Latent Markov Models for Longitudinal Data

Latent Markov Models for Longitudinal Data is a comprehensive guide that provides researchers with the tools they need to analyze categorical longitudinal data using latent Markov models.
Latent Markov Models for Longitudinal Data is a comprehensive guide that provides researchers with the tools they need to analyze categorical longitudinal data using latent Markov models. It focuses on the formulation of latent Markov models and their practical applications in economics, education, sociology, and other fields. The book covers basic and advanced topics, including transition analysis, unobserved heterogeneity, and cluster analysis, and demonstrates how to use the models with R and MATLAB® routines.

Format: Paperback / softback
Length: 254 pages
Publication date: 21 January 2023
Publisher: Taylor & Francis Ltd

Drawing on the author's extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data delves into the formulation of latent Markov models and their practical applications across various fields. Numerous examples showcase the utilization of latent Markov models in economics, education, sociology, and other domains. The R and MATLAB® routines employed for these examples are readily accessible on the author's website.

The book serves as a comprehensive guide, providing essential background on latent variable models, particularly the latent class model. It explores how the Markov chain model and the latent class model serve as valuable paradigms for latent Markov models. The authors elucidate the assumptions underlying the basic version of the latent Markov model, introduce maximum likelihood estimation through the Expectation-Maximization algorithm, and delve into constrained versions of the model, encompassing the inclusion of individual covariates and addressing random effects and multilevel extensions.

After covering advanced topics, the book concludes with a discussion on Bayesian inference as an alternative to maximum likelihood inference.

As longitudinal data gain increasing importance in numerous fields, researchers must rely on specialized statistical and econometric models tailored to their specific applications. Latent Markov Models for Longitudinal Data offers a comprehensive overview of latent Markov models, demonstrating their utility in three types of analysis: transition analysis with measurement errors, analyses considering unobserved heterogeneity, and the identification of clusters of units and the study of transitions between these clusters.

By leveraging the author's extensive expertise and comprehensive coverage, this book serves as a valuable resource for scholars and practitioners seeking to employ latent Markov models in their research endeavors.

Weight: 470g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032477541