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Bayesian thinking in biostatistics / Gary L. Rosner, Purushottam W. Laud, Wesley O. Johnson.

By: Contributor(s): Material type: TextTextPublisher: Boca Raton : CRC Press, 2021Edition: First editionDescription: 621 p. : ill. ; 24 cmContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
Subject(s): Additional physical formats: Print version:: Bayesian thinking in biostatisticsDDC classification:
  • 570.15195 23 ROB
LOC classification:
  • QH323.5
Contents:
Scientific data analysis -- Fundamentals I : Bayes theorem, knowledge distributions, prediction -- Fundamentals II : models for exchangeable observations -- Computational methods for Bayesian analysis -- Comparing populations -- Specifying prior distributions -- Linear regression -- Binary response regression -- Poisson and non-linear regression -- Model assessment -- Survival modeling I : models for exchangeable observations -- Survival modeling 2 : time-to-event regression models -- Clinical trial designs -- Hierarchical models and longitudinal data -- Diagnostic tests.
Summary: "With a focus on incorporating sensible prior distributions and discussions on many recent developments in Bayesian methodologies, Bayesian Thinking in Biostatistics considers statistical issues in biomedical research. The book emphasizes greater collaboration between biostatisticians and biomedical researchers. The text includes an overview of Bayesian statistics, a discussion of many of the methods biostatisticians frequently, such as rates and proportions, regression models, clinical trial design, and methods for evaluating diagnostic tests"-- Provided by publisher.
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Holdings
Item type Current library Call number Copy number Status Date due Barcode
Books Books Central Library, SUST General Stacks 570.15195 ROB (Browse shelf(Opens below)) 1 Available 0082287
Books Books Central Library, SUST General Stacks 570.15195 ROB (Browse shelf(Opens below)) 2 Available 0082288

Includes bibliographical references and index.

Scientific data analysis -- Fundamentals I : Bayes theorem, knowledge distributions, prediction -- Fundamentals II : models for exchangeable observations -- Computational methods for Bayesian analysis -- Comparing populations -- Specifying prior distributions -- Linear regression -- Binary response regression -- Poisson and non-linear regression -- Model assessment -- Survival modeling I : models for exchangeable observations -- Survival modeling 2 : time-to-event regression models -- Clinical trial designs -- Hierarchical models and longitudinal data -- Diagnostic tests.

"With a focus on incorporating sensible prior distributions and discussions on many recent developments in Bayesian methodologies, Bayesian Thinking in Biostatistics considers statistical issues in biomedical research. The book emphasizes greater collaboration between biostatisticians and biomedical researchers. The text includes an overview of Bayesian statistics, a discussion of many of the methods biostatisticians frequently, such as rates and proportions, regression models, clinical trial design, and methods for evaluating diagnostic tests"-- Provided by publisher.

Description based on print version record and CIP data provided by publisher.

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