Umfang:
Online Ressource (xxii, 435 p.)
,
illustrations.
Ausgabe:
1st ed.
Ausgabe:
Online-Ressource ScienceDirect
ISBN:
9780444520449
,
0444520449
,
9780080471266
,
0080471269
Serie:
Handbook of computing and statistics with applications v. 1
Inhalt:
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)
Inhalt:
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
Anmerkung:
Includes bibliographical references and indexes. - Description based on print version record
Weitere Ausg.:
ISBN 0444520449
Weitere Ausg.:
Druckausg. Handbook of latent variable and related models Amsterdam : Elsevier, 2008 ISBN 9780444520449
Sprache:
Englisch
Fachgebiete:
Mathematik
Schlagwort(e):
Datenverarbeitung
;
Multivariate Analyse
;
Statistik
;
Electronic books
;
Electronic books
DOI:
10.1016/B978-0-444-52044-9.X5000-9
URL:
https://doi.org/10.1016/B978-0-444-52044-9.X5000-9
URL:
Volltext
(Deutschlandweit zugänglich)
