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

From: Simon Pickett <S.Pickett_at_exeter.ac.uk>
Date: Tue 05 Sep 2006 - 14:01:30 GMT

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 Pickett
PhD student
Centre For Ecology and Conservation
Tremough Campus
University of Exeter in Cornwall

Tel 01326371852

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