Table of Contents

Part 1. Background

1. Introduction and Overview
Rick H. Hoyle
2. Key Advances in the History of Structural Equation Modeling
Ross L. Matsueda
3. Graphical Representation of Structural Equation Models using Path Diagrams
Moon-ho Ringo Ho, Stephen Stark, and Olexander Chernyshenko
4. Latent Variables in Structural Equation Modeling
Kenneth A. Bollen and Rick H. Hoyle
5. The Causal Foundations of Structural Equation Modeling
Judea Pearl
6. Simulation Methods in Structural Equation Modeling
Deborah L. Bandalos and Phillip Gagné

Part 2. Fundamentals

7. Assumptions in Structural Equation Modeling
Rex B. Kline
8. Model Specification in Structural Equation Modeling
Rick H. Hoyle
9. Identification: A Non-technical Discussion of a Technical Issue
David A. Kenny and Stephanie Milan
10. Estimation in Structural Equation Modeling
Pui-Wa Lei and Qiong Wu
11. Power Analysis for Tests of Structural Equation Models
Taehun Lee, Li Cai, and Robert C. MacCallum
12. Categorical Data in the Structural Equation Modeling Framework
Michael C. Edwards, R. J. Wirth, Carrie R. Houts, and Nuo Xi
13. Model Fit and Model Selection in Structural Equation Modeling
Stephen G. West, Aaron B. Taylor, and Wei Wu
14. Model Modification in Structural Equation Modeling
Chih-Ping Chou and Jimi Huh
15. Equivalent Models: Concepts, Problems, Alternatives
Larry J. Williams

Part 3. Implementation

16. Doing Your Homework: Preparing Data for Structural Equation Modeling
Patrick S. Malone and Jill B. Lubansky
17. Structural Equation Modeling with Missing Data
John W. Graham and Donna L. Coffman
18. Bootstrapping Standard Errors and Data-Model Fit Statistics in Structural Equation Modeling
Gregory R. Hancock and Min Liu
19. Choosing SEM Computer Software: Snapshots of LISREL, EQS, AMOS, and Mplus
Barbara M. Byrne
20. Structural Equation Modeling in R with the sem and OpenMx Packages
John Fox, Jarrett Byrnes, Steven Boker, and Michael Neale
21. The Structural Equation Modeling Research Report
Anne Boomsma, Rick H. Hoyle, and A. T. Panter

Part 4. Basic Applications

22. Confirmatory Factor Analysis
Timothy A. Brown and Michael T. Moore
23. Investigating Measurement Invariance Using Confirmatory Factor Analysis
Roger E. Millsap and Margarita Olivera-Aguilar
24. A Flexible SEM Approach for Analyzing Means
Samuel B. Green and Marilyn S. Thompson
25. Mediation/Indirect Effects in Structural Equation Modeling
Jeewon Cheong and David P. MacKinnon
26. Structural Equation Models of Latent Interaction
Herbert W. Marsh, Zhonglin Wen, Benjamin Nagengast, and Kit-Tai Hau
27. Autoregressive Longitudinal Models
Jeremy C. Biesanz
28. Scale Construction and Development Using Structural Equation Modeling
Tenko Raykov

Part 5. Advanced Applications

29. Measurement Models for Ordered Categorical Indicators
James A. Bovaird and Natalie Koziol
30. Multilevel Structural Equation Modeling
Sophia Rabe-Hesketh, Anders Skrondal, and Xiaohui Zheng
31. An Overview of Growth Mixture Modeling: A Simple Nonlinear Application in OpenMx
Mariya P. Shiyko, Nilam Ram, and Kevin J. Grimm
32. Latent Curve Modeling of Longitudinal Growth Data
John J. McArdle
33. Dynamic Factor Models for Longitudinally Intensive Data:
Description and Estimation via Parallel Factor Models of Cholesky Decomposition
Phillip Wood
34. Latent Trait-State Models
David A. Cole
35. Longitudinal Structural Models for Assessing Dynamics in Dyadic Interactions
Emilio Ferrer and Hairong Song
36. Structural Equation Modeling in Genetics
Sanja Franić, Conor V. Dolan, Denny Borsboom, and Dorret I. Boomsma
37. Structural Equation Models of Imaging Data
Anthony R. McIntosh and Andrea B. Protzner
38. Bayesian Structural Equation Modeling
David Kaplan and Sarah Depaoli
39. Spatial Structural Equation Modeling
Melanie M. Wall
40. Automated Structural Equation Modeling Strategies
George A. Marcoulides and Marsha Ing