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Design of multi-centre trials with binary response.

Vladimir Dragalin1, Valerii Fedorov

  • 1Research Statistics Unit, Biomedical Data Sciences, GlaxoSmithKline Pharmaceuticals, Collegeville, PA 19426-0989, USA. vladimir.2.dragalin@gsk.com

Statistics in Medicine
|October 28, 2005
PubMed
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We developed a correlated beta-binomial model for multi-centre trials. This statistical approach simplifies parameter estimation and provides formulas for precision based on patient and center numbers.

Area of Science:

  • Biostatistics
  • Clinical Trials Methodology

Background:

  • Multi-centre trials involve complex data structures.
  • Accurate statistical modeling is crucial for reliable clinical trial results.

Purpose of the Study:

  • To introduce a novel correlated beta-binomial model for binary outcomes in multi-centre trials.
  • To simplify the estimation of model parameters by avoiding complex numerical integrations.

Main Methods:

  • Development of a correlated beta-binomial model.
  • Derivation of a closed-form likelihood function.
  • Calculation of the asymptotic variance-covariance matrix for the Maximum Likelihood Estimator (MLE).

Main Results:

  • The proposed model offers a closed-form likelihood, facilitating parameter estimation.

Related Experiment Videos

  • The derived formulae provide a straightforward relationship between trial size (number of centres, total patients) and the precision of parameter estimates.
  • Avoidance of computationally intensive multivariate numerical integrations.

    • Conclusions:

    • The correlated beta-binomial model provides an efficient and practical statistical framework for binary data in multi-centre trials.
    • The derived formulae offer valuable insights for study design and sample size calculations to achieve desired precision.