Latent Markov Models for Longitudinal Data: 1st Edition (e-Book) book cover

Latent Markov Models for Longitudinal Data

1st Edition

By Francesco Bartolucci

Chapman and Hall/CRC

252 pages

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Hardback: 9781439817087
pub: 2012-10-29
eBook (VitalSource) : 9780429102578
pub: 2012-10-29
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Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data focuses on the formulation of latent Markov models and the practical use of these models. Numerous examples illustrate how latent Markov models are used in economics, education, sociology, and other fields. The R a

Table of Contents

Overview on Latent Markov Modeling. Background on Latent Variable and Markov Chain Models. Basic Latent Markov Model. Constrained Latent Markov Models. Including Individual Covariates and Relaxing Basic Model Assumptions. Including Random Effects and Extension to Multilevel Data. Advanced Topics about Latent Markov Modeling. Bayesian Latent Markov Models. Appendix. Bibliography. Index.

About the Author

Francesco Bartolucci is a professor of statistics in the Department of Economics, Finance and Statistics at the University of Perugia, where he also coordinates the Ph.D. program in mathematical and statistical methods for the economic and social sciences. His main research interests include latent variable models for cross-sectional and longitudinal categorical data, with applications ranging from educational and psychometric contexts to the analysis of labor market data.

Alessio Farcomeni is a researcher at the University of Rome "La Sapienza". His interests range from analysis of panel data and categorical time series to multiple testing, multivariate analysis and clustering, and model selection.

Fulvia Pennoni is an assistant professor of statistics in the Department of Statistics at the University of Milano-Bicocca. Her main expertise encompasses latent variable modeling. She is currently carrying out research in methods and statistics with intensive statistical programming applications.

Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General