Wrong degrees of freedom in nested model, what goes wrong here?
Marvelde, Luc te <L.teMarvelde at ...> writes:
so, a first simple model i think i have to run (but please say so if you
disagree), is this:
model1<-lme(TFoodhrC ~ age + age2 + STATUS ,random=~1|nest/birdid/age,
method="ML", data=r))
# I used the method="ML" to be able to compare models using anova(model1,
model2)
# Model1 fits a non-linear effect of age with an additive effect of status Here we expect both age and age2 to have 1 df and each STATUS-group will have
1 df as well (which makes 4 df for
the factor STATUS with its 5 levels)... right?
Both age and age2 have 266 df here and STATUS even 71 each! I dont know what
is going wrong here.
Can anyone see what goes wrong here? Many many thanks in advance! Luc te Marvelde
Try anova(model1) and see if that sheds some light on what you are seeing. Mark Lyman