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Sample size planning for rank-based multiple contrast tests.

Anna Pöhlmann1, Edgar Brunner2, Frank Konietschke1

  • 1Institute of Biometry and Clinical Epidemiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

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|April 18, 2024
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Summary
This summary is machine-generated.

This study introduces new sample size planning methods for rank-based multiple contrast tests. These accurate statistical planning tools help researchers determine the necessary sample sizes for detecting treatment effects.

Keywords:
multiple contrast testnonparametric procedurepower considerationssample size determinationsteel test

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Area of Science:

  • Biostatistics
  • Statistical Methods

Background:

  • Rank methods are established for comparing independent groups.
  • Statistical planning for sample size determination in rank-based tests is underdeveloped.

Purpose of the Study:

  • To develop numerical algorithms for sample size planning in pseudo-rank-based multiple contrast tests.
  • To provide accurate sample size estimators for rank-based statistical analyses.

Main Methods:

  • Development of numerical algorithms for sample size estimation.
  • Discussion of treatment effects and variance parameter approximation.
  • Comparison of pairwise versus global rank methods.

Main Results:

  • Developed accurate sample size estimators for pseudo-rank-based multiple contrast tests.
  • Simulation studies confirmed the accuracy of the proposed sample size methods.
  • Demonstrated the practical application through a real data example.

Conclusions:

  • The developed methods provide essential tools for sample size planning in rank-based statistical tests.
  • Accurate sample size determination enhances the reliability of detecting treatment effects.
  • The study bridges a gap in statistical planning for rank-based comparative studies.