Monte Carlo EM algorithm for generalized linear models with linear structural random effects

We propose generalized linear mixed models with linear structural random effects based on generalized linear mixed models. In this article, an Monte Carlo EM type algorithm is developed for maximum likelihood estimations of the proposed models. To avoid computation of the complicated multiple integrals involved, the E-step is completed by Monte Carlo techniques. The M-step is carried out efficiently by simple Conditional Maximization. Standard errors of MLEs are obtained via Louis's identity.