Mixed Process Model: Probit and Linear Regression

Hi there,

I am trying to combine probit and classical linear regression equations in latent variable formulations so that their errors can be correlated in the Seemingly Unrelated Regression way (like in Stata’s --cmp-- command). I am struggling with how to set this up (currently I am explicitly modelling latent variables in a naive way and it doesn’t work well). I found the multivariate probit code by @bgoodri on GitHub and was hoping to tweak it. However, I am not super fluent in manipulating likelihoods, so I was hoping you could point me in the right direction of what I need to do? I checked the user manual to no avail. Any advice you could give me would be greatly appreciated, as always!


Those data augmentation things tend not to work well in Stan. You may well have written things about as good as they can get.