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Relations among Three Parametric Multiple Testing Methods for Correlated Tests.

Changchun Xie1

  • 1Division of Epidemiology and Biostatistics, Department of Environmental Health, University of Cincinnati; Center for Clinical and Translational Science and Training, University of Cincinnati, Ohio 45267, USA.

Journal of Statistical Computation and Simulation
|March 25, 2014
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Summary
This summary is machine-generated.

This study compares multiple testing methods for clinical trials, including flexible fixed-sequence (FFS) testing and adaptive alpha allocation (4A). Simulations investigate the relationships between these methods and a proposed weighted multiple testing correction (WMTC) to guide selection.

Keywords:
Bonferroni correctionCorrelated endpointsFixed-sequenceMultivariate normal distributionWeighted multiple testing correction

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Statistical Methodology

Background:

  • Clinical trials frequently involve multiple endpoints that exhibit correlations.
  • Controlling the family-wise type I error rate is crucial when analyzing multiple correlated endpoints.
  • Existing methods like flexible fixed-sequence (FFS) testing and adaptive alpha allocation (4A) address endpoint correlations.

Purpose of the Study:

  • To investigate the relationships between the adaptive alpha allocation (4A) method and both the flexible fixed-sequence (FFS) testing method and the weighted multiple testing correction (WMTC).
  • To provide tentative guidelines for selecting an appropriate multiple testing method in clinical trials with correlated endpoints.

Main Methods:

  • Conducting simulation studies to compare the performance of different multiple testing correction methods.
  • Evaluating methods including flexible fixed-sequence (FFS) testing, adaptive alpha allocation (4A), and a proposed weighted multiple testing correction (WMTC).

Main Results:

  • The study explores previously unexamined relationships between the 4A method and FFS, as well as between 4A and WMTC.
  • Simulation results provide insights into the comparative performance of these statistical approaches.

Conclusions:

  • The research aims to clarify the interplay between different multiple testing strategies for correlated endpoints.
  • Tentative guidelines will be offered to assist researchers in choosing the most suitable method for their specific clinical trial scenarios.