This manual describes a Stata program gllamm that can estimate Generalized Linear Latent and Mixed Models (GLLAMMs). GLLAMMs are a class of multilevel latent variable models for (multivariate) responses of mixed type including continuous responses, counts, duration/survival data, dichotomous,...

Latent variable modelling has gradually become an integral part of mainstream statistics and is currently used for a multitude of applications in different subject areas. Examples of 'traditional' latent variable models include latent class models, item-response models, common factor models,...

Wooldridge (2005) provided a simple and elegant solution to the initial conditions problem for dynamic nonlinear unobserved-effects models. His original auxiliary model includes the time-varying explanatory variables at each period. Unfortunately, a popular constrained version that includes...

The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent...

Generalized linear mixed models or multilevel regression models have become increasingly popular. Several methods have been proposed for estimating such models. However,to date there is no single method that can be assumed to work well in all circumstances in terms of both parameter recovery and...