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.eisenr...@agroscope.admin.ch<mailto:michael.eisenr...@agroscope.admin.ch> www.agroscope.ch<http://www.agroscope.ch/> Von: Cade, Brian [mailto:ca...@usgs.gov] Gesendet: Mittwoch, 18. Januar 2017 18:20 An: Eisenring Michael Agroscope <michael.eisenr...@agroscope.admin.ch> Cc: r-help@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: ca...@usgs.gov<mailto:brian_c...@usgs.gov> tel: 970 226-9326 On Wed, Jan 18, 2017 at 10:00 AM, <michael.eisenr...@agroscope.admin.ch<mailto:michael.eisenr...@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.eisenr...@agroscope.admin.ch<mailto:michael.eisenr...@agroscope.admin.ch><mailto:michael.eisenr...@agroscope.admin.ch<mailto:michael.eisenr...@agroscope.admin.ch>> www.agroscope.ch<http://www.agroscope.ch><http://www.agroscope.ch/> [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org<mailto:R-help@r-project.org> mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
