Details on model development, particularly working with the gamma and negative binomial parameterizations in JAGS, plus pseudo-code for generating cross-validated posterior predictions.
We develop a Bayesian nonparametric model for a longitudinal response in the presence of nonignorable missing data. Our general approach is to first specify a working model that flexibly models the mi
