In multi-level models DIC can be 'focused' at different levels. In
MCMCglmm, DIC is focussed at the highest possible level because this is
the only level at which it can be analytically computed for non-Gaussian
models. The highest level is not the level at which most scientists want
their information criteria focussed, and so I would not recommend it. In
fact I have wondered about removing it completely from MCMCglmm.
Cross-validation is a much better approach, and in some ways is what
information criteria aspire to. But its more computationally demanding
On 21/06/2018 14:24, jonnations wrote:
I don't have the exact answer you are looking for, but I would highly
recommend the brms package in R. It is incredibly flexible and has
excellent diagnostic tools like LOO and WAIC that are easy to use and
interpret for model selection. I think it would work well for the models
you presented. There is an easy to follow tutorial on phylogenetic mixed
Also there is another list serve called "r-sig-mixed-models" that you might
be interested in. It's not "phylo" focused, but these sorts of questions
come up on there all the time.
ps- my first time responding to the list, sorry for any format errors
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