[R-lang] Re: p-values for mixed effects models with random slopes

[Steven Piantadosi]

Hi All,

Unless I'm out of date, p values are broken on glmer too? I wonder if an
easy solution to these two problems might be to implement a
bootstrapping/resampling algorithm on mixed effect regressions. Does
anyone know about this--would it be conservative or anticonservative or
a problem on data sets of typical size in psycholinguistics? 

If this is actually a good idea, and someone could point me to a
reference on how bootstrapping would work on such models (I know
references for simple non-mixed effect regressions, but not how
bootstrapping interfaces with repeated subject/item measurements and
random effects), I'd be happy to try to put some friendly code
together. 

++Steve






> 
> pvals.fnc works for models that have random intercepts, but not for 
> models with random slopes.  My question is whether anyone has 
> implemented something analogous to pvals.fnc for models with random 
> slopes. 
> 
> Your point about likelihood ratio tests is well-taken though, and these 
> can be performed regardless of the random effects structure.
> 
> Alex
> 
> Sverre Stausland wrote:
> > Hi Alex,
> >
> > pvals.fnc in languageR just uses the mcmcsamp function in lme4. I've
> > also experienced pvals.fnc failing, but as far as I know, that's
> > because Doug Bates chose to not let mcmcsamp work, because he didn't
> > trust its results.
> >
> > That said, pvals.fnc worked just fine when I used it about a week ago.
> > I assume this means mcmcsamp has been implemented in the newest
> > version of lme4. Try using the latest version of lme4.
> >
> > If that doesn't work, the standard approach to get p-values from
> > linear mixed models is to do likelihood ratio tests. If you test fixed
> > effects, though, remember to fit the models with maximum likelihood
> > fitting, and _not_ with restricted maximum likelihood (i.e. include
> > REML=FALSE in the call). (There's an explanation for why in Pinheiro &
> > Bates' 2000 book).
> >
> > -Sverre
> >
> > On Mon, Jan 17, 2011 at 9:53 PM, Alex Fine <afine@bcs.rochester.edu> wrote:
> >   
> >> Hi,
> >>
> >> I would imagine many or most of you are aware of the fact that the pvals.fnc
> >> function in the languageR package cannot currently estimate p-values for
> >> models that include random slopes.  Because we all need p-values, I'm
> >> guessing someone out there has developed a way of getting them from such
> >> models.  Has anyone implemented something that does this, or have any
> >> thoughts on this issue?
> >>
> >> Thanks!
> >> Alex
> >>
> >>
> >>     
> >
> >