
Multilevel Structural Equation Modeling
SAGE Publications Inc (Publisher)
1st Edition
Published on 11. July 2019
Book
Paperback/Softback
144 pages
978-1-5443-2305-3 (ISBN)
Description
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.
Reviews / Votes
"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 SchererMore details
Series
Language
English
Place of publication
Thousand Oaks
United States
Target group
College/higher education
Dimensions
Height: 216 mm
Width: 140 mm
Weight
197 gr
ISBN-13
978-1-5443-2305-3 (9781544323053)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Bruno Castanho Silva is a post-doctoral researcher at the Cologne Center
for Comparative Politics (CCCP), University of Cologne. Bruno received
his PhD from the Department of Political Science at Central European University
and teaches introductory and advanced quantitative methods courses,
including Multilevel Structural Equation Modeling and Machine Learning
at the European Consortium for Political Research Methods Schools. His
methodological interests are on applications of structural equation models
for scale development and causal analysis, and statistical methods of causal
inference with observational and experimental data. Constantin Manuel Bosancianu is a post-doctoral researcher at the Wissenschaftszentrum
Berlin fuer Sozialforschung (WZB), in the Institutions and
Political Inequality research unit. He received his PhD from the Department
of Political Science at Central European University in Budapest, Hungary
and has been an instructor for multiple statistics courses and workshops at
the European Consortium for Political Research Methods Schools, at the
Universities of Heidelberg, Giessen and Zagreb, as well as at the Institute
of Sociology of the Czech Academy of Sciences. Manuel's methodological
focus is on practical applications of multilevel models, Bayesian analysis,
and the analysis of time-series cross-sectional data sets. Levente Littvay is associate professor at Central European University's
Department of Political Science. Recipient of the institution's Distinguished
Teaching Award for graduate courses in research methods and applied statistics
with a topical emphasis on political psychology, experiments and American
politics. He received an MA and a PhD in Political Science and an MS in
Survey Research and Methodology from the University of Nebraska-Lincoln,
taught numerous methods workshops and is an academic co-convenor of the
European Consortium for Political Research Methods Schools. His research
interests include populism, political socialization and biological explanations
of social and political attitudes and behaviors. He often works as a methodologist
with medical researchers and policy analysts, co-runs the Hungarian
Twin Registry, is an associate editor for social sciences of Twin Research and
Human Genetics and publishes in both social science and medical journals.
for Comparative Politics (CCCP), University of Cologne. Bruno received
his PhD from the Department of Political Science at Central European University
and teaches introductory and advanced quantitative methods courses,
including Multilevel Structural Equation Modeling and Machine Learning
at the European Consortium for Political Research Methods Schools. His
methodological interests are on applications of structural equation models
for scale development and causal analysis, and statistical methods of causal
inference with observational and experimental data. Constantin Manuel Bosancianu is a post-doctoral researcher at the Wissenschaftszentrum
Berlin fuer Sozialforschung (WZB), in the Institutions and
Political Inequality research unit. He received his PhD from the Department
of Political Science at Central European University in Budapest, Hungary
and has been an instructor for multiple statistics courses and workshops at
the European Consortium for Political Research Methods Schools, at the
Universities of Heidelberg, Giessen and Zagreb, as well as at the Institute
of Sociology of the Czech Academy of Sciences. Manuel's methodological
focus is on practical applications of multilevel models, Bayesian analysis,
and the analysis of time-series cross-sectional data sets. Levente Littvay is associate professor at Central European University's
Department of Political Science. Recipient of the institution's Distinguished
Teaching Award for graduate courses in research methods and applied statistics
with a topical emphasis on political psychology, experiments and American
politics. He received an MA and a PhD in Political Science and an MS in
Survey Research and Methodology from the University of Nebraska-Lincoln,
taught numerous methods workshops and is an academic co-convenor of the
European Consortium for Political Research Methods Schools. His research
interests include populism, political socialization and biological explanations
of social and political attitudes and behaviors. He often works as a methodologist
with medical researchers and policy analysts, co-runs the Hungarian
Twin Registry, is an associate editor for social sciences of Twin Research and
Human Genetics and publishes in both social science and medical journals.
Content
List of Figures
About the Authors
Series Editor's Introduction
Acknowledgements
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
References
About the Authors
Series Editor's Introduction
Acknowledgements
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
References