Power and Sample Size Calculations in Clinical Trials with Multiple Primary Variables

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This article proposes a method of power and sample size calculation for confirmatory clinical trials, with the objective of showing superiority for all multiple primary variables, assuming normality of the variables. Since one sided <I>t</I>-statistics are used to evaluate statistical significance, the power is calculated based on a Wishart distribution. A Monte Carlo integration is used to calculate the expectation of conditional power, conditioned on Wishart variables, where random numbers are generated using the Bartlett's decomposition. Numerical examples revealed that the required sample size decreases with increases in the correlation coefficient, although the dependency is not large when the correlation coefficient is negative or when the effect sizes, on which power is calculated, are far different between variables. A SAS program (version 9.1) for the proposed method is provided in the Appendix.

収録刊行物

  • 計量生物学  

    計量生物学 27(2), 83-96, 2006-12-01 

    The Biometric Society of Japan

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各種コード

  • NII論文ID(NAID)
    10018385882
  • NII書誌ID(NCID)
    AA11591618
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    0918-4430
  • NDL 記事登録ID
    8596720
  • NDL 雑誌分類
    ZR1(科学技術--生物学)
  • NDL 請求記号
    Z74-B725
  • データ提供元
    CJP書誌  CJP引用  NDL  J-STAGE 
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