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Multilevel Structural Equation Modeling

Multilevel Structural Equation Modeling

May 2019 | 144 pages | SAGE Publications, Inc
 Multilevel Structural Equation Modeling serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in the social sciences. As the first book of its kind, this title is an accessible, hands-on introduction for beginners of the topic. The authors predict a growth in this area, fueled by both data availability and also the availability of new and improved software to run these models. The applied approach, combined with a graphical presentation style and minimal reliance on complex matrix algebra guarantee that this volume will be useful to social science graduate students wanting to utilize such models.
List of Figures  
About the Authors  
Series Editor's Introduction  
Chapter 1: Introduction
About the Book and MSEM  
Quick Review of Structural Equation Models  
Quick Review of Multilevel Models  
Introduction to MSEM and Its Notation  
Estimation and Model Fit  
Scope of the Book and Online Materials  
Chapter 2: Multilevel Path Models
Multilevel Regression Example  
Random Intercepts Model  
Random Slopes Model  
Comparison of Random Intercepts and Random Slopes Models  
Mediation and Moderation  
Chapter 3: Multilevel Factor Models
Multigroup CFA  
Two-Level CFA  
Random Latent Variable Intercepts  
Random Loadings  
Chapter 4: Multilevel Structural Equation Models
Bringing Factor and Path Models Together  
Random Intercept of Observed Outcome  
Multilevel Latent Covariate Model  
Between-Level Latent Variables  
Random Slopes MSEM  
Chapter 5: Conclusion


Student Study Site

A website for the book at includes replication codes for lavaan for R and Mplus, data for all the examples reported, and two LaTeX files to produce all equations and figures from the book.

“This book provides a terrific introduction to the key models and principles of multilevel SEM. The examples speak for themselves, and the authors manage well to help readers understand and evaluate the beauty of MSEM. Datasets are by and large available and ready for course use. This is a book that can easily adopted in an introductory MSEM course.”

Ronny Scherer
University of Oslo
Key features


  • Examples walk readers through the main modeling possibilities of MSEM, including software scripts in R (which is free) and Mplus.
  • Codes and data from the book examples are easy to replicate for use in readers’ own data and models.
  • Description of advanced topics gives a roadmap to more advanced applications which are not covered in the book.
  • New mathematical notation of models make concepts easier for students who don't have a background in matrix algebra.


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ISBN: 9781544323053