[R-sig-ME] Partialing out the effect of a covariable in a Poisson GLMM

[v_coudrain at voila.fr]

Thank you for this information. 
Best,
Valérie


> Message du 21/01/13 à 15h22
> De : "Ben Bolker" 
> A : v_coudrain at voila.fr
> Copie à : r-sig-mixed-models at r-project.org
> Objet : Re: Partialing out the effect of a covariable in a Poisson GLMM
> 
> On 13-01-21 02:51 AM, v_coudrain at voila.fr wrote:
> > Ben Bolker writes: 
> > 
> >> Don't know exactly what you want to do, but presumably fitting
> >> a "null model" with the covariate and then building more complex models
> >> on top of this -- adding the other covariates -- and doing sequential testing
> >> (anova(full_model,model_with_only_first_covariate)). The linear models
> >> idea of partialing out one variable and running a model on the residuals
> >> doesn't work as well, unfortunately.
> > 
> > Oh yes, thank you I can do it this way. Sould I turn REML to FALSE for model comparison? 
> > Best,
> > Valérie
> 
> REML is *ignored* when running glmer() [or lmer() with a 'family'
> argument]; as discussed at http://glmm.wikidot.com/faq , REML is
> somewhat poorly defined for GLMMs. (The development version of lme4 at
> least warns that the REML argument is ignored; the CRAN version just
> silently ignores it.)
> 
> Ben Bolker
> 
> 
> 

___________________________________________________________
Envie de changer de frigo ou de gazinière ? Les soldes électroménager sont sur Voila.fr http://shopping.voila.fr/vitrine/electromenager