Dear MCMCglmm users,
I am running a simple model corrrecting for phylogenetic relationships using MCMCglmm. Now I am interested in the phylogenetic signal, the analogue to Pagels lambda.
Now I have two questions:
1.) According to Hadfield and Nakagawa (2010) the analogue to lambda (Pagel) in the mixed model approach is var(phylo)/var(phylo)+var(residuals), however, in another conversation about pyhlogenetic signal in MCMCglmm I found that actually var(phylo)/var(phylo)+var(residuals)+var(random effects) is the right measurement for the phylogenetic signal. But isnt the var(phylo) and var(random effects) basically the same, cos actually the pyhlogeny is the random effect in such a model? so for me rather var(phylo)/var(phylo) + var(residuals) makes more sense.
My model:
MCMCglmm(Y ~ X random=~animal, data="" pedigree=phylotree, pr=F, saveX=F, pl=T), X and Y are two continuous variables.
2.) Comparing to the PGLS function in caper, there the variance-covariance matrix is adjusted for the strength of the phylogenetic signal (estimated lambda scales the off-diagonals of the phylogenetic vcv matrix). Is that somehow done in the MCMCglmm approach? if yes, how?
For any help I am very grateful.
Cheers,
Sereina
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