[R] lmer, p-values and all that

[David Winsemius]

On Mar 27, 2013, at 7:00 PM, Ben Bolker wrote:

> Michael Grant <michael.grant <at> colorado.edu> writes:
> 
>> 
>> 
>> Dear Help:
> 
>> I am trying to follow Professor Bates' recommendation, quoted by
>> Professor Crawley in The R Book, p629, to determine whether I should
>> model data using the 'plain old' lm function or the mixed model
>> function lmer by using the syntax anova(lmModel,lmerModel).
>> Apparently I've not understood the recommendation or the proper
>> likelihood ratio test in question (or both) for I get this error
>> message: Error: $ operator not defined for this S4 class.
> 
>  I don't have the R Book handy (some more context would be extremely
> useful!  I would think it would count as "fair use" to quote the
> passage you're referring to ...)

This is the quoted Rhelp entry:

http://tolstoy.newcastle.edu.au/R/help/05/01/10006.html

(I'm unable to determine whether it applies to the question at hand.)

> 
>> Would someone be kind enough to point out my blunder?
> 
>  You should probably repost this to the r-sig-mixed-models at r-project.org
> mailing list.
> 
>  My short answer would be: (1) I don't think you can actually
> use anova() to compare likelihoods between lm() and lme()/lmer()
> fits in the way that you want: *maybe* for lme() [don't recall],
> but almost certainly not for lmer().  See http://glmm.wikidot.com/faq
> for methods for testing significance/inclusion of random factors
> (short answer: you should *generally* try to make the decision
> whether to include random factors or not on _a priori_ grounds,
> not on the basis of statistical tests ...)
> 
>  Ben Bolker
> 

-- 
David Winsemius
Alameda, CA, USA