005), it answers the question: given our current uncertainty about the true effect, what sample size gives us a high overall probability of obtaining a statistically significant result?