-------- Original Message -------- Subject: Re: Relationships between shape variables Date: Wed, 3 Dec 2008 05:01:23 -0800 (PST) From: Chris Klingenberg <[EMAIL PROTECTED]> Reply-To: [EMAIL PROTECTED] Organization: University of Manchester To: [email protected] References: <[EMAIL PROTECTED]> Hi Brendan Probably the most widespread technique for this is PLS. A good review of the technique is the following paper: Rohlf, F. J., and M. Corti. 2000. The use of two-block partial least-squares to study covariation in shape. Systematic Biology 49:740–753. PLS has been used for landmarks in separate configurations, for which separate Procrustes fits are used. A couple of examples of this: Tabachnick, R. E., and F. L. Bookstein. 1990. The structure of individual variation in Miocene Globorotalia. Evolution 44:416–434. Bastir, M., and A. Rosas. 2005. Hierarchical nature of morphological integration and modularity in the human posterior face. American Journal of Physical Anthropology 128:26–34. A different option is the approach of using a single Procrustes fit for all landmarks, and then a PLS analysis among sets of landmarks within the configuration. Examples include: Klingenberg, C. P., and S. D. Zaklan. 2000. Morphological integration between developmental compartments in the Drosophila wing. Evolution 54:1273–1285. Bookstein, F. L., P. Gunz, P. Mitteroecker, H. Prossinger, K. Schaefer, and H. Seidler. 2003. Cranial integration in Homo: singular warps analysis of the midsagittal plane in ontogeny and evolution. Journal of Human Evolution 44:167–187. Statistical testing is usually done via permutation methods. I hope this is useful. Best wishes, Chris morphmet wrote:
-------- Original Message -------- Subject: Relationships between shape variables Date: Tue, 2 Dec 2008 16:59:21 -0800 (PST) From: Brendan McCane <[EMAIL PROTECTED]> To: [email protected] G'day, I have a rather technical question (i.e. I'm interested in the underlying technique rather than software that can do it). Here is the problem: Given a sample of images (say lateral images of the human facial skeleton), we locate quite a number of landmarks (actually semi-landmarks or slid-landmarks) with landmarks coming from many different structures. I'd like to test for relationships between the structures - i.e. do changes in this structure (e.g mandible) , produce corresponding changes in that structure (e.g. upper dentition). Of course I can do a Procrustes analysis, followed by a PCA and visually see how the structures co-vary along the principal axes, but I am interested in something a little less qualitative, perhaps more along the lines of a hypothesis test. I was thinking perhaps of canonical correlation analysis between different sets of structures, but I haven't seen much work using this technique in shape analysis. Does anyone have any advice or pointers to other work?
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