I have two suggestions. First, if one were to take the fluctuating shape component for each individual, as found in the output of bilat.symmetry, one could then perform an anova using procD.lm to compare this among groups. That asks whether one group displays a greater degree of FA than another group.
Second, one could also perform a disparity analysis on the fluctuating shape component to determine whether there is greater variation in FA in one group relative to another.
I suspect that the second of these may be more informative. The anova-type analysis is a test of mean location, which makes a bit less sense using FA data, because one may not expect that the fluctuating shape components are all distinct from the grand mean in a particular direction in shape space (they are fluctuating after all). But it still may occur.
The second approach makes considerably more sense and tests whether levels of variation in FA differ among groups. This is far more intuitive, say if one is comparing FA variation in pristine vs. contaminated sites.
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/
phone: 515-294-3834
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