Request for advice: Multivariate Wilcoxon Test

Hello, Faith,

this is a rather not R-related, but statistical question for which you 
should probably seek (professional?) advice. Nevertheless, as unspecific 
as you formulated it, you may want to look at Friedman's test which 
allows to use a (second) blocking variable, or at a regression approach. 
If you are really kean on a nonparametric _multivariate_ method the 
references below *may* be helpful. The first is really mathematical, the 
second more applied.

 ?Hth? --? Gerrit

@misc{puri1971nonparametric,
address = {New York {[u.a.]},

author = {Puri, Madan Lal},

isbn = {0471702404},

series = {Wiley series in probability and mathematical statistics},

title = {Nonparametric methods in multivariate analysis},

year = 1971

}


@misc{pesarin2010permutation,
address = {Chichester},

author = {Pesarin, Fortunato},

isbn = {0470516410},

series = {Wiley series in probability and statistics},

title = {Permutation tests for complex data : theory, applications and 
software},

year = 2010

}



Am 29.08.2023 um 20:56 schrieb Ebhodaghe Faith:

Hello,

I performed an unpaired Wilcoxon test on a continuous measure with
non-parametric distribution and detected a significant difference between
two levels of an independent variable. However, I suspect that another
independent variable could be confounding this outcome. Could you kindly
advise on how I can control for this possible confounder using a
multivariate Wilcoxon test? I'm not quite sure how to go about this.

Thank you,
Faith

	[[alternative HTML version deleted]]

_______________________________________________
R-sig-mixed-models at r-project.org  mailing list
https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models