A note on the Wilcoxon-Mann-Whitney test and tied observations

Recently, it was recommended to omit tied observations before applying the two-sample Wilcoxon-Mann-Whitney test McGee M. et al. (2018). Using a simulation study, we argue for exact tests using all the data (including tied values) as a preferable approach. Exact tests, with tied observations included guarantee the type I error rate with a better exploitation of the significance level and a larger power than the corresponding tests after the omission of tied observations. The omission of ties can produce a considerable change in the shape of the sample, and so can violate underlying test assumptions. Thus, on both theoretical and practical grounds, the recommendation to omit tied values cannot be supported, relative to analysing the whole data set in the same way whether or not ties occur, preferably with an exact permutation test.

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Publication Details

Journal
PLoS ONE
Published
2024-08-21
DOI
https://doi.org/10.1371/journal.pone.0309074
Citations
1
Primary Topic
Statistical Methods and Bayesian Inference
Type
article
Field-Weighted Citation Impact
0.71
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article

A note on the Wilcoxon-Mann-Whitney test and tied observations

Graeme D. Ruxton, Markus Neuhäuser
1 citations
PLoS ONE
Statistical Methods and Bayesian Inference
0.71
article

A note on the Wilcoxon-Mann-Whitney test and tied observations

Graeme D. Ruxton, Markus Neuhäuser
article en
1 citations

Abstract

Recently, it was recommended to omit tied observations before applying the two-sample Wilcoxon-Mann-Whitney test McGee M. et al. (2018). Using a simulation study, we argue for exact tests using all the data (including tied values) as a preferable approach. Exact tests, with tied observations included guarantee the type I error rate with a better exploitation of the significance level and a larger power than the corresponding tests after the omission of tied observations. The omission of ties can produce a considerable change in the shape of the sample, and so can violate underlying test assumptions. Thus, on both theoretical and practical grounds, the recommendation to omit tied values cannot be supported, relative to analysing the whole data set in the same way whether or not ties occur, preferably with an exact permutation test.

PLoS ONEVol. 19(8)
University of Bonn (DE), Koblenz University of Applied Sciences (DE), University of St Andrews (GB), Institut für Medizinische Biometrie, Informatik und Epidemiologie (DE)
Openalex Percentile: Top 27%
Statistical Methods and Bayesian Inference
0.71
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