[R] testing fixed effects in lmer

[Ben Bolker]

Achaz von Hardenberg <fauna <at> pngp.it> writes:

> 
> Dear all,
> I am performing a binomial glmm analysis using the lmer function in  
> the lme4 package (last release, just downloaded). I am using the  
> "Laplace method".
> 
> However, I am not sure about what I should do to test for the  
> significance of fixed effects in the binomial case: Is it correct to  
> test a full model against a model from which I remove the fixed  
> effect I want to test using the anova(mod1.lmer, mod2.lmer) method  
> and then relying on the model with the lower AIC (or on the Log- 
> likelihood test?)?

  The short answer is that testing fixed effects in GLMMs
is difficult and dangerous.  Likelihood ratio tests on fixed
effect differences [which is generally what anova() does]
in a random-effects model are unreliable
(see Pinheiro and Bates 2000).  Most of the world does
F tests with various corrections on the denominator
degrees of freedom, but this is contentious (in particular,
Doug Bates, the author of lme4, disagrees).  lme4 will
eventually let you use an MCMC sampling method to test
fixed effects but that may or may not be working
in the current version.

  I would try this question again on the r-sig-mixed
mailing list.

  good luck,
   Ben Bolker