Currently developing a tutorial of Bayesian random effect modeling using Stan. Right now this is a work in progress. Will include:

1. Examples of using simulated data to check models
2. Examples of Posterior Predictive Checks.
3. Example of using mixture models in a hierarchical context
4. Demonstration of the value of random effect modeling.

The data is from the Beaman, Duflo, Pande, and Topalova (2012) study, which is available on Harvard's Datavese.