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Related Experiment Videos

Sample size determination for matched-pair equivalence trials using rate ratio.

Nian-Sheng Tang1, Man-Lai Tang, Shun-Fang Wang

  • 1Department of Statistics, Yunnan University, Kunming 650091, China.

Biostatistics (Oxford, England)
|October 31, 2006
PubMed
Summary
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This study compares statistical methods for equivalence testing in matched-pair designs. Constrained maximum likelihood (CML) estimation offers superior performance and reliable sample size calculations for binary endpoints.

Area of Science:

  • Biostatistics
  • Clinical Trials
  • Statistical Methods

Background:

  • Equivalence testing is crucial for demonstrating therapeutic similarity.
  • Matched-pair designs are common in clinical studies, especially with binary endpoints.
  • Evaluating different statistical methods is essential for accurate trial design.

Purpose of the Study:

  • To compare Wald-type, logarithmic transformation, and Fieller-type statistics for 2-sided equivalence testing of the rate ratio in matched-pair designs.
  • To develop and evaluate sample size formulae based on constrained maximum likelihood (CML) estimation.
  • To assess the performance of these methods in terms of type I error rate and confidence interval width.

Main Methods:

  • Comparison of Wald-type, logarithmic transformation, and Fieller-type statistics.

Related Experiment Videos

  • Implementation using sample-based, constrained least squares, and CML estimation.
  • Development of sample size formulae controlling power or confidence width.
  • Simulation studies to evaluate statistical performance and sample size validity.

    • Main Results:

    • Statistics based on CML estimation generally outperform other methods.
    • CML-based methods show better control of type I error rates and narrower confidence intervals.
    • Asymptotically valid sample size formulae were developed, with close adherence to prespecified power and coverage probabilities.

    Conclusions:

    • Constrained maximum likelihood (CML) estimation is recommended for equivalence testing in matched-pair designs with binary endpoints.
    • The developed sample size formulae provide a reliable basis for study planning.
    • The findings are applicable to clinical laboratory studies and similar research settings.