Generalized linear models with covariate measurement error can be estimated by maximum likelihood using gllamm, a program that fits a large class of multilevel latent variable models (Rabe-Hesketh, Skrondal, and Pickles 2004). The program uses adaptive quadrature to evaluate the log likelihood,...

This presentation focuses on predicted probabilities for multilevel models for dichotomous or ordinal responses. In a three-level model, for instance with patients nested in doctors nested in hospitals, predictions for patients could be for new or existing doctors and, in the latter case, for...

gllamm is a program to fit generalised linear latent and mixed models. Since gllamm6 appeared in the STB (sg129), a large number of new features have been added. Two important extensions will be discussed: 1) More response processes can now be modelled including ordered and unordered categorical...