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About the Authors
- Covariance Structure Models for Maximal Reliability of Unit-weighted Composites (Peter M. Bentler)
- Advances in Analysis of Mean and Covariance Structure When Data are Incomplete (Mortaza Jamshidian, Matthew Mata)
- Rotation Algorithms: From Beginning to End (Robert I. Jennrich)
- Selection of Manifest Variables (Yutaka Kano)
- Bayesian Analysis of Mixtures Structural Equation Models with Missing Data (Sik-Yum Lee)
- Local Influence Analysis for Latent Variable Models with Nonignorable Missing Responses (Bin Lu, Xin-Yuan Song, Sik-Yum Lee, Fernand Mac-Moune Lai)
- Goodness-of-fit Measures for Latent Variable Models for Binary Data (D. Mavridis, Irini Moustaki, Martin Knott)
- Bayesian Structural Equation Modeling (Jesus Palomo, David B. Dunson, Ken Bollen)
- The Analysis of Structural Equation Model with Ranking Data using Mx (Wai-Yin Poon)
- Multilevel Structural Equation Modeling (Sophia Rable-Hesketh, Anders Skrondal, Xiaohui Zheng)
- Statistical Inference of Moment Structure (Alexander Shapiro)
- Meta-Analysis and Latent Variables Models for Binary Data (Jian-Qing Shi)
- Analysis of Multisample Structural Equation Models with Applications to Quality of Life Data (Xin-Yuan Song)
- The Set of Feasible Solutions for Reliability and Factor Analysis (Jos M.F. ten Berge, Gregor Soèan)
- Nonlinear Structural Equation Modeling as a Statistical Method (Melanie M. Wall, Yasuo Amemiya)
- Matrix Methods and Their Applications to Factor Analysis (Haruo Yanai, Yoshio Takane)
- Robust Procedures in Structural Equation Modeling (Ke-Hai Yuan, Peter M. Bentler)
- 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.
- 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 Education
Secondary Market(s) Business, Biomedical
- No. of pages:
- © North Holland 2007
- 8th February 2007
- North Holland
- Hardcover ISBN:
- eBook ISBN:
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