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Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models - Hardcover
Book 9 of 45: Chapman & Hall/CRC Interdisciplinary Statistics
Synopsis
This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wide range of estimation and prediction methods from biostatistics, psychometrics, econometrics, and statistics. They present exciting and realistic applications that demonstrate how researchers can use latent variable modeling to solve concrete problems in areas as diverse as medicine, economics, and psychology. The examples considered include many nonstandard response types, such as ordinal, nominal, count, and survival data. Joint modeling of mixed responses, such as survival and longitudinal data, is also illustrated. Numerous displays, figures, and graphs make the text vivid and easy to read.
About the authors:
Anders Skrondal is Professor and Chair in Social Statistics, Department of Statistics, London School of Economics, UK
Sophia Rabe-Hesketh is a Professor of Educational Statistics at the Graduate School of Education and Graduate Group in Biostatistics, University of California, Berkeley, USA.
"synopsis" may belong to another edition of this title.
About the Author
Anders Skrondal, Sophia Rabe-Hesketh
"About this title" may belong to another edition of this title.
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Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models (Chapman & Hall/CRC Interdisciplinary Statistics)
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Chapman and Hall/CRC 11/05/2004, 2004
ISBN 10: 1584880007
ISBN 13: 9781584880004
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Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models
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ISBN 10: 1584880007
ISBN 13: 9781584880004
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Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models (Chapman & Hall/CRC Interdisciplinary Statistics)
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