Abstract Breslow and Clayton (J Am Stat Assoc 88: 9–25, 1993) was, and still is, a highly
influential paper mobilizing the use of generalized linear mixed models in epidemiology and …

We consider the situation where the random effects in a generalized linear mixed model
may be correlated with one of the predictors, which leads to inconsistent estimators. We …

The Rasch model is one of the most prominent item response models. In this article, different
item parameter estimation methods for the Rasch model are systematically compared …

Recent literature on panel data emphasizes the importance of accounting for time-varying
unobservable individual effects, which may stem from either omitted individual …

We introduce a diagnostic test for the mixing distribution in a generalised linear mixed
model. The test is based on the difference between the marginal maximum likelihood and …

We study generalized linear latent variable models without requiring a distributional
assumption of the latent variables. Using a geometric approach, we derive consistent …

Generalized linear mixed models (GLMMs) have been widely appreciated in biological and
medical research. Maximum likelihood estimation has received a great deal of attention …

In psychometrics, the canonical use of conditional likelihoods is for the Rasch model in
measurement. Whilst not disputing the utility of conditional likelihoods in measurement, we …

Stratified data arise in several settings, such as longitudinal studies or multicenter clinical
trials. Between‐strata heterogeneity is usually addressed by random effects models, but an …

Generalized linear and nonlinear mixed models (GMMMs and NLMMs) are commonly used
to represent non-Gaussian or nonlinear longitudinal or clustered data. A common …