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Books > Social sciences > Psychology > Psychological methodology
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Latent Markov Models for Longitudinal Data (Paperback)
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Latent Markov Models for Longitudinal Data (Paperback)
Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences
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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 and MATLAB (R)
routines used for the examples are available on the authors'
website. The book provides you with the essential background on
latent variable models, particularly the latent class model. It
discusses how the Markov chain model and the latent class model
represent a useful paradigm for latent Markov models. The authors
illustrate the assumptions of the basic version of the latent
Markov model and introduce maximum likelihood estimation through
the Expectation-Maximization algorithm. They also cover constrained
versions of the basic latent Markov model, describe the inclusion
of the individual covariates, and address the random effects and
multilevel extensions of the model. After covering advanced topics,
the book concludes with a discussion on Bayesian inference as an
alternative to maximum likelihood inference. As longitudinal data
become increasingly relevant in many fields, researchers must rely
on specific statistical and econometric models tailored to their
application. A complete overview of latent Markov models, this book
demonstrates how to use the models in three types of analysis:
transition analysis with measurement errors, analyses that consider
unobserved heterogeneity, and finding clusters of units and
studying the transition between the clusters.
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