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Multilevel Structural Equation Modeling

Multilevel Structural Equation Modeling

May 2019 | 144 pages | SAGE Publications, Inc
Multilevel Structural Equation Modeling, by Silva, Bosancianu, and Littvay focuses on the confluence of two fields in applied statistics: multilevel modeling (MLM) and structural equation modeling (SEM). Multilevel structural equation modeling (MSEM) extends SEM techniques into multilevel data, while also allowing for the testing of more complex relationships than one dependent variable and multiple independent variables, and permits the inclusion of latent variables into multilevel models. While these two fields are closely related, there have been very few works demonstrating how they can be combined; those that exist are isolated chapters in advanced handbooks or short sections in textbooks. Additionally, much of the existing work is highly technical. Multilevel Structural Equation Modeling serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in in the social sciences. 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 authors' applied approach, combined with a graphical presentation style and minimal reliance on complex matrix algebra should guarantee that the volume will appeal 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.

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ISBN: 9781544323053