Generalized Latent Variable Modeling

<p>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.</p><p>About the authors: </p><p><b>Anders Skrondal</b> is Professor and Chair in Social Statistics Department of Statistics London School of Economics UK </p><p><b>Sophia Rabe-Hesketh </b>is a Professor of Educational Statistics at the Graduate School of Education and Graduate Group in Biostatistics University of California Berkeley USA.</p>