Timeline for Permutation test vs Mann–Whitney U test
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Sep 27, 2021 at 13:25 | comment | added | Single Malt | This may have solved my confusion. This link treats the X and Y as peers en.wikipedia.org/wiki/Mann–Whitney_U_test, but as per your comment it can also be viewed as an ordinal or continuous variable against an independent group indicator. | |
| Sep 27, 2021 at 12:06 | vote | accept | Neggor | ||
| Sep 26, 2021 at 22:09 | comment | added | Frank Harrell | In the Wilcoxon test the dependent variable is the ordinal or continuous measure you are comparing, and the independent variable is the group indicator. | |
| Sep 26, 2021 at 18:06 | comment | added | Single Malt | Incorporating your comment, the generalization is in two “dimensions”: 1. The dependent variable has the number of ordinal variables (whereas Wilcoxon-Mann-Whitney has only two variables, neither of which, by the nature of the test needs to be termed dependent ). 2. Optional addition of explanatory variables. Is this correct? Handling ties better is more of a bonus, but could be viewed as a slight generalization as in a sense uses more of the data. | |
| Sep 26, 2021 at 2:05 | comment | added | Frank Harrell | The proportional odds model is for one Y. But yes to the other. Also it handles ties better than Wilcoxon | |
| Sep 25, 2021 at 18:10 | comment | added | Single Malt | The null hypothesis [for the Wilcoxon test is] that, for randomly selected values X and Y from two populations, the probability of X being greater than Y is equal to the probability of Y being greater than X. [Wikipedia Mann–Whitney U test]. I am assuming the proportional odd model means ordinal logistic regression. Thus I think the generalization in parentheses refers to 1. adding explanatory regressor variables, and 2. being able to compare more than two dependent variables. Is this a correct interpretation? | |
| Sep 25, 2021 at 12:18 | history | answered | Frank Harrell | CC BY-SA 4.0 |