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Sample size recalculation using conditional power.

J S Denne1

  • 1Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285, U.S.A. denne.jonathan@lilly.com

Statistics in Medicine
|August 28, 2001
PubMed
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This study introduces a new method for sample size recalculation in clinical trials using an internal pilot. It ensures the study maintains its power to detect a true difference while preventing an increased Type I error rate.

Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Statistical Methods

Background:

  • Sample size determination is crucial for clinical trial power.
  • Internal pilot studies are used to adjust sample size based on nuisance parameters.
  • Existing methods may inflate Type I error rates by not accounting for observed data.

Purpose of the Study:

  • To propose a novel method for sample size recalculation using an internal pilot.
  • To maintain the probability of rejecting the null hypothesis conditional on observed data.
  • To prevent Type I error rate inflation in sequential trial designs.

Main Methods:

  • Developed a method to recalculate the target sample size based on observed data.
  • Utilized an internal pilot study to estimate nuisance parameters.

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  • Employed a two-group error-spending sequential test framework.
  • Modified the sequential test to control the Type I error rate.

    • Main Results:

    • The proposed method ensures the desired power is maintained throughout the study.
    • It accurately accounts for data from the internal pilot in sample size adjustments.
    • The Type I error rate is effectively controlled, preventing inflation.

    Conclusions:

    • The proposed internal pilot method provides a robust approach to sample size recalculation.
    • This method enhances the reliability of clinical trial results by maintaining statistical power and controlling error rates.
    • It offers a valuable tool for adaptive clinical trial design.