Compară metode

	Test A/B (Experiment Controlat Online)	Concepția adaptativă a studiilor clinice	Studiul clinic randomizat (SCR)	Proiectare secvențială / secvențială de grup a studiului
Domeniu	Design experimental	Design experimental	Design experimental	Design experimental
Familie	Hypothesis test	Hypothesis test	Hypothesis test	Hypothesis test
Anul apariției	1935	1994	1948	1979
Autorul original	Ron Kohavi et al. (Microsoft); conceptual roots in R. A. Fisher's randomized experiments (1935)	Bauer & Köhne	James Lind (early precursor, 1747); modern formulation: Austin Bradford Hill & Medical Research Council (1948)	O'Brien & Fleming; Pocock; Lan & DeMets
Tip	Parametric comparison (frequentist or Bayesian)	Adaptive hypothesis test with interim analyses	Interventional comparative study	Adaptive stopping trial design
Sursa seminală	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.	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.	O'Brien, P.C. & Fleming, T.R. (1979). A Multiple Testing Procedure for Clinical Trials. Biometrics, 35(3), 549–556.
Denumiri alternative	split test, controlled experiment, two-variant test, A/B Testi (Online Kontrollü Deney)	adaptive design, group sequential design, sample size re-estimation, platform trial	RCT, randomised controlled trial, clinical trial, Randomize Kontrollü Çalışma (RCT) Tasarımı	group sequential design, adaptive stopping design, Ardışık Deneme Tasarımı (Sequential / Group Sequential)
Înrudite	4	3	7	3
Rezumat	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.	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).	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.