手法を比較

	A/Bテスト（オンライン制御実験）	適応的臨床試験デザイン
分野	実験計画法	実験計画法
系統	Hypothesis test	Hypothesis test
提唱年	1935	1994
提唱者	Ron Kohavi et al. (Microsoft); conceptual roots in R. A. Fisher's randomized experiments (1935)	Bauer & Köhne
種類	Parametric comparison (frequentist or Bayesian)	Adaptive hypothesis test with interim analyses
原典	Kohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing. Cambridge University Press. ISBN: 9781108724265	Bauer, P. & Köhne, K. (1994). Evaluation of Experiments with Adaptive Interim Analyses. Biometrics, 50(4), 1029–1041.
別名	split test, controlled experiment, two-variant test, A/B Testi (Online Kontrollü Deney)	adaptive design, group sequential design, sample size re-estimation, platform trial
関連	4	3
概要	An A/B test is a randomized controlled experiment that simultaneously exposes two groups of users to a control variant (A) and a treatment variant (B) in order to determine whether a measured outcome differs significantly between them. The modern online controlled experiment framework was systematized by Ron Kohavi and colleagues at Microsoft in the early 2000s, building on R. A. Fisher's classical randomization principles from 1935. It is the dominant causal inference tool in web product development, digital marketing, and experimentation platforms.	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.