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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