Department of Mathematics and Technology, RheinAhrCampus, Koblenz University of Applied Sciences, Remagen, Germany.
Institute for Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany.
PLoS One. 2024 Aug 21;19(8):e0309074. doi: 10.1371/journal.pone.0309074. eCollection 2024.
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.
最近，有人建议在应用两样本 Wilcoxon-Mann-Whitney 检验之前省略 tied 观测值，McGee M. 等人（2018）。通过模拟研究，我们认为使用所有数据（包括 tied 值）的精确检验是一种更好的方法。包含 tied 观测值的精确检验可以保证 I 型错误率，并且与省略 tied 观测值后的相应检验相比，更好地利用了显著性水平和更大的功效。省略 ties 可能会导致样本形状发生很大变化，从而违反了基础检验假设。因此，无论是否存在 ties，相对于以相同的方式分析整个数据集，建议省略 ties 值，这在理论和实践上都不能得到支持，最好使用精确的排列检验。
