-------- Original Message --------
Subject: RE: Relative warp question
Date: Tue, 09 Feb 2010 21:43:00 -0500
From: F. James Rohlf <[email protected]>
Organization: Stony Brook University
To: [email protected]
References: <[email protected]>
An analysis of relative warps is just a PCA using the weight matrix (matrix
of partial warp scores) as the data matrix. The partial warps are the
variables. If some variable had high loadings on the first few dimensions
then one might be tempted to do a t-test using that variable. However, in
just cases the variable was selected because of its empirical pattern so the
t-test would have to be adjusted to allow for multiple testing. It is not
clear how large the correction should be. It was selected based on a linear
combination and there are an infinite number of such linear combinations.
One should at least correct for the number of variables (partial warps) that
could possibly be considered for testing. Of course, once you find that a
particular partial warp shows a 'significant' difference it is unclear what
you should do next. Partial warps are usually not too interesting by
themselves. Their purpose is to simply span a space that captures all
possible shape variation for a given set of landmarks.
----------------------
F. James Rohlf, Distinguished Professor
Dept. Ecology and Evolution, Stony Brook University, NY 11794-5245
-----Original Message-----
From: morphmet [mailto:[email protected]]
Sent: Tuesday, February 09, 2010 3:12 PM
To: morphmet
Subject: Relative warp question
-------- Original Message --------
Subject: Relative warp question
Date: Mon, 1 Feb 2010 09:29:50 -0500
From: Richards Paul <[email protected]>
To: <[email protected]>
Hi , I am applying relative warp analysis to a population of land
snails, but I am new to all the theory and methods. I'm doing a
preliminary analysis to see if shell colour (i.e. dark, intermediate,
light) is associated with differences in shape. I have run the relative
warp analysis using tpsrelw, but have a few queries about using the
output and potential analysis.
RW1 to 3 appear to describe the apparent shape variance I am interested
in (i.e. high spired vs flat and aperture size). Do the relative warps
correspond directly to the identical partial warps in the weight matrix
(e.g. RW1 scores column corresponds to the first variable column in the
weight matrix)? If so could I take the first variable in the weight
matrix (assuming it corresponds to RW1) and perform a T test just for
this variable between my dark and light colour groups? I have tried
using a MANOVA approach, but because these samples weren't collected
specifically with this analysis in mind I am lacking enough samples in
each of my colour groups to get sufficient power, but I think a T test
on a per variable basis should be OK in the first instance.
I would be most grateful for any advice, and apologise if I have
overlooked something obvious!
Thanks, Paul
----------------
Paul Richards
School of Biology
University of Nottingham
University Park
NG7 2RD
+44 (0)115 8213128
[email protected]
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