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Introduction to Structural Equation Models
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Social and behavioral scientists routinely grapple with abstract concepts—like depression, democracy, or organizational culture—that resist simple measurement and often exist within intricate webs of relationships. Introduction to Structural Equation Models by Shawn Bauldry offers a comprehensive and accessible entry point into the world of SEMs, blending statistical rigor with practical application. Designed for graduate students and researchers, this volume guides readers through the process of translating complex theoretical frameworks into testable statistical models, fitting models to data, and evaluating model fit.

The book is structured around the SEM workflow, from model specification and identification to estimation and evaluation, with each chapter building systematically on the last. Readers benefit from a balanced approach: advanced mathematical concepts are paired with concrete, worked examples, and each chapter concludes with suggestions for further reading.


 
About the Authors
 
Preface
 
Series Editor’s Introduction
 
Acknowledgments
 
Chapter 1: Introduction
Latent and Observed Variables

 
Multiple Endogenous Variables

 
General Structural Equation Model

 
Statistical Software and Code

 
Outline of Book

 
Further Reading

 
 
Chapter 2: Model Specification
Measurement Model

 
Structural Model

 
*SEMs and DAGs

 
Conclusion

 
 
Chapter 3: Identification and Estimation
Model Identification

 
Estimators

 
Conclusion

 
 
Chapter 4: Model Evaluation and Modification
Overall Model Fit

 
Localized Model Fit

 
Comparative Model Fit

 
Model Modification

 
Conclusion

 
 
Chapter 5: Mediation Analysis
Classical Approach

 
*Counterfactual Approach

 
Sensitivity Analyses

 
Conclusion

 
 
Chapter 6: Categorical and Limited Endogenous Variables
Binary and Ordinal Variables

 
Estimators

 
Model Fit and Parameter Interpretation

 
Generalized Linear Model Framework

 
Conclusion

 
 
Chapter 7: FinalWords
Extensions

 
Pitfalls

 
 
Appendix: General SEM in Matrix Notation
 
References
 
Index

Shawn Bauldry’s Introduction to Structural Equation Models is a clear, comprehensible, and thoughtful guide to SEMs. With relatable examples, balanced coverage of theory and application, and attention to contemporary issues like mediation and categorical outcomes, this book will be invaluable for graduate students and instructors alike.

John Hoffman
Brigham Young University

This book is a game changer. Our program evaluation students need to understand SEM to excel, and this book will transform them from timid to eager. The quality of their projects will improve significantly because they will go beyond memorizing jargon to truly comprehending the purpose and process of SEM in applied settings.

Rick Sperling
St. Mary's University
Key features
  • Balanced Pedagogy: Each chapter combines advanced mathematical concepts with concrete, worked examples, ending with suggestions for further reading.
  • Practical Application: A sustained example runs throughout the book, with downloadable data and code for R, Stata, and Mplus—enables readers to reproduce tables, figures, and compare software outputs.
  • Up-to-date Coverage: Includes advanced topics such as the relationship between SEMs and Directed Acyclic Graphs (DAGs), algebraic identification methods, and the model-implied instrumental variable (MIIV) estimator.
  • Accessible for Multiple Audiences: Clearly marked advanced sections and a structure that supports both newcomers and experienced SEM users.