Francesco Bartolucci, Alessio Farcomeni, Fulvia Pennoni

Latent Markov Models for Longitudinal Data (eBook, PDF)

• Format: PDF

Produktbeschreibung

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 models.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 252
• Erscheinungstermin: 29. Oktober 2012
• Englisch
• ISBN-13: 9781466583719
• Artikelnr.: 43977088

Autorenporträt

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.

Inhaltsangabe

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.

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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.

Rezensionen

"I enjoyed reading this book very much: the writing style is clear and concise, and the mathematical presentation is easy to follow. Notations are well thought out and the technical derivations are thorough. The book is a valuable resource on latent Markov models to students, researchers, and practitioners."
-Alexander R. De Leon, Technometrics, February 2015

"... a useful contribution to the literature. ... The exposition is easy to follow for anyone who has encountered random effects models for longitudinal data. ... The overall structure is well thought out. ... The authors clearly have considerable practical experience in the application of this technique, and they have made important contributions to its literature."
-Geoff Jones, Australian & New Zealand Journal of Statistics, 56, 2014

"The book gives an excellent introduction as well as coverage of theoretical basics of latent Markov model analysis and their practical applications. ... I enjoyed reading the book, its clarity of exposition, its fairly compact format, and carefully worked out examples that did a good job in illustrating the background theory."
-Seppo Pynnönen, International Statistical Review, 2014