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E-grāmata: Sample Sizes for Clinical Trials

(University of Sheffield, Sheffield, England, UK)
  • Formāts: 420 pages
  • Izdošanas datums: 21-Jun-2023
  • Izdevniecība: CRC Press
  • Valoda: eng
  • ISBN-13: 9780429994555
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Sample Sizes for Clinical TrialsPalielināt
  • Formāts: 420 pages
  • Izdošanas datums: 21-Jun-2023
  • Izdevniecība: CRC Press
  • Valoda: eng
  • ISBN-13: 9780429994555
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Sample Sizes for Clinical Trials, Second Edition is a practical book that assists researchers in their estimation of the sample size for clinical trials. Throughout the book there are detailed worked examples to illustrate both how to do the calculations and how to present them to colleagues or in protocols. The book also highlights some of the pitfalls in calculations as well as the key steps that lead to the final sample size calculation.

Features:

  • Comprehensive coverage of sample size calculations, including Normal, binary, ordinal, and survival outcome data
  • Covers superiority, equivalence, non-inferiority, bioequivalence and precision objectives for both parallel group and crossover designs
  • Highlights how trial objectives impact the study design with respect to both the derivation of sample formulae and the size of the study
  • Motivated with examples of real-life clinical trials showing how the calculations can be applied
    • New edition is extended with all chapters revised, some substantially, and four completely new chapters on multiplicity, cluster trials, pilot studies, and single arm trials

    • The book is primarily aimed at researchers and practitioners of clinical trials and biostatistics, and could be used to teach a course on sample size calculations. The importance of a sample size calculation when designing a clinical trial is highlighted in the book. It enables readers to quickly find an appropriate sample size formula, with an associated worked example, complemented by tables to assist in the calculations.



    This book assists researchers in their estimation of the sample size for clinical trials. Throughout the book there are detailed worked examples to illustrate both how to do the calculations and how to present them.

    1. Introduction. 2.Seven Key Steps to Cook up a Sample Size.
    3. Sample Sizes for Parallel Group Superiority Trials with Normal Data.
    4. Sample Size Calculations for Superiority Cross-Over Trials with Normal Data.
    5. Sample Size for Cluster Randomized Trials.
    6. Allowing for Multiplicity in Sample Sizes Calculations for Clinical Trials.
    7. Samples Size Calculations for Non-Inferiority Clinical Trials with Normal Data.
    8. Sample Size Calculations for Equivalence Clinical Trials with Normal Data.
    9. Sample Size Calculations for Bioequivalence Trials.
    1. Sample Size Calculations for Precision Clinical Trials with Normal Data. Sample Size for Pilot Studies.
    12. Sample Size Calculations for Parallel Group Superiority Clinical Trials with Binary Data.
    13. Sample Size Calculations for Superiority Cross-Over Clinical Trials with Binary Data.
    14. Sample Size Calculations for Non-Inferiority Trials with Binary Data.
    15. Sample Size Calculations for Equivalence Trials with Binary Data.
    16. Sample Size Calculations for Precision Trials with Binary Data.
    17. Sample Size Calculations for Single Arm Clinical Trials and Studies with Finite Population Size.
    18. Sample Sizes for Clinical Trials with an Adaptive Design.
    19. Sample Size Calculations for Clinical Trials with Ordinal Data.
    20. Estimating the Number of Events for Clinical Trials with Survival Data for a Negative Outcome.
    21. Sample Size Calculations for Clinical Trials with Survival Data and a Positive Outcome.
    22. Sample Size Calculations for Clinical Trials with Survival Data Allowing for Recruitment and Withdrawal.
    23. Appendix.
    24. References.

    Steven A. Julious is a Professor of Medical Statistics at the University of Sheffield. His research interests include clinical trials, clinical trial design, early phase trials, and the development of new methodologies related to clinical trials.
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