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From |
David Airey <david.airey@Vanderbilt.Edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: RE: non-parametric MANOVA |

Date |
Tue, 28 Oct 2008 10:39:59 -0500 |

Here is the statistician/ecologist I remembered... She does permutation based on a distance measure. Software is provided. http://www.stat.auckland.ac.nz/~mja/Programs.htm http://www.stat.auckland.ac.nz/~mja/prog/PERMANOVA_UserNotes.pdf On Oct 28, 2008, at 10:23 AM, Lachenbruch, Peter wrote:

I'm in semi-agreement with Steve Self's approach: use a bootstrapon MANOVA. However, I seem to recall a paper in the Annals ofStatistics in the late 1970s by a statistician named Maronna whoshowed that the breakdown point (where contamination wiped you out)was at 1/k, the number of variables. Thus, if you have more than 7%contamination (I assume that means non-normal) you have a problem.But maybe I'm over-interpreting. My initial reaction was to proposea bootstrap approach as Steve suggested.Tony Peter A. Lachenbruch Department of Public Health Oregon State University Corvallis, OR 97330 Phone: 541-737-3832 FAX: 541-737-4001 -----Original Message-----From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick CoxSent: Tuesday, October 28, 2008 7:02 AM To: statalist@hsphsun2.harvard.edu Subject: st: RE: non-parametric MANOVAI find some inconsistency in this request. After all, what would anon-parametric MANOVA look like except something like a MANOVA,except that your data have been transformed to ranks? If you arehappy to reduce your data to ranks, why cavil at some othertransformation, which typically would lose less information?Further, my visceral instinct is that MANOVA is more robust to non-normality than people fear.More positively, if this were my problem, I might do 1. MANOVA on original data 2. MANOVA on rank-transformed dataIf the conclusions were substantively similar, stop there.Otherwise, consider what specific transformations were advisable.Nick n.j.cox@durham.ac.uk Jochen SpäthI want to do a Manova (14 different dependent variables, 2 mainfactors) and am stuck with the problem that most of my fourteenvariables are not normally distributed (and I do not want totransform them in order to get them normal since I have only remoteaccess to the data which complicates things a lot). So, my questionis: is there a way to do such a MANOVA in STATA using non-parametrictechniques (the -kwallis- command allows only for one factor and onedependent variable as far as I know)?* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

* * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: non-parametric MANOVA***From:*Jochen Späth <jochen.spaeth@iaw.edu>

**st: RE: non-parametric MANOVA***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**st: RE: RE: non-parametric MANOVA***From:*"Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>

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