I have a question about modeling correlated random effects. The model is:
I converted it to non-centered parametrization:
where is 10 dimensional vector of parameters and f is system of DOEs.
However, stan gave me two modes for which are visible for some i. Pairs plot for vectorshows that scales of random effects are correlated. Therefore, my guess is that by introducing covariance matrixwould help to remove those correlations and hopefully multiple modes. The problem is in PK domain and i is a patient while t is time when a sample of blood is drawn (is plasma concentration for patient i at time t). Each patient has 10 PK parameters and there are two groups of patients. Because of physical considerations (different transporters) some parameters in the second group should be fixed to 0. Can anybody suggest how to define covariance matrix in such case. Actually I was planning to use Cholesky decomposition to speed up stan simulation.
Thanks for any advice,