手法を比較

	逐次 / 群逐次試験デザイン	適応的臨床試験デザイン	検出力分析	ランダム化比較試験 (RCT)
分野	実験計画法	実験計画法	統計学	実験計画法
系統	Hypothesis test	Hypothesis test	Hypothesis test	Hypothesis test
提唱年	1979	1994	1969 (1st ed.); 1988 (seminal 2nd ed.)	1948
提唱者	O'Brien & Fleming; Pocock; Lan & DeMets	Bauer & Köhne	Jacob Cohen	James Lind (early precursor, 1747); modern formulation: Austin Bradford Hill & Medical Research Council (1948)
種類	Adaptive stopping trial design	Adaptive hypothesis test with interim analyses	Sample size and power planning	Interventional comparative study
原典	O'Brien, P.C. & Fleming, T.R. (1979). A Multiple Testing Procedure for Clinical Trials. Biometrics, 35(3), 549–556.	Bauer, P. & Köhne, K. (1994). Evaluation of Experiments with Adaptive Interim Analyses. Biometrics, 50(4), 1029–1041.	Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 978-0805802832	Schulz, K.F., Altman, D.G., Moher, D., for the CONSORT Group (2010). CONSORT 2010 Statement: Updated Guidelines for Reporting Parallel Group Randomised Trials. BMJ, 340, c332.
別名	group sequential design, adaptive stopping design, Ardışık Deneme Tasarımı (Sequential / Group Sequential)	adaptive design, group sequential design, sample size re-estimation, platform trial	sample size calculation, power calculation, sensitivity analysis, a priori power analysis	RCT, randomised controlled trial, clinical trial, Randomize Kontrollü Çalışma (RCT) Tasarımı
関連	3	3	5	7
概要	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.	Adaptive clinical trial design is a flexible experimental framework, formalised by Bauer and Köhne in 1994, in which pre-specified rules allow the trial to be modified mid-course — adjusting sample size, treatment arms, or randomisation ratios — based on accumulating interim data while rigorously controlling the Type I error rate.	Power analysis is a planning and evaluation technique that quantifies the probability of detecting a real effect of a given magnitude at a chosen significance level. It links four quantities — sample size, effect size, significance level (alpha), and statistical power (1 minus beta) — so that researchers can determine the sample size needed before data collection or evaluate the sensitivity of a completed study.	A randomized controlled trial (RCT) is the gold standard experimental design in clinical and health research, in which participants are randomly allocated to a treatment group or a control group so that the effect of an intervention can be measured with the highest possible degree of internal validity. The modern parallel-group RCT was formalized by Austin Bradford Hill and the Medical Research Council in their landmark streptomycin trial of 1948, and its reporting is governed today by the CONSORT 2010 guidelines (Schulz et al., 2010).