Christy, I would strongly advocate using visualizations of group means for describing shape differences among groups as compared to CVA.
A Procrustes MANOVA provides the statistical inferences related to any differences that might be present among groups, and the corresponding thin-plate spline deformations of the overall mean to the group means provides the shape deformations describing how groups may differ from that mean. Visualizing multiple group means simultaneously in a figure, as is commonly done in many morphometric studies, facilitates a visual language to describe how they differ from the consensus, and thus how they differ from one another. In geomorph, advanced.procD.lm provides the appropriate LS means for groups from any linear model (manova, factorial manova, mancova, etc.). Shape differences of these relative to the overall consensus shape as found using ‘mshape’ can then be generated using plotRefToTarget. Hope this helps. Dean Dr. Dean C. Adams Professor Department of Ecology, Evolution, and Organismal Biology Department of Statistics Iowa State University www.public.iastate.edu/~dcadams/<http://www.public.iastate.edu/~dcadams/> phone: 515-294-3834 From: Christy Hipsley [mailto:chips...@museum.vic.gov.au] Sent: Monday, November 28, 2016 5:04 PM To: MORPHMET <morphmet@morphometrics.org> Subject: [MORPHMET] the problem with CVA... or is it? Dear Morphmet-ers, I'm seeking advice on methods for visualizing shape features that distinguish multiple groups using GM. I know CVA has fallen out of favor for a number of reasons discussed here - e.g., more variables than groups, nonisotropic variation: Mitteroecker, P., and Bookstein, F. 2011. Linear discrimination, ordination, and the visualization of selection gradients in modern morphometrics. Evol. Biol. 38:100–114. Klingenberg, C. P., and Monteiro, L. R. 2005. Distances and directions in multidimensional shape spaces: Implications for morphometric applications. Syst. Biol. 54:678–688. Although given these limitations, is it really expected to give completely false results regarding the visualization of shape changes? In my study sytem, I show that ecological groups have statistically different cranial shapes, using both Procrustes ANOVA and PGLS. Now I simply want to visualize what the main features are that distinguish them, preferably using warps or wireframes, so that those changes must be directly relateable to the original landmark coordinates. I did that using individual specimens instead of species means, so I have 161 individuals vs 144 variables (48 landmarks*3D). I also did a between-group PCA on the species means which shows the same pattern, so is it technically "wrong" to show both? Thanks for any feedback on this issue, and I would appreciate to hear any alternative methods that people might use. I use MorphoJ and Geomorph for analyses. Best, Christy -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org --- You received this message because you are subscribed to the Google Groups "MORPHMET" group. To unsubscribe from this group and stop receiving emails from it, send an email to morphmet+unsubscr...@morphometrics.org<mailto:morphmet+unsubscr...@morphometrics.org>. -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org --- You received this message because you are subscribed to the Google Groups "MORPHMET" group. To unsubscribe from this group and stop receiving emails from it, send an email to morphmet+unsubscr...@morphometrics.org.