Data-Graph

by Jichuan Wang
 

I highly recommend this book 

I have just finished reading "Structural Equation Modeling" by Wang and Wang. I found that the book contributed greatly to my knowledge of SEM. As a person who has worked with SEM for years and supports many studies, this book advanced my knowledge, allows me to get much deeper into complex SEM and allows me to utilize the most advance modeling techniques. First, the book provides a clear introduction on the mathematics and the algebra of SEM with helpful examples of graphical illustrations and the matrix algebra that generates these models. This is, of course, not the focus of the book, but offers a background for the modeling examples. Then, the authors explain how to use different measurements for goodness of fit and quality of the model. They also discuss situations in which  these measurements exceed the expected range and how to treat such cases. I use the Mplus examples and they save me the time usually necessary for experimenting with the program before building the final model. Beyond these advantages, in my experience I receive immediate and clear answers when directly asking the authors more complex questions on topics which do not appear in the book. I recommend the book warmly both for those who would like to get into SEM and those who are already into SEM but would like to go further with this statistical technique.

Among the topics of the book are: measurement model, confirmatory factor analysis, latent variables, latent clusters in growth models, multi-group analysis, and sample size for structural equation models.

Dr. Gabriel Liberman – Data-Graph Statistical Consulting 

Link to Amazon