We provide a comprehensive overview of latent Markov (LM) models for the analysis of
longitudinal categorical data. We illustrate the general version of the LM model which …

Drawing on the authors' extensive research in the analysis of categorical longitudinal data,
this book focuses on the formulation of latent Markov models and the practical use of these …

The focus of this book is on models for contingency table analysis. It deals mainly with log-
linear models and special models for ordinal data (log-linear or nonlinear). Special models …

Statistical models defined by imposing restrictions on marginal distributions of contingency
tables have received considerable attention recently. This paper introduces a general …

For the analysis of multivariate categorical longitudinal data, we propose an extension of the
dynamic logit model. The resulting model is based on a marginal parameterization of the …

We provide a comprehensive overview of latent Markov (LM) models for the analysis of
longitudinal categorical data. The main assumption behind these models is that the …

We extend Bergsma and Rudas (2002)'s hierarchical complete marginal parameterization to
allow for logits and higher order effects of global and continuation type which may be more …

We propose a class of multidimensional Item Response Theory models for polytomously-
scored items with ordinal response categories. This class extends an existing class of …

A class of Item Response Theory (IRT) models for binary and ordinal polytomous items is
illustrated and an R package for dealing with these models, named MultiLCIRT, is …

The motivation for this book stems from the apparent lack of a general and flexible
methodology for testing hypotheses about relations among correlated categorical marginal …