방법 비교

	시뮬레이션 기반 검정력 분석 (몬테카를로 검정력)	순차 분석 (그룹 순차 설계)
분야	통계학	통계학
계열	Hypothesis test	Hypothesis test
기원 연도	2011	1977
창시자	Arnold et al. (2011); Green & MacLeod (2016) for mixed-model extension	P. C. O'Brien & T. R. Fleming; P. C. Pocock
유형	Simulation-based (Monte Carlo)	Sequential / adaptive hypothesis test
원전	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.
별칭	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)
관련	6	5
요약	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.