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 second model has the structure: log(Weight) ~ log(Trait)+ Biogeography + 
(1|Species/Animal), pedigree = phylogeny, i.e. variance between species is 
constrained by the branch lengths between the species.

The aim of running these two models is compare which is more predictive and to 
increase usability: Including family is user-friendly (and easy for the end 
user, especially if they’re not a taxonomist) whereas the phylogenetic model is 
more attractive theoretically however from a predictive sense requires your 
species of interest to be contained within the phylogeny used to fit the model,

Therefore, my question is how best can I compare these two models in model 
selection? Can I compare them directly by their DIC weighting if the only 
difference is the phylogenetic random term? Or is there be a better way to 
compare them? So far, we are also comparing their performance based off k-fold 
cross validation and RMSE but in the ‘age of AIC’, DIC appears a good place to 
start for model selection.

Any advice would be much appreciated.

Best,
Liam


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