[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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