Сравнение методов

	Байесовское рандомизированное контролируемое исследование	Адаптивное рандомизированное клиническое исследование
Область	Эпидемиология	Эпидемиология
Семейство	Process / pipeline	Process / pipeline
Год появления	1980s–2000s (formal methodology consolidated ~2004–2006)	Late 1990s–2000s (widespread adoption post-2010)
Автор метода	Donald A. Berry and David J. Spiegelhalter (applied Bayesian inference formally to RCT design)	Donald Berry and colleagues; formalized by FDA guidance in 2010 and 2019
Тип	Randomized experimental study with Bayesian inference	Experimental clinical trial design
Основополагающий источник	Spiegelhalter, D. J., Abrams, K. R., & Myles, J. P. (2004). Bayesian Approaches to Clinical Trials and Health-Care Evaluation. Wiley. ISBN: 978-0471499756	Berry, D. A. (2006). Bayesian clinical trials. Nature Reviews Drug Discovery, 5(1), 27–36.
Другие названия	Bayesian RCT, Bayesian adaptive trial, Bayesian clinical trial design, BRCT	adaptive RCT, adaptive trial design, response-adaptive randomization trial, adaptive clinical trial
Связанные	5	6
Сводка	A Bayesian randomized clinical trial (Bayesian RCT) combines the rigour of random treatment allocation with Bayesian statistical inference, allowing researchers to incorporate prior evidence and update beliefs continuously as trial data accumulate. Unlike the classical frequentist RCT, it yields direct probability statements about treatment effects and supports pre-specified adaptive stopping rules based on posterior probabilities.	An adaptive randomized clinical trial (adaptive RCT) is a prospective experimental study that uses pre-specified rules to modify one or more trial aspects — such as sample size, allocation ratios, or treatment arms — based on accumulating data collected during the trial itself, while maintaining statistical validity and integrity of the study.