[R] help: advice on the structuring of ReML models for analysing growth curves

[Simon Pickett]

Hi R experts,
I am interested on the effects of two dietry compunds on the growth of
chicks. Rather than extracting linear growth functions for each chick and
using these in an analysis I thought using ReML might provide a neater and
better way of doing this. (I have read the pdf vignette("MlmSoftRev") and
"Fitting linear mixed models in R" by Douglas Bates but I am not entirely
sure that I have the right solution).

Basically I fed chicks in nest boxes over a period of time and weighed
them each time I fed them. I presume that "chick id" should be a random
factor and should be nested within "nest box number"? (Chicks were not
moved around so this should make things more simple). Also since the
chicks were measured repeatedly over time I presume that this should be a
random factor? Growth is not linear exactly (more quadratic), so I thought
rather than put time in the fixed model I want to control for the effects
of time as a random factor....
The resulting model is this
where id=chick identity and brood=nest box
model1<-lmer(weight~treatment1*treatment2*brood
size*sex+(id|brood)+(1|brood)+(1|age), data=H)

Is this the "right" approach or am I barking up the wrong tree?
Any suggestions much appreciated,
Simon


Simon Pickett
PhD student
Centre For Ecology and Conservation
Tremough Campus
University of Exeter in Cornwall
TR109EZ
Tel 01326371852