Hi Alex,

Another type of allometry that is worth mentioned is the static allometry.
So, if you want to remove this allometry effect (differences in shape in a
same age group in adults, per example) you can use the same regression.

Cheers
Carlos

On Sat, Mar 28, 2015 at 8:04 PM, <oliverhoo...@prstatistics.co.uk> wrote:

> 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 <ro...@life.bio.sunysb.edu> 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:<ryanfel...@gmail.com>]
> > Sent: Friday, March 27, 2015 7:34 AM
> > To: Alex Marshall
> > Cc: <morphmet@morphometrics.org>
> > 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>
> > <ryanfel...@gmail.com>
> > (201)981-8642
> >
> >
> >
> > On Fri, Mar 27, 2015 at 7:49 AM, Alex Marshall <<
> alpmar...@googlemail.com>> 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
> > > <alexander.marshall...@ucl.ac.uk>
> > >
> > > --
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-- 
Carlos Eduardo R. D. Alencar - Biólogo, PhD. - Academia.edu Profile
<https://ufrn.academia.edu/CaducasRochaDuarte>
carlosce2...@gmail.com
Grupo de Estudos em Ecologia e Fisiologia de Animais Aquáticos - GEEFAA [
www.geefaa.com]

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