Hi,
You might try looking at:
A general and simple method for obtaining R2 from generalized linear
mixed-effects models by Nakagawa Schielzeth.
They detail some of the issues with comparing null versus full models,
and it is a well presented paper.
I can't remember whether they deal
Hi Gustaf,
In the model with just species the residual variation is measurement
error/plasticity error, but could also include deviations from the
assumed BM process. If you add species.ide that term captures
deviations from the assumed BM process.
Va/(Va+Ve) is the proportion of
Jarrod,
Thanks for your input. Dropping species.ide result in a model that is
estimated without any problems.
prior = list(R = list(V = 1, nu = 0), G = list(G1 = list(V = 1, nu = 1,
alpha.mu = 0, alpha.V = 1000)))
m1.mcmc - MCMCglmm(y ~ habitat, random =~ species,
data =
