-------- Original Message --------
Subject: Re: PCA & CVA questions
Date: Thu, 4 Jun 2009 06:18:04 -0700 (PDT)
From: Joseph Kunkel <[email protected]>
To: [email protected]
CC: Joseph Kunkel <[email protected]>
References: <[email protected]>
From my understanding you are confusing two different objectives.
That the two groups are significantly different is based on the mean
difference between the groups and this can be made more significant by
increasing the sample size.
But the PC is demonstrating the irreducible overlap of the two
populations which could change a bit with sample size but is a fact of
life that must be lived with based on your current traits measured.
One might never be able to discriminate an individual using the
measures you have used but that just indicates the stage of divergence
of the two sampled populations or species.
Joe Kunkel
On Jun 4, 2009, at 8:58 AM, morphmet wrote:
-------- Original Message --------
Subject: PCA & CVA questions
Date: Wed, 3 Jun 2009 19:25:10 -0700 (PDT)
From: Kimberly Tice <[email protected]>
To: [email protected]
Hi,
I am new to the morphometrics world, and am having a bit of trouble
figuring out what tests to use to analyze my data and how to interpret
them. I was hoping someone might be able to offer a bit of advice...
I have two types of snails, and I want to determine if they are
different shapes. I've been using the IMP programs, and when I
perform
a principal components analysis, I have 1 distinct principal
component,
but the two different groups are almost completely overlapping along
that PC. I did a MANOVA of all of the partial warps/uniform warps,
but
in this case, I found that the groups were significantly different.
How
do I reconcile this with the PCA? Is there any way to determine
whether
the differences in the MANOVA are "biologically significant" or
exactly
what the shape differences are? Is it appropriate to do an ANOVA on
one
principle component?
I also did a CVA, and found 1 significant CV, with an eigenvalue of
0.8. What does the eigenvalue mean? Is there any way to determine
how
important this CV is in terms of the amount of variation it explains?
I know these are relatively basic statistics questions, but these
tests
are new to me. I'd really appreciate any advice you might have or
information about resources that might be helpful.
Thank you!
Kim
[email protected] <mailto:[email protected]>
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Joseph G. Kunkel, Professor
Biology Department
University of Massachusetts Amherst
Amherst MA 01003
http://www.bio.umass.edu/biology/kunkel/
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