Patrick Giraudoux <patrick.giraudoux <at> univ-fcomte.fr> writes:
> > 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) ... > 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 > Ask the author of pgirmess to add some checks for the model as anova and stepAIC do: Dieter ----- library(MASS) library(nlme) fm1 <- lme(distance ~ age, data = Orthodont) fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) >>In anova.lme(fm1, fm2) : << Fitted objects with different fixed effects. REML comparisons are not<< meaningful. stepAIC(fm2) >>Error in extractAIC.lme(fit, scale, k = k, ...) : >> AIC undefined for REML fit ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
