Methoden vergleichen

	Simulationsbasierte Power-Analyse (Monte-Carlo-Power)	Sequenzielle Analyse (Gruppensequenzielle Planung)
Fachgebiet	Statistik	Statistik
Familie	Hypothesis test	Hypothesis test
Entstehungsjahr	2011	1977
Urheber	Arnold et al. (2011); Green & MacLeod (2016) for mixed-model extension	P. C. O'Brien & T. R. Fleming; P. C. Pocock
Typ	Simulation-based (Monte Carlo)	Sequential / adaptive hypothesis test
Wegweisende Quelle	Arnold, B.F. et al. (2011). Simulation Methods to Estimate Design Power: An Overview for Applied Research. BMC Medical Research Methodology, 11, 94.	O'Brien, P.C. & Fleming, T.R. (1979). A Multiple Testing Procedure for Clinical Trials. Biometrics, 35(3), 549–556.
Aliasnamen	Monte Carlo power analysis, Monte Carlo simulation power, MC power, Simülasyon Tabanlı Güç Analizi (Monte Carlo Power)	sequential testing, group sequential design, interim analysis, Sıralı Analiz (Sequential Testing / Group Sequential Design)
Verwandt	6	5
Zusammenfassung	Simulation-based power analysis estimates the statistical power and required sample size of a study by repeating a full analysis pipeline thousands of times on artificially generated data. Because it relies on Monte Carlo simulation rather than closed-form equations, it is applicable to designs — mixed models, complex measurement structures, non-standard outcomes — where analytical power formulas do not exist. The approach was systematically described for applied research by Arnold et al. in 2011, and the mixed-model implementation via the SIMR package was formalised by Green and MacLeod in 2016.	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.