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Elementary bayesian biostatistics

By: Moye, lemuel A.
Material type: materialTypeLabelBookSeries: Chapman and Hall/CRC Biostatistics Series. Publisher: London Chapman and Hall/CRC 2008Description: xxi, 377 p. With at Acc. No. CD1061.ISBN: 9781584887249.Subject(s): Medicine - Research - Statistical methods | Bayesian statistical decision theory - History | Biometry - methods | Bayes TheoremDDC classification: 616 Summary: Bayesian analyses have made important inroads in modern clinical research due, in part, to the incorporation of the traditional tools of noninformative priors as well as the modern innovations of adaptive randomization and predictive power. Presenting an introductory perspective to modern Bayesian procedures, Elementary Bayesian Biostatistics explores Bayesian principles and illustrates their application to healthcare research. Building on the basics of classic biostatistics and algebra, this easy-to-read book provides a clear overview of the subject. It focuses on the history and mathematical foundation of Bayesian procedures, before discussing their implementation in healthcare research from first principles. The book concludes with recommendations for Bayesians to improve their standing in the clinical trials community. As Bayesian methods gain more acceptance in healthcare, it is necessary for clinical scientists to understand Bayesian principles.
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Bayesian analyses have made important inroads in modern clinical research due, in part, to the incorporation of the traditional tools of noninformative priors as well as the modern innovations of adaptive randomization and predictive power. Presenting an introductory perspective to modern Bayesian procedures, Elementary Bayesian Biostatistics explores Bayesian principles and illustrates their application to healthcare research. Building on the basics of classic biostatistics and algebra, this easy-to-read book provides a clear overview of the subject. It focuses on the history and mathematical foundation of Bayesian procedures, before discussing their implementation in healthcare research from first principles. The book concludes with recommendations for Bayesians to improve their standing in the clinical trials community. As Bayesian methods gain more acceptance in healthcare, it is necessary for clinical scientists to understand Bayesian principles.

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