Latent Markov Models for Longitudinal Data - Bartolucci, Francesco; Farcomeni, Alessio; Pennoni, Fulvia
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Exploring the theory and applications of latent Markov modeling in a common conceptual framework, this book presents a nontechnical overview of latent Markov models and their potential in socio-economic applications. The statistical approach of the text emphasizes inference and the use of models in applications. The book first describes the latent Markov model proposed by Wiggins, taking into account other models in the field, such as latent transition analysis and hidden Markov analysis. The authors then lead readers to the possibility of implementing, using, and calibrating the latest…mehr

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Produktbeschreibung
Exploring the theory and applications of latent Markov modeling in a common conceptual framework, this book presents a nontechnical overview of latent Markov models and their potential in socio-economic applications. The statistical approach of the text emphasizes inference and the use of models in applications. The book first describes the latent Markov model proposed by Wiggins, taking into account other models in the field, such as latent transition analysis and hidden Markov analysis. The authors then lead readers to the possibility of implementing, using, and calibrating the latest developments. They also provide ad hoc MATLABA(R) routines for fitting the proposed models.
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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.
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