[R] repeated values, nlme, correlation structures

[Patrick Giraudoux]

Dear listers,

My request of last week seems not to have drawn someone's attention. 
Suppose it was not clear enough.

I am coping with an observational study where people's aim was to fit 
growth curve for a population of young blue tits. For logistic reasons, 
people have not been capable to number each individual, but they have a 
method to assess their age. Thus, nestboxes were visited occasionnally, 
youngs aged and weighted.

This makes a multilevel data set, with two classification factors:

- the nestbox (youngs shared the same parents and general feeding 
conditions)
- age in each nestbox (animals from the same nestbox have been weighed 
along time, which likely leads to time correlation)

Life would have been heaven if individuals were numbered, and thus nlme 
correlation structure implemented in the package be used easy. As 
mentioned above, this could not be the case. In a first approach, I 
actually used the mean weight of the youngs weighed at each age in nest 
boxes for the variable "age", and could get a nice fit with "nestbox" as 
random variable and corCAR1(form=~age|nestbox) as covariation structure.

modm0c<-nlme(pds~Asym/(1+exp((xmid-age)/scal)),
    fixed=list(Asym~1,xmid~1,scal~1),
    random=Asym+xmid~1|nestbox,data=croispulm,
    start=list(fixed=c(10,5,2.2)),
    method="ML",
    corr=corCAR1(form=~age|nestbox)
    )

Assuming that I did not commited some error in setting model parameters 
(?), this way of doing is not fully satisfying, since using the mean of 
each age category as variable  leads to a  loss of information regarding 
the variance on the weight at each age and nestbox.

My question is: is there a way to handle repeated values per group (here 
several youngs in an age category in each nestbox) in such a case?

I would really appreciate an answer, even negative...

Kind regards,

Patrick