Gabi,
If you are interested in the relationship between a set of shape variables
(your Procrustes coordinates) and a single variable (e.g. precipitation),
you could use a Multivariate Regression in MorphoJ, or better, a Procrustes
ANOVA (which is procD.lm() in geomorph. Not sure if the Procrustes ANOVA in
morphoJ can do this...). If you have a set of environmental variables and
wish for them to be treated together, maybe 2 block partial least squares
can be used.
I would NOT use a single PC axis in a bivariate analysis of correlation
with an environmental variable. Use all the shape variables and a
Multidimensional method such as multivariate regression or Procrustes
ANOVA.
Good luck!
Emma
P.S. It my own personal opinion, but every time shape data is reduced to a
few PC axes and used in an analysis, a fairy dies... ;)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Emma Sherratt, PhD.
Lecturer in Zoology,
Zoology Division, School of Environmental and Rural Science,
Room L120 Bldg C02,
University of New England,
Armidale, NSW, Australia, 2351
Tel: +61 2 6773 5041
email: emma.sherr...@une.edu.au
Caecilians are legless amphibians...
* __
(\ .-. .-. /_")
\\_//^\\_//^\\_//
`"` `"` `"`*
learn more about them here: www.emmasherratt.com/caecilians
On 11 February 2015 at 09:28, gnavas <gna...@mlml.calstate.edu> wrote:
> Hi guys,
>
> Thanks a ton for your quick responses. Emma, the CV scores were so
> tempting to use for comparison to other variables...What would you suggest
> would be a more appropriate index to use in order to compare the shape
> ordination results to say, environmental variables, such as sediment size
> (I am studying clam morphology differences)?
>
> On Tuesday, February 10, 2015 at 2:00:04 PM UTC-8, Emma Sherratt wrote:
>>
>> Gabi,
>>
>> While Michael is correct i how you can export the CV scores from MorphoJ,
>> I would highly recommend against exporting the CV scores to plot against
>> other parameters. The reason being that CVA should not be used like
>> Principal Components Analysis. CVA axes should be used for inspecting the
>> data for the aspects of shape that delimit and discriminate between two or
>> more groups. Not as reduced axes for use in correlation tests.
>>
>> Emma
>>
>>
>>
>> ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
>>
>> Emma Sherratt, PhD.
>>
>> Lecturer in Zoology,
>> Zoology Division, School of Environmental and Rural Science,
>> Room L120 Bldg C02,
>> University of New England,
>> Armidale, NSW, Australia, 2351
>> Tel: +61 2 6773 5041
>> email: emma.s...@une.edu.au
>>
>> Caecilians are legless amphibians...
>>
>> * __
>> (\ .-. .-. /_")
>> \\_//^\\_//^\\_//
>> `"` `"` `"`*
>>
>> learn more about them here: www.emmasherratt.com/caecilians
>>
>>
>>
>>
>> On 11 February 2015 at 08:33, gnavas <gna...@mlml.calstate.edu> wrote:
>>
>>> Dear Morphometrics Wizards,
>>>
>>> I have 2 questions for which I am hoping to get help on:
>>>
>>> Question 1. CVA analysis: I have 6 sites. Within each site I have at
>>> least 22 samples. When I ran a CVA comparison on these 6 sites in Morpho J.
>>> I was hoping to find a way to get an actual value for each of my samples
>>> that plotted. So, for instance, CV1 values for each specimen, and the same
>>> for CV2. In the results tab, I can only find data relevant to my landmarks
>>> and canonical variates coefficients relating to lanmarks.
>>>
>>> I would love to figure out a way to export my CV1 and CV2 values for
>>> each specimen to then plot that against other parameters that may be
>>> effecting shape at those 2 or more canonical variate axes. Has anyone run
>>> into this problem, and found a solution?
>>>
>>> Question 2. Discriminant Analysis:
>>> Again, 6 sites with 22 samples, but this time I was only able to compare
>>> 2 sites at a time. Has anyone ever been able to run 1 site against all
>>> remaining sites? It would be great to get an idea of how my sites compare
>>> to all others, rather than to just one other at a time. I suspect I have to
>>> play with my classifier variables, but I am not sure how to go about that.
>>> At this point, I have made 1 classifier variable that allows me to
>>> distinguish the different sites.
>>>
>>> If any of you have run into this or simply know how to do this, please
>>> let me know. I am also happy to give more detail on my study if that would
>>> help?
>>>
>>> Thank you in advance!
>>> Gabi
>>>
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>>>
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>>
>> --
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