[R] non-parametric manova with post-hoc test

[Bert Gunter]

You really need to go to the literature. The analysis of rank
transformed data has a long history going back to the 1970's/80's, at
least. See, e.g.

https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&uact=8&ved=0ahUKEwjDg_uGuM7RAhWmrVQKHaYRDb0QFggcMAA&url=http%3A%2F%2Fpeople.umass.edu%2Fbioep740%2Ftopics%2Famstat-1985-iman.pdf&usg=AFQjCNHcbe_1R6vRtMSBrMW9YIeFQxjb1Q&sig2=9JeOaP1f61m7REfmScefVg

There is even a Wikipedia entry for "Anova on Ranks".
So you really really should do some homework.

Moreover, statistical discussions are largely OT here.
stats.stackexchange.com is a more appropriate list if you wish to
continue online.

Cheers,
Bert


Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Wed, Jan 18, 2017 at 11:19 PM,  <michael.eisenring at agroscope.admin.ch> wrote:
> Dear Brian,
> Thank you for your answer.
> Another thing that came to my mind: Would it be possible just to separately rank-transform my 3 dependent  variables and then to conduct a normal MANOVA on this data?
>
>
> Thanks,
> Mike
> Eisenring Michael, Msc.
> PhD Student
>
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> michael.eisenring at agroscope.admin.ch<mailto:michael.eisenring at agroscope.admin.ch>
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>
> Von: Cade, Brian [mailto:cadeb at usgs.gov]
> Gesendet: Mittwoch, 18. Januar 2017 18:20
> An: Eisenring Michael Agroscope <michael.eisenring at agroscope.admin.ch>
> Cc: r-help at r-project.org
> Betreff: Re: [R] non-parametric manova with post-hoc test
>
> You could try a multi-response permutation procedure (MRPP) for multivariate hypothesis testing (null is groups come from a common distribution) without resorting to ranks.  There are no automated multiple comparison procedures, but one could either look at pairwise contrasts of group (if that is what you are implying by post-hoc testing) with some sort of correction procedure for multiple comparisons (e.g., Holm's sequential procedure).  Or similarly, comparisons with different subsets of the multivariate outcome variables (again, adjusting for multiple comparisons) across the grouping structure.  There are several R packages that I think implement MRPP but the Blossom package might be one of the better implementations in terms of alternatives provided (including permutation version of Hotelling's test).
>
> Brian
>
> Brian S. Cade, PhD
>
> U. S. Geological Survey
> Fort Collins Science Center
> 2150 Centre Ave., Bldg. C
> Fort Collins, CO  80526-8818
>
> email:  cadeb at usgs.gov<mailto:brian_cade at usgs.gov>
> tel:  970 226-9326
>
>
> On Wed, Jan 18, 2017 at 10:00 AM, <michael.eisenring at agroscope.admin.ch<mailto:michael.eisenring at agroscope.admin.ch>> wrote:
> Good day,
> I am looking for a way to perform a non parametric manova and to analyze the result using post-hoc tests (an equivalent of the kruskal wallis test for anova)
>
> In my book (discovering statistic using R) two tests are described Munzel and Brunners method (mulrank) and Choi and Mardens test (cmanova). Both are from the package WRS which unfortunately does not exist anymore (and WRS2 is not containing these tests). Furthermore the test do to my knowledge not allow post-hoc analyses-
>
> I would be grateful for your help
>
> Best,
> Mike
>
> Eisenring Michael, Msc.
> PhD Student
>
> Federal Department of Economic Affairs, Education and Research
> EAER
> Agroecology and Environment
> Biosafety
>
> Reckenholzstrasse 191, CH-8046 Zürich
> Tel. +41 44 37 77181
> Fax +41 44 37 77201
> michael.eisenring at agroscope.admin.ch<mailto:michael.eisenring at agroscope.admin.ch><mailto:michael.eisenring at agroscope.admin.ch<mailto:michael.eisenring at agroscope.admin.ch>>
> www.agroscope.ch<http://www.agroscope.ch><http://www.agroscope.ch/>
>
>
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