পদ্ধতির তুলনা করুন

	ডোজ-এসকেলেশন ডিজাইন (কন্টিনিউয়াল রিঅ্যাসেসমেন্ট মেথড)	বেয়েশীয় অনুমান (Bayesian Inference)	সিকোয়েন্সিয়াল / গ্রুপ সিকোয়েন্সিয়াল ট্রায়াল ডিজাইন
ক্ষেত্র	পরীক্ষামূলক নকশা	পরিসংখ্যান	পরীক্ষামূলক নকশা
পরিবার	Process / pipeline	Bayesian methods	Hypothesis test
উদ্ভবের বছর	1990	1763	1979
প্রবর্তক	John O'Quigley, Margaret Pepe & Lloyd Fisher	Thomas Bayes; Pierre-Simon Laplace	O'Brien & Fleming; Pocock; Lan & DeMets
ধরন	Adaptive Bayesian dose-finding design	Probabilistic inference paradigm	Adaptive stopping trial design
মৌলিক উৎস	O'Quigley, J., Pepe, M., & Fisher, L. (1990). Continual reassessment method: a practical design for phase 1 clinical trials in cancer. Biometrics, 46(1), 33–48.	Bayes, T. (1763). An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society of London, 53, 370–418.	O'Brien, P.C. & Fleming, T.R. (1979). A Multiple Testing Procedure for Clinical Trials. Biometrics, 35(3), 549–556.
অপর নাম	Continual Reassessment Method, CRM Design, Phase I Dose-Finding Design, Doz Artırma Tasarımı	Bayes inference, Bayesian statistics, Bayesian updating, posterior inference	group sequential design, adaptive stopping design, Ardışık Deneme Tasarımı (Sequential / Group Sequential)
সম্পর্কিত	2	3	3
সারসংক্ষেপ	Dose-Escalation Design, formalized as the Continual Reassessment Method (CRM), is a Bayesian adaptive algorithm for identifying the Maximum Tolerated Dose (MTD) in Phase I clinical trials. Introduced by John O'Quigley, Margaret Pepe, and Lloyd Fisher in 1990, CRM treats dose-toxicity response as a parametric curve, updates a prior probability model after each patient's outcome, and assigns subsequent patients to the dose currently estimated closest to a pre-specified target toxicity probability.	Bayesian inference is a statistical paradigm in which probability represents degrees of belief rather than long-run frequencies. It encodes prior knowledge about parameters in a prior distribution, combines that prior with the likelihood of observed data via Bayes' theorem, and produces a posterior distribution that quantifies updated uncertainty. The foundational theorem was published posthumously by Thomas Bayes in 1763 and subsequently systematized by Pierre-Simon Laplace in his 1812 Théorie analytique des probabilités.	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.