[R] AIC and anova, lme
Patrick Giraudoux
patrick.giraudoux at univ-fcomte.fr
Tue Feb 26 14:59:12 CET 2008
ian white a écrit :
> Patrick,
>
> The likelihoods of two models fitted using REML cannot be compared
> unless the fixed effects are the same in the two models.
>
Many thanks for this reminder. Shame on me: it recalls me that this
subject may have been already largely discussed on this list. Now, I can
search the archives specifically with the REML issue...
All the best,
Patrick
>
> On Tue, 2008-02-26 at 14:38 +0100, Patrick Giraudoux wrote:
>
>> Dear listers,
>>
>> Here we have a strange result we can hardly cope with. We want to
>> compare a null mixed model with a mixed model with one independent
>> variable.
>>
>> > lmmedt1<-lme(mediane~1, random=~1|site, na.action=na.omit, data=bdd2)
>> > lmmedt9<-lme(mediane~log(0.0001+transat), random=~1|site,
>> na.action=na.omit, data=bdd2)
>>
>> Using the Akaike Criterion and selMod of the package pgirmess gives the
>> following output:
>>
>> > selMod(list(lmmedt1,lmmedt9))
>> model LL K N2K AIC deltAIC w_i AICc
>> deltAICc w_ic
>> 2 log(1e-04 + transat) 44.63758 4 7.5 -81.27516 0.000000 0.65 -79.67516
>> 0.000000 0.57
>> 1 1 43.02205 3 10.0 -80.04410 1.231069 0.35 -79.12102
>> 0.554146 0.43
>>
>> The usual conclusion would be that the two models are equivalent and to
>> keep the null model for parsimony (!).
>>
>> However, an anova shows that the variable 'log(1e-04 + transat)' is
>> significantly different from 0 in model 2 (lmmedt9)
>>
>> > anova(lmmedt9)
>> numDF denDF F-value p-value
>> (Intercept) 1 20 289.43109 <.0001
>> log(1e-04 + transat) 1 20 31.18446 <.0001
>>
>> Has anyone an opinion about what looks like a paradox here ?
>>
>> Patrick
>>
>>
>>
>> ______________________________________________
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
>
>
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