# Should people stop using the WMW rank-sum test?

**URL:** <https://discourse.datamethods.org/t/should-people-stop-using-the-wmw-rank-sum-test/540>\
**Category:** journal club\
**Tags:** stat-test, nonparametric\
**Created:** [August 31, 2018, 1:12am UTC](https://discourse.datamethods.org/t/should-people-stop-using-the-wmw-rank-sum-test/540 "2018-08-31T01:12:31Z")\
**Posts on this page:** 1\
**Showing post:** 15

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**Author:** ![RGNewcombe](https://discourse.datamethods.org/letter_avatar_proxy/v4/letter/r/85f322/32.png) [@RGNewcombe](https://discourse.datamethods.org/u/RGNewcombe)\
**Post date:** [October 4, 2018, 7:03pm UTC](https://discourse.datamethods.org/t/should-people-stop-using-the-wmw-rank-sum-test/540/15 "2018-10-04T19:03:27Z")

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As with so many tests, the real issue is whether significance testing should be paramount. It should not. Mann-Whitney U easily turns into an index U/mn by dividing by the product of the two sample sizes. U/mn is a very useful effect size measure and is equivalent to the area under the ROC curve. It equals 0.5 on H0 and 0 or 1 if the two samples don’t overlap. Report it with a confidence interval, see  
Newcombe RG. Confidence intervals for an effect size measure based on the Mann-Whitney statistic. Part 2: Asymptotic methods and evaluation. Statistics in Medicine 25, 4, 559-573. Feb 2006. DOI: 10.1002/sim.2324  
Excel resources for calculating confidence intervals for this and other effect size measures related to proportions are available at  
[http://profrobertnewcomberesources.yolasite.com/](http://profrobertnewcomberesources.yolasite.com/)

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