國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Bayesian adaptive methods for clinic...

Berry, Scott M.

Bayesian adaptive methods for clinical trials

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Bayesian adaptive methods for clinical trialsScott 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.
標題:	Clinical trialsStatistical methods.
電子資源:	Distributed by publisher. Purchase or institutional license may be required for access.
ISBN:	9781439825518 (e-book : PDF)

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: 9781439825518 (e-book : PDF)Subjects--Topical Terms:

181899
Clinical trials
--Statistical methods.Index Terms--Genre/Form:

214472
Electronic books.

Bayesian adaptive methods for clinical trials
LDR:02697cmm 2200289Ia 4500 001 275878
003 FlBoTFG
005 20100929160852.0
006 a|||||s|||||||||||
007 cr||||
008 110107s2011 flu sb 001 0 eng d
020 $a 9781439825518 (e-book : PDF)
020 $a 9781439825488
035 $a CRC0KE11133PDF
040 $a FlBoTFG $c FlBoTFG
090 $a R853.C55 $b B385 2011
092 $a 615.50724 $b B357
245 0 0 $a Bayesian adaptive methods for clinical trials $h [electronic resource] / $c Scott M. Berry ... [et al.].
260 $a Boca Raton : $b Chapman & Hall/CRC, $c 2011.
300 $a 323 p.
490 1 $a Chapman & Hall/CRC biostatistics series ; $v 38
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.
538 $a Mode of access: World Wide Web.
650 0 $a Clinical trials $x Statistical methods. $3 181899
650 0 $a Bayesian statistical decision theory. $3 182005
655 7 $a Electronic books. $2 local. $3 214472
700 1 $a Berry, Scott M. $3 487297
776 1 $z 9781439825488
830 0 $a Chapman & Hall/CRC biostatistics series ; $v 38. $3 487298
856 4 0 $u http://marc.crcnetbase.com/isbn/9781439825518 $q application/PDF $z Distributed by publisher. Purchase or institutional license may be required for access.