The focus of this article is on Markov models for the analysis of panel data and, more
specifically, on data obtained from repeated measurements of one categorical variable at …

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 …

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 …

The process of change in a discrete characteristic is seldom the same for every respondent
in a panel survey. Mixed Markov latent class models describe cross-tables of consecutive …

The influx of intensive longitudinal data creates a pressing need for complex modeling tools
that help enrich our understanding of how individuals change over time. Multilevel vector …

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 …

With a few exceptions (see Tuma, 1976; Littman and Mode, 1977; Pickens and Soyka,
1980), most attempts to model individual choice behavior with Markov and related models …

Markov modeling presents an attractive analytical framework for researchers who are
interested in state-switching processes occurring within a person, dyad, family, group, or …

Panel data are observations of a continuous-time process at arbitrary times, for example,
visits to a hospital to diagnose disease status. Multi-state models for such data are generally …

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 …