[R-sig-ME] anova (lm, lmer ) question

[Farrar, David]

If I understood, the following should have worked?

> m.ML <- lmer(
+ log10(TWA) ~ ns(Wind.Speed,3) + isLamar + isLime1p + isLime5p  + log10(TWAuw)
+ + (1|BiosolidSource) + (1|sample) + (1|sample.trial),
+ REML=F,
+ data=da.regr
+ )
> m.lm <- lm(
+ log10(TWA) ~ ns(Wind.Speed,3) + isLamar + isLime1p + isLime5p + log10(TWAuw),
+ data=da.regr
+ )
> anova(m.ML, m.lm)
Error in UseMethod("isREML") : 
  no applicable method for 'isREML' applied to an object of class "lm"



-----Original Message-----
From: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf Of Ben Pelzer
Sent: Saturday, October 04, 2014 10:13 AM
To: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] anova (lm, lmer ) question

Dear romunov, Ben and Ken,

Thanks for your replies. From these I conclude that:
- for linear (lmer vs. lm) models there's no problem in using the deviance difference
- for generalized  linear models (glmer vs. glm) it's ok to use the deviance difference as long as nAGQ=1.
Would you agree with me? Best regards,

Ben.

On 4-10-2014 2:48, Ben Bolker wrote:
> Thanks for checking.  The comparison with Stata isn't necessarily 
> relevant though -- or question is whether `lm` and `lmer` (or `glm` 
> and `glmer`) include/exclude the same additive constants, so that 
> their log-likelihoods are directly comparable.
>
> On Fri, Oct 3, 2014 at 8:38 PM, Ken Beath <ken.beath at mq.edu.au> wrote:
>
>> nAGQ=1 and greater than 1 give different results, and the nAGQ=1 
>> matches fairly closely the log likelihood from Stata for 3 quadrature 
>> points, so presumably is correct. Stata's Laplace didn't converge with my data.
>>
>>
>> Ken
>>
>>
>>
>> On 4 October 2014 09:06, Ben Bolker <bbolker at gmail.com> wrote:
>>
>>> romunov <romunov at ...> writes:
>>>
>>>> FWIW, this is from the glmm faq site <http://glmm.wikidot.com/faq>.
>>>>
>>>> How can I test whether a random effect is significant?
>>>>
>>>    ...
>>>
>>>>     - *do not* compare lmer models with the corresponding lm fits, or
>>>>     glmer/glm; the log-likelihoods are not commensurate (i.e., they
>>> include
>>>>     different additive terms)
>>>    For what it's worth, I believe this is out of date, _except_ for 
>>> glmer fits with nAGQ>1.  It should be possible to implement
>>> anova(<merMod>,<lm>/<glm>) -- it's only a nuisance (sadly, if we 
>>> were still using S4 classes at this level it would be easier ...)
>>>
>>>    Ben Bolker
>>>
>>> _______________________________________________
>>> R-sig-mixed-models at r-project.org mailing list 
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>>
>>
>>
>> --
>>
>> *Ken Beath*
>> Lecturer
>> Statistics Department
>> MACQUARIE UNIVERSITY NSW 2109, Australia
>>
>> Phone: +61 (0)2 9850 8516
>>
>> Building E4A, room 526
>> http://stat.mq.edu.au/our_staff/staff_-_alphabetical/staff/beath,_ken
>> /
>>
>> CRICOS Provider No 00002J
>> This message is intended for the addressee named and 
>> m...{{dropped:11}}
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