[R] Why does dredge() rank models differently for lmer() and MCMCglmm()?

Corina itsme at CorinaLogan.com
Tue Jul 21 11:20:03 CEST 2015


Hi Ben,
Thank you so much for your helpful advice! I changed the lmer model to REML=FALSE and the best-fitting model in dredge is MUCH more similar to what I found with MCMCglmm.

My best,
Corina

-- 
Dr. Corina Logan 
Leverhulme Early Career Research Fellow 
Department of Zoology
University of Cambridge
itsme at CorinaLogan.com 
www.CorinaLogan.com


On Jul 18, 2015, at 18:06, bbolker [via R] <ml-node+s789695n4710029h10 at n4.nabble.com> wrote:

Corina <itsme <at> CorinaLogan.com> writes: 

> 
> Hello, 
> I am running my full model (fm) through lmer() and MCMCglmm() using the 
> default settings: 
> 
> model.lmer <- lmer(fm) 
> model.MCMCglmm <- MCMCglmm(fm) 
> 

  [snip] 

> However, when I run the models through dredge(): 
> 
> dredge(model.lmer) 
> dredge(model.MCMCglmm) 
  
> It ranks the models very differently for lmer() and MCMCglmm() in 
> the model selection tables, even though I used the default settings 
> for dredge() as well (ranked by AICc). I would assume the difference 
> is because lmer() uses REML and MCMCglmm() uses Bayes Rule, however 
> if this is the case then why weren’t the summary outputs different 
> as well? 
  
  [snip] 

   This question *might* be better on [hidden email] <x-msg://2/user/SendEmail.jtp?type=node&node=4710029&i=0> ... 
You shouldn't be comparing models with fixed effects that are fitted 
with REML -- try  refitting with REML=FALSE.  The model comparison 
functions in the lme4 package (e.g. anova()) try to stop you from 
making this mistake, but I'm not sure the MuMIn::dredge does. 

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