Calculate a Mann-Whitney-Wilcoxon test for a difference between treatment levels using nested ranks. This test can be used when observations are structured into several groups and each group has received both treatment levels. The p-value is determined via bootstrapping. The nested ranks test is intended to be one possible mixed-model extension of the Mann-Whitney-Wilcoxon test, for which treatment is a fixed effect and group membership is a random effect.
|Author||Douglas G. Scofield [aut, cre]|
|Date of publication||2015-06-06 14:40:26|
|Maintainer||Douglas G. Scofield <firstname.lastname@example.org>|
|License||LGPL-3 | file LICENSE|
nestedRanksTest: Mann-Whitney-Wilcoxon ranks test when data are in groups.
nestedRanksTest-package: Mann-Whitney-Wilcoxon ranks test when data are in groups.
nestedRanksTest_weights: Calculates weights for 'nestedRanksTest' based on group...
nestedRanksTest_Z: Calculates Z-score from ranks.
plot.htest_boot: Diagnostic plot of result held in 'htest_boot' object
print.htest_boot: Print result held in 'htest_boot' object
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