Thank you all for your very informative responses.
I will try the brms package as Jon suggested - I have read a bit about WAIC
being more appropriate or favourable than the DIC but I was (until now)
unfamiliar with the brms package.
We are very much working within a predictive framework where
Hi Liam,
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
Hi Liam,
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
Dear all,
I am conducting an analysis predicting insect body sizes using a co-varying
trait and their biogeographic region within two model formulations using
MCMCglmm.
The first model has the structure: log(Weight) ~ log(Trait)+ Biogeography +
Family (i.e. Taxonomic family of species)
The
