Christy,
If your model is: shape~eco.group, then the LS means for each ecological group
can be extracted. These can then be examined visually by using TPS from the
overall reference to each LS mean.
Dean
Dr. Dean C. Adams
Professor
Department of Ecology, Evolution, and Organismal Biology
Department of Statistics
Iowa State University
www.public.iastate.edu/~dcadams/<http://www.public.iastate.edu/~dcadams/>
phone: 515-294-3834
From: Christy Hipsley [mailto:[email protected]]
Sent: Monday, November 28, 2016 6:44 PM
To: MORPHMET <[email protected]>
Subject: [MORPHMET] Re: the problem with CVA... or is it?
Dean - so in this case how would I use the LS means for each group (here I have
only one factor and no slope) as the coordinates for the target specimen and
the mean shape for all species as the reference?
Sorry I should have been more clear - the CVA was done using individual shapes,
so n=161, and the bgPCA was on species means (the basic unit of my study), so
n=92. I did the CVA on the individuals so as not to have more "groups" than
variables and avoid false separation. I've seen your bat paper and indeed
thought of doing something similar. I just liked the CVA because it showed very
well the environmental gradient along which the different cranial shapes fall.
On Tuesday, November 29, 2016 at 10:04:02 AM UTC+11, Christy Hipsley wrote:
Dear Morphmet-ers,
I'm seeking advice on methods for visualizing shape features that distinguish
multiple groups using GM. I know CVA has fallen out of favor for a number of
reasons discussed here - e.g., more variables than groups, nonisotropic
variation:
Mitteroecker, P., and Bookstein, F. 2011. Linear discrimination, ordination,
and the visualization of selection gradients in modern morphometrics. Evol.
Biol. 38:100–114.
Klingenberg, C. P., and Monteiro, L. R. 2005. Distances and directions in
multidimensional shape spaces: Implications for morphometric applications.
Syst. Biol. 54:678–688.
Although given these limitations, is it really expected to give completely
false results regarding the visualization of shape changes? In my study sytem,
I show that ecological groups have statistically different cranial shapes,
using both Procrustes ANOVA and PGLS. Now I simply want to visualize what the
main features are that distinguish them, preferably using warps or wireframes,
so that those changes must be directly relateable to the original landmark
coordinates. I did that using individual specimens instead of species means, so
I have 161 individuals vs 144 variables (48 landmarks*3D). I also did a
between-group PCA on the species means which shows the same pattern, so is it
technically "wrong" to show both?
Thanks for any feedback on this issue, and I would appreciate to hear any
alternative methods that people might use. I use MorphoJ and Geomorph for
analyses.
Best,
Christy
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