Generalized Latent Variable Modeling

Anders Skrondal

ISBN 10: 1584880007 / ISBN 13: 9781584880004

Published by CRC Press Mai 2004, 2004

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 522 pp. Englisch.

Seller Inventory # 9781584880004

Bibliographic Details

• Title: Generalized Latent Variable Modeling
• Publisher: CRC Press Mai 2004
• Publication Date: 2004
• Language: English
• ISBN 10: 1584880007
• ISBN 13: 9781584880004
• Binding: Buch
• Condition: Neu
• Dimensions: 242W x 167H x 32D millimeters 242 millimeters width by 167 millimeters height by 32 millimeters depth
• Weight: 862 grams

About this title

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.

About the Author

Anders Skrondal, Sophia Rabe-Hesketh