-------- Original Message -------- Subject: Re: common allometric components and residual shape components Date: Thu, 8 Mar 2012 11:41:55 -0500 From: ejsch...@ucalgary.ca To: morphmet@morphometrics.org Thanks for that, I will try that out in R to see how they compare. It's becoming clearer. I've noticed in more traditional morphometric studies (linear distance based), similar approaches have been used, or what I interpret to be similar, in that axes of size-related variation are plotted against size-independent variation, but the terminology applied to the types of axes is different. eric -------- Original Message -------- Subject: Re: common allometric components and residual shape components Date: Thu, 8 Mar 2012 11:12:06 -0500 From: Dean Adams <dcad...@iastate.edu> To: morphmet@morphometrics.org Eric, Actually, if your specimens comprise only a single group, the CAC of Mitteroecker et al. (2004) and the regression score (S) from Drake and Klingenberg (2008) will be identical. The reason is that both are based on size-regressions of mean-centered shape variables, which for 1 group are obtained from the same mean (i.e. the 'global' mean and group mean are the same in this case). You can confirm this quite simply in R by obtaining both the CAC and the S values for the same data and correlating/plotting them. Of course, for multiple groups the CAC and S will be different, as CAC is found from group-mean-centered data. This is something that should have been made explicit in the previous literature, but was not pointed out (or perhaps not appreciated). Dean -- Dr. Dean C. Adams Associate Professor Department of Ecology, Evolution, and Organismal Biology Department of Statistics Iowa State University Ames, Iowa 50011 www.public.iastate.edu/~dcadams/ phone: 515-294-3834 On 3/8/2012 9:56 AM, morphmet wrote:
-------- Original Message -------- Subject: Re: common allometric components and residual shape components Date: Wed, 7 Mar 2012 17:44:06 -0500 From: ejsch...@ucalgary.ca To: morphmet@morphometrics.org thanks, and i've got my figures now. I'm also comparing appending the coordinate data with centroid size and running the prcomp() in R to the output from MorphoJ, in which I regressed PC1 (from residual data) against the regression scores of shape coordinates vs centroid size. If they are the same or similar, then the regression scores are the same or similar to the so called CAC, and PC1 of size corrected data is equivalent to the so called RSC1. eric -------- Original Message -------- Subject: Re: common allometric components and residual shape components Date: Wed, 7 Mar 2012 11:29:04 -0500 From: Aki Watanabe <awatan...@bio.fsu.edu> To: morphmet@morphometrics.org Hi Eric, For R, you can use prcomp(), instead of princomp(). The former uses spectral decomposition, so it doesn't give you an error when you have more variables than specimens. Cheers, Aki On Wed, Mar 7, 2012 at 10:54 AM, morphmet <morphmet_modera...@morphometrics.org <mailto:morphmet_modera...@morphometrics.org>> wrote: -------- Original Message -------- Subject: common allometric components and residual shape components Date: Wed, 7 Mar 2012 07:27:41 -0500 From: ejsch...@ucalgary.ca <mailto:ejsch...@ucalgary.ca> To: morphmet@morphometrics.org <mailto:morphmet@morphometrics.org> Hi, I have a question about common allometric components and residual shape components, or CAC and RSC, and how RSCs relate to PCs generated from size-corrected data. So, the CAC is a regression line, calculated using a pooled within group regression of coordinate data on size. And if so, is this line also referred to as a pooled allometric vector? And will MorphoJ allow one to use this vector in a regression with another variable, such as the RSC? Or is it a better bet to obtain the allometric vector in another program, such as R. Using the residuals from that regression and doing a PCA, the PC1 is the same as the RSC? Is this correct? If so, MorphoJ will certainly do this. One more issue: doing PCA using R...I have problems with an error about having too many variables (relative to the number or rows, I suppose). How do I work around this in R? Eric U of Calgary -- Aki Watanabe Department of Biological Science Florida State University King Life Science Building 319 Stadium Drive Tallahassee, FL 32306-4295 University of Chicago - AB '09 Biological Sciences and Geophysical Sciences Website: http://sites.google.com/site/akinopteryx/home Weblog: http://akiopteryx.blogspot.com/
