[R-sig-ME] Likelihood ratios

[Ben Bolker]

  Yes, or

exp(logLik(fit2,REML=FALSE)-logLik(fit1,REML=FALSE))


   What is a "complexity-corrected" likelihood ratio?
   I'm very nervous about mixing in the AIC penalty terms with the rest
of the likelihood ratio -- and, as I think has been pointed out, you
have to be careful to set REML=FALSE ...

fengsj at mail.utexas.edu wrote:
> Is there someting similar for glmer models?
> Thanks!
> 
> 
> Quoting Mike Lawrence <Mike.Lawrence at dal.ca>:
> 
>> After posting this, I thought to contact Pete Dixon himself and indeed
>> it seems he already coded the functions to obtain a likelihood ratio
>> comparing two lmer models:
>>
>> AIC_lmer = function(x){
>> 	require(lme4)
>> 	print(formula(attr(x,"call")))
>> 	summary(x)@AICtab
>> }
>>
>> LR_lmer = function(m0,m1){
>> 	exp((AIC_lmer(m0)[[1]]-AIC_lmer(m1)[[1]])/2)
>> }
>>
>> #example usage:
>> LR_lmer( my_fit1 , my_fit2 )
>>
>>
>>
>> On Tue, Jun 1, 2010 at 1:50 PM, Mike Lawrence <Mike.Lawrence at dal.ca> wrote:
>>> oops, I guess that should be:
>>>
>>> LR = exp( anova( fit1 , fit2 )$Chisq[2] / -2 )
>>>
>>>
>>> On Tue, Jun 1, 2010 at 1:28 PM, Mike Lawrence <Mike.Lawrence at dal.ca> wrote:
>>>> Hi folks,
>>>>
>>>> I have 2 lmer fits, one (fit1) nested in the other (fit2), and I'd
>>>> like to compute the likelihood ratio comparing the models so I can say
>>>> something like "there is X times more evidence for fit1 than for fit2"
>>>> (as in Glover & Dixon, 2004, www.ncbi.nlm.nih.gov/pubmed/15732688).
>>>>
>>>> I know I can use anova(fit1,fit2) to obtain a null-hypothesis
>>>> significance test of the fits, and I suspect the output also contains
>>>> the information I need to make my evidentiary statement, but I'm not
>>>> confident of what I'm doing here. Is it correct that the reported
>>>> value of chi-square from anova() is simply the D of the likelihood
>>>> ratio test (http://en.wikipedia.org/wiki/Likelihood_ratio_test)? If
>>>> so, does it sound right that I can simply derive the
>>>> complexity-corrected likelihood ratio as:
>>>>
>>>> LR = exp( -2 * anova( fit1 , fit2 )$Chisq[2] )
>>>>
>>>> ?
>>>>
>>>>
>>>> Mike
>>>>
>>>> --
>>>> Mike Lawrence
>>>> Graduate Student
>>>> Department of Psychology
>>>> Dalhousie University
>>>>
>>>> Looking to arrange a meeting? Check my public calendar:
>>>> http://tr.im/mikes_public_calendar
>>>>
>>>> ~ Certainty is folly... I think. ~
>>>>
>>>
>>>
>>> --
>>> Mike Lawrence
>>> Graduate Student
>>> Department of Psychology
>>> Dalhousie University
>>>
>>> Looking to arrange a meeting? Check my public calendar:
>>> http://tr.im/mikes_public_calendar
>>>
>>> ~ Certainty is folly... I think. ~
>>>
>>
>>
>> --
>> Mike Lawrence
>> Graduate Student
>> Department of Psychology
>> Dalhousie University
>>
>> Looking to arrange a meeting? Check my public calendar:
>> http://tr.im/mikes_public_calendar
>>
>> ~ Certainty is folly... I think. ~
>>
>> _______________________________________________
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>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
> 
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-- 
Ben Bolker
Associate professor, Biology Dep't, Univ. of Florida
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