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
