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

Bruno C bruno.rproject at gmail.com
Thu Jan 19 15:31:56 CET 2017


Bruno.rproject at gmail.com

Em qui, 19 de jan de 2017 05:22, <michael.eisenring at agroscope.admin.ch>
escreveu:

> 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
>
> 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>
> www.agroscope.ch<http://www.agroscope.ch/>
>
> 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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>
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