Multilevel Structural Equation Modeling

Multilevel Structural Equation Modeling
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Описание книги

Multilevel Structural Equation Modeling by Bruno Castanho Silva, Constantin Manuel Bosancianu, and Levente Littvay 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.

Оглавление

Bruno Castanho Silva. Multilevel Structural Equation Modeling

Quantitative Applications in the Social Sciences

MULTILEVEL STRUCTURAL EQUATION MODELING

CONTENTS

LIST OF FIGURES

Series Editor’s Introduction

About the Authors

Acknowledgments

Publisher’s Acknowledgments

Companion Website

Chapter 1. Introduction. About the Book and MSEM

Quick Review of Structural Equation Models

Model Specification and Identification

Identification

Estimation

Model Fit

Further Readings on SEM

Quick Review of Multilevel Models

Notation

Estimation and Model Fit

Sample Sizes

Further Readings on MLM

Introduction to MSEM and Its Notation. A Multilevel Path Model

Full Structural Models in a Multilevel Setting

Estimation and Model Fit

Scope of the Book and Online Materials

Descriptions of Images and Figures

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

Mediation

Moderation

Centering in MSEM

Summary

Descriptions of Images and Figures

Chapter 3. Multilevel Factor Models

Confirmatory Factor Analysis in Multiple Groups

Two-Level CFA

Estimation

Identification

Results

Partial Saturation Fit Test

Unidimensional Level 2 Factor Structure

Random Latent Variable Intercepts

Multilevel CFA With Random Loadings

Measurement Invariance

Example

Model Fit and Comparison

Summary

Descriptions of Images and Figures

Chapter 4. Multilevel Structural Equation Models. Bringing Factor and Path Models Together

Random Intercept of Observed Outcome

Multilevel Latent Covariate Model

Structural Models With Between-Level Latent Variables

Random Intercepts of Latent Variables

Random Slopes MSEM

Model Comparison

Summary

Descriptions of Images and Figures

Chapter 5. Conclusion

References

Index

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A SAGE PUBLICATIONS SERIES

Los Angeles | London | New Delhi | Singapore | Washington DC | Melbourne

.....

Series Editor

Carl Berning, University of Mainz

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