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Handbook of Latent Variable and Related Models - 1st Edition - ISBN: 9780444520449, 9780080471266

Handbook of Latent Variable and Related Models, Volume 1

1st Edition

Series Volume Editor: Sik-Yum Lee
Hardcover ISBN: 9780444520449
eBook ISBN: 9780080471266
Imprint: North Holland
Published Date: 8th February 2007
Page Count: 460
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Table of Contents

About the Authors
1. Covariance Structure Models for Maximal Reliability of Unit-weighted Composites (Peter M. Bentler)
2. Advances in Analysis of Mean and Covariance Structure When Data are Incomplete (Mortaza Jamshidian, Matthew Mata)
3. Rotation Algorithms: From Beginning to End (Robert I. Jennrich)
4. Selection of Manifest Variables (Yutaka Kano)
5. Bayesian Analysis of Mixtures Structural Equation Models with Missing Data (Sik-Yum Lee)
6. Local Influence Analysis for Latent Variable Models with Nonignorable Missing Responses (Bin Lu, Xin-Yuan Song, Sik-Yum Lee, Fernand Mac-Moune Lai)
7. Goodness-of-fit Measures for Latent Variable Models for Binary Data (D. Mavridis, Irini Moustaki, Martin Knott)
8. Bayesian Structural Equation Modeling (Jesus Palomo, David B. Dunson, Ken Bollen)
9. The Analysis of Structural Equation Model with Ranking Data using Mx (Wai-Yin Poon)
10. Multilevel Structural Equation Modeling (Sophia Rable-Hesketh, Anders Skrondal, Xiaohui Zheng)
11. Statistical Inference of Moment Structure (Alexander Shapiro)
12. Meta-Analysis and Latent Variables Models for Binary Data (Jian-Qing Shi)
13. Analysis of Multisample Structural Equation Models with Applications to Quality of Life Data (Xin-Yuan Song)
14. The Set of Feasible Solutions for Reliability and Factor Analysis (Jos M.F. ten Berge, Gregor Soèan)
15. Nonlinear Structural Equation Modeling as a Statistical Method (Melanie M. Wall, Yasuo Amemiya)
16. Matrix Methods and Their Applications to Factor Analysis (Haruo Yanai, Yoshio Takane)
17. Robust Procedures in Structural Equation Modeling (Ke-Hai Yuan, Peter M. Bentler)
18. Stochastic Approximation Algorithms for Estimation of Spatial Mixed Models (Hongtu Zhu, Faming Liang, Minggao Gu, Bradley Peterson)


This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables.

Key Features

  • Covers a wide class of important models
    - Models and statistical methods described provide tools for analyzing a wide spectrum of complicated data
    - Includes illustrative examples with real data sets from business, education, medicine, public health and sociology.
    - Demonstrates the use of a wide variety of statistical, computational, and mathematical techniques.


Primary Market(s)
Psychology, sociology

Secondary Market(s)
Business, Biomedical


No. of pages:
© North Holland 2007
8th February 2007
North Holland
Hardcover ISBN:
eBook ISBN:

Ratings and Reviews

About the Series Volume Editor

Sik-Yum Lee