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Bayesian adaptive methods for clinic...

Berry, Scott M.

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Bayesian adaptive methods for clinical trials

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Bayesian adaptive methods for clinical trials/ Scott M. Berry ... [et al.].
其他作者:	Berry, Scott M.
出版者:	Boca Raton :Chapman & Hall/CRC, : 2011.,
面頁冊數:	323 p.
內容註:	(Publisher-supplied data) Statistical approaches for clinical trials -- Basics of Bayesian inference -- Phase I studies -- Phase II studies -- Phase III studies -- Special topics.
標題:	Bayesian statistical decision theory. -
電子資源:	http://marc.crcnetbase.com/isbn/9781439825518 Distributed by publisher. Purchase or institutional license may be required for access.
ISBN:	9781439825488

Bayesian adaptive methods for clinical trials
Bayesian adaptive methods for clinical trials[electronic resource] /Scott M. Berry ... [et al.]. - Boca Raton :Chapman & Hall/CRC,2011. - 323 p. - Chapman & Hall/CRC biostatistics series ;38. - Chapman & Hall/CRC biostatistics series ;38..

Includes bibliographical references and indexes.

(Publisher-supplied data) Statistical approaches for clinical trials -- Basics of Bayesian inference -- Phase I studies -- Phase II studies -- Phase III studies -- Special topics.

"As has been well-discussed, the explosion of interest in Bayesian methods over the last 10 to 20 years has been the result of the convergence of modern computing power and e�cient Markov chain Monte Carlo (MCMC) algo- rithms for sampling from and summarizing posterior distributions. Prac- titioners trained in traditional, frequentist statistical methods appear to have been drawn to Bayesian approaches for three reasons. One is that Bayesian approaches implemented with the majority of their informative content coming from the current data, and not any external prior informa- tion, typically have good frequentist properties (e.g., low mean squared er- ror in repeated use). Second, these methods as now readily implemented in WinBUGS and other MCMC-driven software packages now oʼer the simplest approach to hierarchical (random eʼects) modeling, as routinely needed in longitudinal, frailty, spatial, time series, and a wide variety of other settings featuring interdependent data. Third, practitioners are attracted by the greater �exibility and adaptivity of the Bayesian approach, which permits stopping for e�cacy, toxicity, and futility, as well as facilitates a straightforward solution to a great many other specialized problems such as dose-nding, adaptive randomization, equivalence testing, and others we shall describe. This book presents the Bayesian adaptive approach to the design and analysis of clinical trials"--Provided by publisher.

Mode of access: World Wide Web.

ISBN: 9781439825488Subjects--Topical Terms:

551404
Bayesian statistical decision theory.
Index Terms--Genre/Form:

542853
Electronic books.

Bayesian adaptive methods for clinical trials
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504 $a Includes bibliographical references and indexes.
505 0 $a (Publisher-supplied data) Statistical approaches for clinical trials -- Basics of Bayesian inference -- Phase I studies -- Phase II studies -- Phase III studies -- Special topics.
520 $a "As has been well-discussed, the explosion of interest in Bayesian methods over the last 10 to 20 years has been the result of the convergence of modern computing power and e�cient Markov chain Monte Carlo (MCMC) algo- rithms for sampling from and summarizing posterior distributions. Prac- titioners trained in traditional, frequentist statistical methods appear to have been drawn to Bayesian approaches for three reasons. One is that Bayesian approaches implemented with the majority of their informative content coming from the current data, and not any external prior informa- tion, typically have good frequentist properties (e.g., low mean squared er- ror in repeated use). Second, these methods as now readily implemented in WinBUGS and other MCMC-driven software packages now oʼer the simplest approach to hierarchical (random eʼects) modeling, as routinely needed in longitudinal, frailty, spatial, time series, and a wide variety of other settings featuring interdependent data. Third, practitioners are attracted by the greater �exibility and adaptivity of the Bayesian approach, which permits stopping for e�cacy, toxicity, and futility, as well as facilitates a straightforward solution to a great many other specialized problems such as dose-nding, adaptive randomization, equivalence testing, and others we shall describe. This book presents the Bayesian adaptive approach to the design and analysis of clinical trials"--Provided by publisher.
530 $a Also available in print edition.
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