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Structural Equation Modeling: Applications Using Mplus (Wiley Series in Probability and Statistics) Hardcover – 21 Sep 2012

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4.6 out of 5 stars 16 reviews from the U.S.

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Product description

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.

Key features:

  • 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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Amazon.com: 4.6 out of 5 stars 16 reviews
5.0 out of 5 stars Mplus is a wonderful program, but unfortunately it is difficult to use ... 6 July 2015
By Alberto F. Cabrera - Published on Amazon.com
Format: Hardcover Verified Purchase
This book provides an invaluable introduction to using Mplus for estimating latent class analyses. Mplus is a wonderful program, but unfortunately it is difficult to use if one were to rely solely on its manual. In contrast, Jichuan Wang and Xiaoqian Wang provide excellent examples as to how to unlock the potential of this incredible statistical program, while sharing with the reader some important tips for using Mplus for mixture modeling.
5.0 out of 5 stars Excellent book on SEM using Mplus, the best I have seen!! 8 July 2015
By Seungyoung Hwang - Published on Amazon.com
Format: Hardcover Verified Purchase
I decided to buy this book because this is the only book that covers a MIMIC model (Chapter 3.1) and latent transition analysis with a covariate and interaction with latent status at time 1 with two different parameterization approaches (Appendix 6.A).

Highly recommended for those starting out in SEM using Mplus as well as refreshers who need advanced techniques along with theoretical foundations.
3.0 out of 5 stars I understood 16.7% of this textbook. 4 Mar. 2017
By Bryan Tanner - Published on Amazon.com
Format: Hardcover Verified Purchase
Pretty sure this is the only book on this subject. When you've got only option, there's only one choice! :)
4.0 out of 5 stars GREAT 10 April 2014
By John R. Turner - Published on Amazon.com
Format: Hardcover Verified Purchase
This book is an excellent guide to be used in conjunction with with the Mplus user guide. The descriptions about CFA, SEM in this book are as good as any that I have read in other books on CFA and SEM. Good set of examples are provided and a fair overview of interpreting each output is also provided. This would be a great graduate course book for those using Mplus.
5.0 out of 5 stars Great, I love this book! 12 April 2015
By Cheng - Published on Amazon.com
Format: Hardcover Verified Purchase
I enjoy reading this book. It is plain and simple to understand. After reading this book, I can run my SEM model using Mplus easily. I would recommend this book to my colleagues and students.
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