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

[Alex Fine]

Hi Sverre,

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
>>
>>
>>     
>
>