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 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). 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? I will be using this information in >phylogenetically independent contrasts >analysis looking at ecomorphological relationships. 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.html -- 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
