-------- Original Message -------- Subject: Re: multiple comparisons test for Procrustes ANOVA Date: Fri, 12 Sep 2008 01:59:12 -0700 (PDT) From: Chris Klingenberg <[EMAIL PROTECTED]> Reply-To: [EMAIL PROTECTED] Organization: University of Manchester To: [email protected] References: <[EMAIL PROTECTED]> Dear Shane The simplest way to do the comparison of the amounts of FA in different groups, to my knowledge, is to use an analogue to Levene's test, which has been recommended for univariate distance data in traditional FA analyses (e.g. Palmer, A. R., and C. Strobeck. 2003. Fluctuating asymmetry analyses revisited. Pp. 279–319 in M. Polak, ed. Developmental instability: causes and consequences. Oxford University Press, New York.) For geometric morphometrics, Leandro Monteiro and I have suggested such a method. For each individual, you compute a scalar measure of asymmetry (corrected for directional asymmetry), which you can then compare with a t-test or univariate ANOVA according to your experimental design. As measures of asymmetry, there are two choices: Procrustes distance and a measure based on Mahalanobis distance. These are measures of absolute shape differences and shape differences relative to the variation in the total sample, respectively. In practice, both distances tend to give similar results (in my experience -- but this presumably depends on study organisms and experimental settings). More detail is provided in the following paper: Klingenberg, C. P., and L. R. Monteiro. 2005. Distances and directions in multidimensional shape spaces: implications for morphometric applications. Systematic Biology 54:678–688. http://www.flywings.org.uk/PDF%20files/SystBiol2005.pdf This method is implemented in MorphoJ. If you run a Procrustes ANOVA, an output dataset will be generated, which contains the two measures of asymmetry for every individual in your sample. You can export these values to a text file (File > Export dataset) and use a univariate ANOVA to test for differences among groups, according to the design of your study. For details: http://www.flywings.org.uk/MorphoJ_guide/frameset.htm?variation/procANOVA.htm A fairly large-scale application of this approach was used in a study that related the amouts of variation and FA in size and shape across 115 groups of flies with distinct genotypes: Breuker, C. J., J. S. Patterson, and C. P. Klingenberg. 2006. A single basis for developmental buffering of Drosophila wing shape. PLoS ONE 1(1): e7. http://www.flywings.org.uk/PDF%20files/PLoSONE2006.pdf I hope this helps. Best wishes, Chris morphmet wrote:
-------- Original Message -------- Subject: multiple comparisons test for Procrustes ANOVA Date: Wed, 10 Sep 2008 06:38:07 -0700 (PDT) From: Shane Welch <[EMAIL PROTECTED]> To: [email protected] Hello everyone, I'm new to geometric morphometric analysis but I have a good understanding of univariate statistics. I've been recruited by my lab to perform a quick analysis for wing landmark data. The objective is to compare fluctuating asymmetry (FA) among different treatment groups. We have 8 landmarks per wing (right vs. left), landmarks were recorded by the same person 3 times, there are approximate 100 replicates per treatment, and 4 treatment groups. I preformed a *Procrustes fit* and a Procrustes ANOVA. The main effect of treatment was significant, but here I get lost, I would like to know how to perform the equivalent of post-hoc multiple comparisons test to determine which treatments exhibited greater FA. My understanding of multivariate statistics is limited, so if the answer is in that direction, please go slow. Any help is great. Thanks Shane
-- *************************************************************** Christian Peter Klingenberg Faculty of Life Sciences The University of Manchester Michael Smith Building Oxford Road Manchester M13 9PT United Kingdom Telephone: +44 161 275 3899 Fax: +44 161 275 5082 E-mail: [EMAIL PROTECTED] Web: http://www.flywings.org.uk *************************************************************** -- Replies will be sent to the list. For more information visit http://www.morphometrics.org
