Sample size calculation for Mann-Whitney U test with five methods


  • Xiaoping Zhu Department of Biostatistics and Data Management, Regeneron Pharmaceuticals, New Jersey, USA



Mann-Whitney U test, Nonparametric, Sample size, Power, Monte Carlo simulation


Background: Precise sample size estimation plays a vital role in the planning of a study specifically for medical treatment expenses that are expensive and studies that are of high risk.

Methods: Among a variety of sample size calculation methods for the nonparametric Mann-Whitney U test, five potential methods are selected for evaluation in this article. The evaluation of method performance is based on the results obtained from high precision Monte Carlo simulations.

Results: The sample size deviations (from the simulation ones) are performance indicators. The sum of the squared deviations over all scenarios is used as the criterion for ranking the five methods. For power comparisons, the percentage errors (relative to the simulated powers) are used. The effect size and target power both have large impacts on the minimum required sample sizes.

Conclusions: Based on the ranking criterion, Shieh's method has the best performance. Noether's method always overestimates the minimum required sample sizes but not too severe.

Author Biography

Xiaoping Zhu, Department of Biostatistics and Data Management, Regeneron Pharmaceuticals, New Jersey, USA

Department of Biostatistics and Data Management

Senior Director Biostatistics


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