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Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models
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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.
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Taylor and Francis; May 2004
528 pages; ISBN 9781135443405
Read online, or download in secure PDF format
528 pages; ISBN 9781135443405
Read online, or download in secure PDF format
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ISBNs
0203489438
9780203489437
9781135443399
9781135443405
9781584880004