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Handbook of latent variable and related models

Author: Sik-Yum Lee
Publisher: Amsterdam ; Boston : Elsevier/North-Holland, 2007.
Series: Handbook of computing and statistics with applications, v. 1.
Edition/Format:   eBook : Document : English : 1st edView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Handbook of latent variable and related models.
Amsterdam ; Boston : Elsevier/North-Holland, 2007
(DLC) 2006052150
(OCoLC)73954771
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Sik-Yum Lee
ISBN: 9780444520449 0444520449 9780080471266 0080471269
OCLC Number: 162130471
Description: 1 online resource (xxii, 435 pages) : illustrations.
Contents: Preface --
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 Söan) --
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).
Series Title: Handbook of computing and statistics with applications, v. 1.
Responsibility: edited by Sik-Yum Lee.
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Abstract:

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

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