Description

Book Synopsis

Power and Sample Size in R guides the reader through power and sample size calculations for a wide variety of study outcomes and designs and illustrates their implementation in R software. It is designed to be used as a learning tool for students as well as a resource for experienced statisticians and investigators.

The book begins by explaining the process of power calculation step by step at an introductory level and then builds to increasingly complex and varied topics. For each type of study design, the information needed to perform a calculation and the factors that affect power are explained. Concepts are explained with statistical rigor but made accessible through intuition and examples. Practical advice for performing sample size and power calculations for real studies is given throughout.

The book demonstrates calculations in R. It is integrated with the companion R package powertools and also draws on and summarizes the capabilities of other R packages.

Power and Sample Size in R

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    £71.24

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    RRP £74.99 – you save £3.75 (5%)

    Order before 4pm tomorrow for delivery by Fri 26 Jun 2026.

    A Hardback by Catherine M. Crespi

    15 in stock


      View other formats and editions of Power and Sample Size in R by Catherine M. Crespi

      Publisher: Taylor & Francis Ltd
      Publication Date: 1/6/2025
      ISBN13: 9781138591622, 978-1138591622
      ISBN10: 1138591629
      Also in:
      Clinical trials

      Description

      Book Synopsis

      Power and Sample Size in R guides the reader through power and sample size calculations for a wide variety of study outcomes and designs and illustrates their implementation in R software. It is designed to be used as a learning tool for students as well as a resource for experienced statisticians and investigators.

      The book begins by explaining the process of power calculation step by step at an introductory level and then builds to increasingly complex and varied topics. For each type of study design, the information needed to perform a calculation and the factors that affect power are explained. Concepts are explained with statistical rigor but made accessible through intuition and examples. Practical advice for performing sample size and power calculations for real studies is given throughout.

      The book demonstrates calculations in R. It is integrated with the companion R package powertools and also draws on and summarizes the capabilities of other R packages.

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