SAMPLE SIZES OF CLINICAL TRIALS: FOR SCIENCE AND DECISION MAKING(Keynote Papers)

    • Brown Jr.
    • Division of Biostatistics, Department of Health Research and Policy, School of Medicine, Stanford University
    • Halpern Jerry
    • Division of Biostatistics, Department of Health Research and Policy, School of Medicine, Stanford University

Abstract

Implicit assumptions in the current use of the Neyman-Pearson approach to sample size calculations when planning for medical clinical trials are noted. The pros and cons of using decision theory instead of or to supplement Neyman-Pearson when planning such trials are discussed. Why the sample sizes suggested by these two approaches are often very different is explained. A computer program is presented and described for the two arm completely randomized trial with a binary endpoint. This program is available from the WEB, requires simple practical input, and is intended to be easily used by the clinical scientist and biostatistician. An example of its use is given which illustrates the additional quantitative insights afforded by using decision theory together with the more customary Neyman-Pearson approach to design clinical trials.

Journal

Journal of the Japanese Society of Computational Statistics   [List of Volumes]

Journal of the Japanese Society of Computational Statistics 15(2), 27-35, 2003-06  [Table of Contents]

Japanese Society of Computational Statistics

References:  18

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Codes

  • NII Article ID (NAID) :
    110001235160
  • NII NACSIS-CAT ID (NCID) :
    AA10823693
  • Text Lang :
    ENG
  • Article Type :
    REV
  • ISSN :
    09152350
  • Databases :
    CJP  NII-ELS 

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