Power and Sample Size Calculations

  • Jürgen Bock
Chapter

Abstract

Sample size calculations belong to the routine steps in the design of studies for drug development. The importance of the determination of the appropriate sample size for clinical studies is emphasized in the ICH Guidelines: “The number of subjects in a clinical trial should always be large enough to provide a reliable answer to the question addressed.” A simple example may help to understand the basic problem.

Keywords

Confidence Limit Sample Size Calculation Total Sample Size Bioequivalence Study Sequence Group 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Amaratunga, D. (1999). Searching for the right sample size. The American Statistician 53, 52–55.Google Scholar
  2. Bock, J. (1998). Bestimmung des Stichprobenumfangs für biologische Experimente und kontrollierte klinische Studien. R. Oldenbourg Verlag, München.Google Scholar
  3. Guilbaud, O. (1997). An approach to sample size determination for confidence intervals proposed by hsu. Proceedings of the Biopharmaceutical Section of the American Statistical Association pp. 179–184.Google Scholar
  4. Hauschke, D., Kieser, M., Diletti, E., and Burke, M. (1999). Sample size determination for proving equivalence based on the ratio of two means for normally distributed data. Statist. Med. 18, 93–105.CrossRefGoogle Scholar
  5. Hsu, J. (1998). Sample size computation for designing multiple comparison experiments. Computational Statistics Data Analysis 7, 79–91.CrossRefGoogle Scholar
  6. ICH Harmonized Tripartite Guideline: Statistical Principles for Clinical Trials (1998).Google Scholar
  7. Jones, B., and Kenward, M. (1989). Design and Analysis of Cross-Over Trials. Chapman Hall, London.MATHGoogle Scholar
  8. Sasabuchi, S. (1988). A multivariate one-sided test with composite hypotheses when the covariance matrix is completely unknown. Memoirs of the Faculty of Science Kyushu University 42, 37–46.MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Jürgen Bock
    • 1
  1. 1.F. Hoffmann-La Roche AGBaselSwitzerland

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