Hey
I want to model data where repeated measurements where taken from animals.
I want to compare different treatment groups while correcting for animal specific effects.
The model I want to fit in BRMS looks something like this:
outcome ~ treatment_group + (1 | animal_id)
However, for some measurements the animal_id is missing. These animals have also been measured multiple times but I cannot connect the measured values through their animal_id.
So for this animals I cannot measure the animal specific effect.
I could remove the these measurements but I believe they still contain useful information for the data model.
I was wondering how to best model this in brms?
What I tried currently is to add a new unique ID for each measurement with missing ID. So all these measurements are assumed to be from a different animal (even if they are not).
Are there flaws with this approach?
Thanks in advance