We propose a class of Bayesian semiparametric mixed-effects models; its distinctive feature is the randomness of the grouping of observations, which can be inferred from the data. The model can be viewed under a more natural perspective, as a Bayesian semiparametric regression model on the...

An algorithm that computes nonparametric maximum likelihood estimates of a mixing distribution for a logistic regression model containing random intercepts and slopes is proposed. The algorithm identifies mixing distribution support points as the maxima of the gradient function using a direct...