Quantile Regression for Binary Longitudinal Data
Description
Implements the Bayesian quantile regression model for binary longitudinal data
(QBLD) developed in Rahman and Vossmeyer (2019) .
The model handles both fixed and random effects and implements both a blocked
and an unblocked Gibbs sampler for posterior inference.