> > >Hope this helps some. Let me know if you want information about >SuperAnova or PC-Ord. > >Steve > > > > > >At 7:31 PM -0500 8/21/06, Chris Taylor wrote: >>Hey Steve. What do you run those nested discriminant analyses with? >>Hope all is well! >> >>Chris >> >>At 11:18 AM 8/21/2006, you wrote: >>>Matthew, >>> >>>You may also want to do a nested discriminant analysis to determine >>>whether the mean morphology differs among populations, while >>>controlling for species. The nesting of populations within species >>>should "correct for phylogeny", unless there is something I'm missing >>>here (e.g., phylogenetic relationships among populations within >>>species). Don't really see the need for PICs. Make sure the >>>assumptions of multivariate normality are met. >>> >>>Steve >>> >>> >>> >>> >>> >>>
Matthew, >>>At 10:30 AM -0400 8/18/06, Matthew Gifford wrote: >>>>I am looking for advice regarding principal components analysis. My >>>>situation is as follows: I have a >>>>data set of morphological measurements for 6 "taxa" (4 populations >>>>of one species and 2 >>>>populations of another). I read somewhere that in order to do a PCA >>>>appropriately, one needs to >>>>have more "taxa" (i.e., rows) than measurement variables (i.e., >>>>columns). This is to avoid negative eigenvalues. But if you only focus on the first few eigenvalues, this should be no problem. If I use mean values for >>>>each "taxon" then I viiolate this assumption. To circumvent this, >>>>is it valid to do a PCA on all data >>>>and use mean PC scores? No need to do this. And if you do, it doesn't solve the engative eigenvalue problem. No need for multivariate normality neither. I will be using this information in >>>>phylogenetically independent contrasts >>>>analysis looking at ecomorphological relationships. The real problem with morphometric data is that the first axes become size and shape axes. See: Jolliffe IT (2002) Principal Component Analysis. Springer: New York and: Claude, J., Jolliffe, I.T., Zuur, A.F., Ieno, E.N. and Smith, G.M. Multivariate analyses of morphometric turtle data size and shape. Chapter 30 in Zuur, AF., Ieno, EN, Smith. GM. (Expected publication date: March 2007). Springer Kind regards, Alain Zuur www.highstat.com Any >>>>thoughts/opinions are most appreciated. >>>> >>>>Best, >>>> >>>>Matthew E. Gifford >>>>Ph.D. Candidate >>>>Washington University, St. Louis, MO >>>>http://www.biology.wustl.edu/larsonlab/people/Gifford/Matt's_webpage.ht ml >>> >>> >>>-- >>>Department of Biology >>>PO Box 1848 >>>University of Mississippi >>>University, Mississippi 38677-1848 >>> >>>Brewer web page - http://home.olemiss.edu/~jbrewer/ >>> >>>FAX - 662-915-5144 >>>Phone - 662-915-1077 >> >>*************************************************************** >>Christopher M. Taylor >>Associate Professor of Biological Sciences >>Dept. of Biological Sciences >>Mississippi State University >>Mississippi State, MS 39762 >>Phone: 662-325-8591 >>Fax: 662-325-7939 >>Email: [EMAIL PROTECTED] >>http://www2.msstate.edu/~ctaylor/ctaylor.htm > > >-- >Department of Biology >PO Box 1848 >University of Mississippi >University, Mississippi 38677-1848 > >Brewer web page - http://home.olemiss.edu/~jbrewer/ > >FAX - 662-915-5144 >Phone - 662-915-1077 >=========================================================================
