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Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural
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Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models Hardcover - 2004 - 1st Edition

by Anders Skrondal

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Exciting and realistic applications demonstrate how researchers can use latent variable modeling to solve concrete problems in areas as diverse as medicine, economics, and psychology.

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From the publisher

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.

First line

Since this book is about latent variable models it is natural to begin with a discussion of the meaning of the concept `latent variable'.