Hi Alex,

If you want to remove the effect of size on shape that is caused by ontogenetic 
allometry (differences in shape due to age/size per-say) you can regress the 
Procrustes coordinates of your samples on the centroid size  and then use the 
residuals.

Hope this helps,

Oliver Hooker
PR~Statistics


On 28 March 2015, F. James Rohlf <[email protected]> wrote:
> Procrustes superimposition only removes isometric size variation. Shape 
> changes that are a function of size (allometry) are not removed so a 
> regression of some sort is needed.
> 
> ____________________________________________
> F. James Rohlf, Distinguished Professor, Emeritus. Ecology & Evolution
> Research Professor, Anthropology
> Stony Brook University
> 
> -----Original Message-----
> From: Ryan Felice [mailto:<[email protected]>]
> Sent: Friday, March 27, 2015 7:34 AM
> To: Alex Marshall
> Cc: <[email protected]>
> Subject: Re: [MORPHMET] PC Ranks in Evolutionary PCA
> 
> 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
> <http://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]>
> > 
> > --
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> > 
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> > 
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