Structural Equation Modeling: Applications Using Mplus (Wiley Series in Probability and Statistics) Hardcover – 21 Sep 2012
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From the Back Cover
A reference guide for applications of SEM using Mplus
Structural Equation Modeling: Applications Using Mplus is intended as both a teaching resource and a reference guide. Written in non–mathematical terms, this book focuses on the conceptual and practical aspects of Structural Equation Modeling (SEM). Basic concepts and examples of various SEM models are demonstrated along with recently developed advanced methods, such as mixture modeling and model–based power analysis and sample size estimate for SEM. The statistical modeling program, Mplus, is also featured and provides researchers with a flexible tool to analyze their data with an easy–to–use interface and graphical displays of data and analysis results.
- Presents a useful reference guide for applications of SEM whilst systematically demonstrating various advanced SEM models, such as multi–group and mixture models using Mplus.
- Discusses and demonstrates various SEM models using both cross–sectional and longitudinal data with both continuous and categorical outcomes.
- Provides step–by–step instructions of model specification and estimation, as well as detail interpretation of Mplus results.
- Explores different methods for sample size estimate and statistical power analysis for SEM.
By following the examples provided in this book, readers will be able to build their own SEM models using Mplus. Teachers, graduate students, and researchers in social sciences and health studies will also benefit from this book.
About the Author
Jichuan Wang, Children’s National Medical Center, The George Washington University, USA
Xiaoqian Wang, Mobley Group Pacific Ltd., P.R. China
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Most Helpful Customer Reviews on Amazon.com (beta)
Overall, an excellent source for those who wish to learn how to use SEM beyond linear SEM.
Dr. Gabriel Liberman – Data-Graph, Research and Statistical Consulting at: [...] .
I found this book to be easy to read. All the concepts were explained clearly. The authors went through several examples and provided the syntax, output, and described the output quite well. I would highly recommend this book for people trying to figure out how to implement their knowledge of SEM in Mplus. If you are new to SEM, I would suggest taking a class or reading Kline first, then reading this book.
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