विधियों की तुलना करें

	अनुकूली प्रयोगशाला प्रयोग	बहु-भुज प्रयोग
क्षेत्र	प्रयोगात्मक अभिकल्प	प्रयोगात्मक अभिकल्प
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	1947 (sequential analysis foundations); adaptive laboratory applications widespread from 1990s	1990s–2000s (clinical formalization); multi-arm concept implicit in ANOVA-era factorial designs
प्रवर्तक	Rooted in sequential analysis (Abraham Wald, 1947); adaptive clinical/lab designs formalized by Berry and colleagues (1990s–2000s)	Developed within clinical trials methodology; formalized by Parmar, Royston and colleagues (UK MRC CTU, early 2000s)
प्रकार	Adaptive experimental design	Experimental design
मौलिक स्रोत	Berry, D. A. (2006). Bayesian clinical trials. Nature Reviews Drug Discovery, 5(1), 27–36.	Royston, P., Parmar, M. K. B., & Qian, W. (2003). Novel designs for multi-arm clinical trials with survival outcomes with an application in ovarian cancer. Statistics in Medicine, 22(14), 2239–2256.
उपनाम	adaptive lab experiment, sequential adaptive laboratory study, response-adaptive laboratory design, adaptive experimental laboratory design	multi-arm trial, multiple-arm experiment, multi-group experiment, many-arm design
संबंधित	5	5
सारांश	An adaptive laboratory experiment is a controlled experimental design conducted in a laboratory setting where pre-specified decision rules allow modifications to the study — such as sample size, treatment allocation, or stopping criteria — based on accumulating data. Unlike fixed designs, adaptive designs incorporate planned interim analyses that permit the experiment to respond to emerging evidence while maintaining statistical validity and Type I error control.	A multi-arm experiment simultaneously compares three or more treatment or intervention conditions — each called an arm — against a shared control or against one another. By testing multiple alternatives in a single study, it yields more information per participant than running separate two-group experiments sequentially, while controlling the overall Type I error rate through pre-specified comparison strategies.