[R] lmer, p-values and all that

Nicole Ford nicole.ford at me.com
Thu Mar 28 03:16:23 CET 2013


i meant to add, i am not sure if an "example" lmer model woulf be helpful, since i can't see the OP.


On Mar 27, 2013, at 10:13 PM, Nicole Ford wrote:

> i literally just ran one.
> 
> when i ran one of mine and the did summary(mod) i get the following:
> 
>> mod <- lmer(dem ~ xbar + cpi + (1 | country), data=wvsAB)
>> summary(mod)
> Linear mixed model fit by REML 
> Formula: dem ~ xbar + cpi + (1 | country) 
>   Data: wvsAB 
>   AIC   BIC logLik deviance REMLdev
> 34383 34418 -17187    34355   34373
> Random effects:
> Groups   Name        Variance Std.Dev.
> 
> with a bunch more stuff below.
> 
> 
> On Mar 27, 2013, at 10:00 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 ...)
>> 
>>> 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
>> 
>> ______________________________________________
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>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
> 
> 
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> 
> ______________________________________________
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