Multiple imputation vs Full Bayesian approach for handling missing data in Stan

[torkar]

Hi, I think this post and the discussions in there could be of help:

How to handle NA values in multivariate models?

You have two options as @paul.buerkner writes (he might add something to this thread): 1. Multiple imputation using MICE or, 2. Handle missingness during model fitting. The first approach uses, as default, all data to try to infer the missingness, the other approach models the missingness according to your expertise, i.e., you decide explicitly how to model the missingness given your assumptions (it can be done in MICE too, but I find it a bit cumbersome). I see it as in the first case we thro…