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Related Experiment Videos

Sample size determination for repeated measurements in bioequivalence test

K J Lui1

  • 1Department of Mathematical Sciences, College of Sciences, San Diego State University, California 92182-7720, USA.

Journal of Pharmacokinetics and Biopharmaceutics
|August 1, 1997
PubMed
Summary

This study presents a method for calculating sample sizes in clinical trials when multiple measurements are taken per subject. It helps determine the optimal number of subjects needed for a bioequivalence test, balancing cost and statistical power.

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Pharmacokinetics

Background:

  • Reliable outcome measurement is crucial in clinical trials.
  • High costs associated with acquiring new subjects can impact trial feasibility.
  • Repeated measurements per subject can enhance statistical power or reduce overall costs.

Purpose of the Study:

  • To develop an asymptotic procedure for calculating sample size in bioequivalence tests with repeated measures.
  • To evaluate the accuracy of the proposed sample size calculation method.
  • To provide guidance on optimizing the number of repeated measurements per subject.

Main Methods:

  • Development of an asymptotic sample size calculation procedure for bioequivalence trials.
  • Utilizing Monte Carlo simulations to assess the accuracy of the approximate sample size calculations.

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  • Analysis of scenarios where multiple measurements per subject are considered.

    • Main Results:

    • The study provides a method to determine the required number of subjects per group for a given power in bioequivalence testing.
    • The asymptotic procedure offers an efficient way to estimate sample sizes under repeated measurements.
    • Simulation results validate the accuracy of the proposed sample size calculation approach.

    Conclusions:

    • The developed procedure is valuable for designing clinical trials with repeated measures, especially when subject recruitment is costly.
    • Optimizing the number of repeated measurements is key to achieving desired statistical power efficiently.
    • This methodology aids in cost-effective and statistically sound bioequivalence trial design.