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Structural Equation Modeling: Applications Using MPlus (Wiley Series in Probability and Statistics) [Hardcover]

Jichuan Wang , Xiaoqian Wang

Price: £69.50 & FREE Delivery in the UK. Details
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Book Description

14 Sep 2012 1119978297 978-1119978299 3
A reference guide for applications of SEM using M plus Structural Equation Modeling: Applications Using M plus 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, M plus , 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 M plus . 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 M plus 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 M plus . Teachers, graduate students, and researchers in social sciences and health studies will also benefit from this book.

Frequently Bought Together

Structural Equation Modeling: Applications Using MPlus (Wiley Series in Probability and Statistics) + Structural Equation Modeling with Mplus: Basic Concepts, Applications, and Programming (Multivariate Applications Series) + Data Analysis with Mplus (Methodology in the Social Sciences)
Price For All Three: £122.50

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From the Back Cover

A reference guide for applications of SEM using M plus Structural Equation Modeling: Applications Using M plus 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, M plus , 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 M plus . 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 M plus 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 M plus . 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: 4.5 out of 5 stars  11 reviews
5.0 out of 5 stars Only book that has discussed variables other than continuous! 6 July 2014
By Mash - Published on Amazon.com
Format:Hardcover
The only book on Mplus, which has touched on different variables than just continuous. In the real world it is necessary so for me this was a breath of fresh air. The author has done a good job in explaining concepts I have not found elsewhere. The only drawback is that formative models are not covered and the emphasis is on reflective models. Will look forward to an update, which discusses more details including formative models and how to interpret them.

Overall, an excellent source for those who wish to learn how to use SEM beyond linear SEM.
5.0 out of 5 stars Excelent 10 Jun 2014
By Hugo Cogo Moreira - Published on Amazon.com
Format:Hardcover|Verified Purchase
I do recommend the book (clear, straight to the point, and very applied). Indeed, the author gently provided a prompt answers to emerged issues throughout the reading.
5.0 out of 5 stars Excellent book for understanding Mplus 21 May 2014
By Ross Larsen - Published on Amazon.com
Format:Kindle Edition
I am an assistant professor preparing for an SEM class in Mplus and I have found this book to be the most clear, concise, and accessible of all the books I have looked at. I especially like how thoughtfully the authors have discussed the output and how to understand it. I would recommend this book to anyone who is considering learning Mplus.
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 reference 31 Jan 2014
By Eduwin - Published on Amazon.com
Format:Hardcover
Here I found an "up to date" development of structural equation model, plus the programming using MPlus. This helps me a lot for my work, in particular using Latent Growth Model and Mixture Model in social science research. The examples along with the MPlus codes teach me a lot, not only the basic theory, but to extend the analysis. 5 stars for this book.
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