-------- Original Message --------
Subject: RE: CVA and MANOVA
Date: Wed, 27 Feb 2008 15:09:24 -0800 (PST)
From: F. James Rohlf <[EMAIL PROTECTED]>
Reply-To: <[EMAIL PROTECTED]>
Organization: Stony Brook University
To: <[email protected]>
References: <[EMAIL PROTECTED]>

Statistically (and geometrically) a matrix of relative warp scores is
just a matrix of principal component scores. If you keep all of the
dimensions for which the eigenvalues are > 0 then you are just doing a
rigid rotation of a multivariate space so ordination analyses,
probabilities computed in a MANOVA, etc. must be unchanged. If you
only use a few dimensions then you are projecting into a lower
dimensional space and thus losing information so subsequent analyses
can give different results. Difficult to predict in advance what the
consequences will be (it could be that dimensions that account for
relatively little of the overall variance just happen to be good at
distinguishing groups - that would be lost if you happened to have
discarded those dimensions.

If you use relative warps as your variables then to be able to
construct shapes you will have to back transform to coordinates. This
can be done (this operation is built into tpsRelw). For other
analyses, such as CVA based on relative warps you can use the trick of
using the tpsRegr program to regress shapes (your original tps file)
onto each vector of CVA scores. If you use all of the relative warp
dimensions then the CVA scores should be identical to those based on
the original matrix of partial warp scores or a matrix of GPA
coordinates after the invariant dimensions have been removed.

=========================
F. James Rohlf
Distinguished Professor, Stony Brook University
http://life.bio.sunysb.edu/ee/rohlf


-----Original Message-----
From: morphmet [mailto:[EMAIL PROTECTED]
Sent: Wednesday, February 27, 2008 5:39 PM
To: morphmet
Subject: Re: CVA and MANOVA

-------- Original Message --------
Subject:        Re: CVA and MANOVA
Date:   Wed, 27 Feb 2008 08:02:38 -0800 (PST)
From:   Cristian Correa <[EMAIL PROTECTED]>
To:     <[email protected]>
References:     <[EMAIL PROTECTED]>



Hi Amelia,

Comments from another beginner: I think you can use RW to reduce
dimensionality before conducting MANOVA. I don't see the problem,
unless
you're severely violating assumptions (in which case you can do
NPMANOVA). It may (or may not) be more difficult to visualize the
results of your analyses (depending on the RW obtained and kept)
because
you will be moving in the more integrated and distorted space of RW
compared to the more shape-comprehensive space of PW (using all PW).

You could use a few RW (e.g. the first two, if they account for much
of
the variance) in a MANOVA for statistic test. Then do a CVA to
visualize
significant differences between groups and get centroids for each
group.
It is very likely that each CV axis will pick up a different RW more
heavily. In this case it is easy to interpret morphological
differences
in each of the CV axes; you just have to move along the RW plots. I
don't think you can directly predict shape from the CVA using RW.
Can you?

In summary, I would go for RW if I really need to reduce
dimensionality,
otherwise I'd choose using the full set of PWs. But I'm a novice as
well
and I'd love to see the answers of experts.

Buena suerte!

Cristian


     ----- Original Message -----
     *From:* morphmet <mailto:[EMAIL PROTECTED]>
     *To:* morphmet <mailto:[email protected]>
     *Sent:* Wednesday, February 27, 2008 9:11 AM
     *Subject:* CVA and MANOVA

     -------- Original Message --------
     Subject: CVA and MANOVA
     Date: Wed, 27 Feb 2008 05:15:56 -0800 (PST)
     From: M. Amelia Chemisquy <[EMAIL PROTECTED]
     <mailto:[EMAIL PROTECTED]>>
     To: [email protected]
<mailto:[email protected]>

     Hi!
     I'm using geometric morphometry for analyzing orchid seeds, and
since I
     am quite new at this (and at statistics two) I have a few
questions. I
     want to perform a CVA and a MANOVA with my morphometric
results, and I
     want to know if I can use the relative warps scores for doing
this, or
     it can only be done with the partial warps. What if I don´t
fulfill the
     number of samples (4 times the number of variables) needed, may
I use
     the relative warps in this case?

     Besides, is there any way to obtain the deformation grids for
the CVA
     using any of the the tps software?

     Thanks a lot!

     Amelia

     --
     Lic. Amelia Chemisquy
     Instituto de Botánica Darwinion
     Casilla de Correo 22
     B1642HYD, San Isidro
     Argentina
     Tel. (54 11) 4743 4800/4742 8534
     [EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>
     www.darwin.edu.ar <http://www.darwin.edu.ar>






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