I would like to derive individual growth rates from our growth model directly, similar to this OP and this OP.
I am working with a dataset that contains the age and weight (wt) measurements for ~2000 individuals in a population. Each individual is represented by a unique id number.
A sample of the data can be found here. Here is what the data looks like:
id age wt
1615 6 15
3468 32 61
1615 27 50
1615 60 145
6071 109 209
6071 125 207
10645 56 170
10645 118 200
I have developed a non-linear growth curve to model growth for this dataset (at the population level). It looks like this:
wt~ A*atan(k*age - t0) + m
which predicts weight (wt) for a given age and has modifiable parameters A, t0, and m. I have fit this model to the dataset at the population level using a nlme regression fit where I specified individual id as a random effect and used pdDiag to specify each parameter as uncorrelated. (Note: the random effect would need to be dropped when looking at the individual level.)
The code for this looks like:
nlme.k = nlme(wt~ A*atan(k*age - t0) + m,
data = df,
fixed = A+k+t0+m~1,
random = list(id = pdDiag(A+t0+k+m~1)), #cannot include when looking at the individual level
start = c(A = 99.31,k = 0.02667, t0 = 1.249, m = 103.8), #these values are what we are using at the population level # might need to be changed for individual models
na.action = na.omit,
control = nlmeControl(maxIter = 200, pnlsMaxIter = 10, msMaxIter = 100))
I have our population level growth model (nlme.k), but I would like to use it to derive/extract individual values for each growth constant.
How can I extract individual growth constants for each id using my population level growth model (nlme.k)? Note that I don't need it to be a solution that uses nlme, that is just the model I used for the population growth model.
Any suggestions would be appreciated!