Gllamm: Generalized Linear Latent & Mixed Models

gllamm is a user contributed STATA program to handle a very wide variety of models for addressing multilevel latent and mixed variable models. There are three components to gllamm: estimations tasks(gllamm), post-estimation predictions tasks(gllapred) and simulation(gllasim). Why would one care? In some settings having a unified treatment of estimation for many seemingly unrelated models can help one gain insights into applications and estimation inter-relationships. For example the following models: GLMMs, Multilevel Regressions, Factor models, Item Response, SEM models and Latent Class models are all special cases. If you have access to STATA follow the instructions to download and install gllamm.