An extension of the Rasch model with correlated latent variables is proposed to model correlated binary data within families. The latent variables have the classical correlation structure of Fisher (1918) and the model parameters thus have genetic interpretations. The proposed model is fitted to data using a hybrid of the Metropolis-Hastings algorithm and the MCEM modification of the EM-algorit...

Most MRCP and MRCS Part 1 candidates would be advised to invest in a Sainsbury’s shopping trolley if they decide to venture to their local university bookshop in pursuit of a relevant MCQs textbook. The shelves of these stores creak from the burden of the wide selection of texts. The unfortunate MCEM / MRCS A&E candidate will be left with growing anxiety and the knowledge that there are very fe...

Hierarchical models have emerged as a promising tool for the analysis of repeated binary data. However, the computational complexity in these models have limited their applications in practice. Several approaches have been proposed in the literature to overcome the computational difficulties including maximum likelihood estimation from a frequentist perspective (e.g., J.Amer. Statist.Assoc. 89 ...

The analysis of finite mixture models for exponential repeated data is considered. The mixture components correspond to different possible states of the statistical units. Dependency and variability of repeated data are taken into account through random effects. For each component, an exponential mixed model is thus defined. When considering parameter estimation in this mixture of exponential m...

Mixed data refers to a mixture of continuous and categorical variables. The clustering problem with mixed is long-standing statistical problem. latent Gaussian model, model-based approach for such problem, has received attention owing its simplicity interpretability. However, these approaches are prone dimensionality problems. Specifically, parameters must be estimated each group, the number co...