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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