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 …

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 …

First of all I find that the authors have written an excellent, comprehensive framework on
latent Markov modeling. This model and related models, such as mixture models, latent …

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 …

Latent Markov (LM) models represent an important class of models for the analysis of
longitudinal data, especially when response variables are categorical. These models have a …

We compare different selection criteria to choose the number of latent states of a multivariate
latent Markov model for longitudinal data. This model is based on an underlying Markov …

For a class of latent Markov models for discrete variables having a longitudinal structure, we
introduce an approach for formulating and testing linear hypotheses on the transition …

This article presents a general framework for the analysis of discrete-time longitudinal data
using latent class models. The encompassing model is the mixture latent Markov model, a …

Abstract focus... on Markov models that allow us to make statements about change
(progress, growth or decay, regression) and/or stability across time/these models start from …

This chapter deals with longitudinal categorical data. Such data may be of two types, in
general. Type I refers to the situation in which a few subjects are measured repeatedly at …