- Hardcover: 478 pages
- Publisher: John Wiley & Sons; 3rd ed. edition (21 Sept. 2012)
- Language: English
- ISBN-10: 1119978297
- ISBN-13: 978-1119978299
- Product Dimensions: 16 x 2.8 x 23.6 cm
- Amazon Bestsellers Rank: 1,283,694 in Books (See Top 100 in Books)
- See Complete Table of Contents
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
Most Helpful Customer Reviews on Amazon.com (beta)
The book unfortunately proved to be useless and really frustrating for the following reasons:
1. The data sets used for book examples are not available. This means I cannot recreate the results reported to see how it really works in MPlus.
2. It is not clear what version of MPlus the book uses (I see that the book mentions version 5 somewhere in the middle of the text). When I try to use the codes provided in the book using my data set and MPlus version 6, in some cases I am getting an error message, in some cases the output is not provided as it should, according to the book (for example, no standardized results are returned for CFA analysis when I copy the code from p. 43).
3. The book is full (i mean FULL) of typos. To detect some of them, you need to be familiar with matrix algebra.
4. The book contains a lot of distantly relevant material that should be in footnotes at best (like error structure assumptions used in LISREL... seriously, this book is not about LISREL, no need to show off the authors' knowledge of other statistical packages, IMHO).
All in all, this book might be helpful for somebody who already works with SEM/MPlus. For me, it was a waste of money.
Dr. Gabriel Liberman – Data-Graph, Research and Statistical Consulting at: [...] .
Overall, an excellent source for those who wish to learn how to use SEM beyond linear SEM.
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