Description

Book Synopsis

Hybrid Frequentist/Bayesian Power and Bayesian Power in Planning Clinical Trials provides a practical introduction to unconditional approaches to planning randomised clinical trials, particularly aimed at drug development in the pharmaceutical industry. This book is aimed at providing guidance to practitioners in using average power, assurance and related concepts. This book brings together recent research and sets them in a consistent framework and provides a fresh insight into how such methods can be used.

Features:

  • A focus on normal theory linking average power, expected power, predictive power, assurance, conditional Bayesian power and Bayesian power.
  • Extensions of the concepts to binomial, and time-to-event outcomes and non-inferiority trials
  • An investigation into the upper bound on average power, assurance and Bayesian power based on the prior probability of a positive treatment effect
  • Application of assurance to a ser

Hybrid FrequentistBayesian Power and Bayesian

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    £999.99

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    A Paperback by Andrew P. Grieve

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      View other formats and editions of Hybrid FrequentistBayesian Power and Bayesian by Andrew P. Grieve

      Publisher: CRC Press
      Publication Date: 8/26/2024
      ISBN13: 9781032111315, 978-1032111315
      ISBN10: 1032111313

      Description

      Book Synopsis

      Hybrid Frequentist/Bayesian Power and Bayesian Power in Planning Clinical Trials provides a practical introduction to unconditional approaches to planning randomised clinical trials, particularly aimed at drug development in the pharmaceutical industry. This book is aimed at providing guidance to practitioners in using average power, assurance and related concepts. This book brings together recent research and sets them in a consistent framework and provides a fresh insight into how such methods can be used.

      Features:

      • A focus on normal theory linking average power, expected power, predictive power, assurance, conditional Bayesian power and Bayesian power.
      • Extensions of the concepts to binomial, and time-to-event outcomes and non-inferiority trials
      • An investigation into the upper bound on average power, assurance and Bayesian power based on the prior probability of a positive treatment effect
      • Application of assurance to a ser

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