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 model selection is followed by k-fold cross validation so I would very much be curious about your thoughts on that type of cross-validation on a phylogenetic glmm Thanks again and all the best Liam > On 22 Jun 2018, at 1:34 am, Jarrod Hadfield <j.hadfi...@ed.ac.uk> wrote: > > 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 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 of course. > > Cheers, > > Jarrod > > > > > > On 21/06/2018 14:24, jonnations wrote: >> 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 presented. There is an easy to follow tutorial on phylogenetic mixed >> models too. >> >> 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. >> >> Good luck! >> Jon >> >> >> ps- my first time responding to the list, sorry for any format errors >> > > > -- > The University of Edinburgh is a charitable body, registered in > Scotland, with registration number SC005336. > _______________________________________________ R-sig-phylo mailing list - Remail@example.com https://stat.ethz.ch/mailman/listinfo/r-sig-phylo Searchable archive at http://firstname.lastname@example.org/