Handbook of Latent Variable and Related Models
eBook - ePub

Handbook of Latent Variable and Related Models

,
  1. 458 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Handbook of Latent Variable and Related Models

,

About this book

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.

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Yes, you can access Handbook of Latent Variable and Related Models by in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
North Holland
Year
2011
Print ISBN
9780444520449
eBook ISBN
9780080471266
Topic
Mathematics
Subtopic
Probability & Statistics
Index
Mathematics

Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Handbook of Computing and Statistics with Applications
  5. Copyright
  6. Handbook Series on Computing and Statistics with Applications
  7. Preface
  8. About the Authors
  9. Contributors
  10. Chapter 1: Covariance Structure Models for Maximal Reliability of Unit-Weighted Composites
  11. Chapter 2: Advances in Analysis of Mean and Covariance Structure when Data are Incomplete
  12. Chapter 3: Rotation Algorithms: From Beginning to End
  13. Chapter 4: Selection of Manifest Variables
  14. Chapter 5: Bayesian Analysis of Mixtures Structural Equation Models with Missing Data
  15. Chapter 6: Local Influence Analysis for Latent Variable Models with Non-Ignorable Missing Responses
  16. Chapter 7: Goodness-of-Fit Measures for Latent Variable Models for Binary Data
  17. Chapter 8: Bayesian Structural Equation Modeling
  18. Chapter 9: The Analysis of Structural Equation Model with Ranking Data using Mx
  19. Chapter 10: Multilevel Structural Equation Modeling
  20. Chapter 11: Statistical Inference of Moment Structures
  21. Chapter 12: Meta-Analysis and Latent Variable Models for Binary Data
  22. Chapter 13: Analysis of Multisample Structural Equation Models with Applications to Quality of Life Data
  23. Chapter 14: The Set of Feasible Solutions for Reliability and Factor Analysis
  24. Chapter 15: Nonlinear Structural Equation Modeling as a Statistical Method
  25. Chapter 16: Matrix Methods and their Applications to Factor Analysis
  26. Chapter 17: Robust Procedures in Structural Equation Modeling
  27. Chapter 18: Stochastic Approximation Algorithms for Estimation of Spatial Mixed Models
  28. Author Index
  29. Subject Index