Hi Alex, I'm assuming that your shape data are landmark configurations that have been subjected to a Procrustes superimposition. is that correct? If so, I dont think the regression you described is really necessary- Procrustes analysis will remove the effects of size, orientation, and position.
What software are you using for your analysis? you might find it easier/more streamlined to use the phyl.pca function in the phytools R package. If you use that function, make sure that you are using the original shape data and not the independent contrasts of shape data. Good luck! -Ryan Ryan N. Felice, PhD Ohio University Department of Biological Sciences 107 Irvine Hall Athens, OH 45701 www.rnfelice.com [email protected] (201)981-8642 On Fri, Mar 27, 2015 at 7:49 AM, Alex Marshall <[email protected]> wrote: > Hello everyone, > I'm a MSci student new to morphometrics and this group. I'm studying > morphological integration in squamate crania and one of the things I'd like > to do is an Evolutionary PCA of all my species, accounting for phylogeny and > allometry. > > I think I do this correctly but in the PCA results the PCs are not ranked by > proportion of variance e.g. PC5 has greater % variance that PCs 3 & 4. Is > this normal? > > To conduct the evolutionary PCA I created independant contrasts of all my > shape data, regressed centroid size on shape and conducted PCA on the > residuals. After this I applied the resultant PC scores to another PCA of my > original data. > > Would anyone kindly confirm if this is the right way to do it? > > Many thanks, > > Alex Marshall > MSci Student > University College London > [email protected] > > -- > MORPHMET may be accessed via its webpage at http://www.morphometrics.org > > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org To unsubscribe from this group and stop receiving emails from it, send an email to [email protected].
