Structural Equation Modeling: Applications Using Mplus (Wiley Series in Probability and Statistics)

by Jichuan Wang
 

I recommend the book warmly

I have just finished reading "Structural Equation Modeling" by Wang and Wang. I find the book extremely contributing to my knowledge of SEM. As a person who works with SEM for years and supports many studies and researches, this book advances my knowledge and allows me to get much deeper into complex SEM and puts me in the most advance modeling techniques. First, the book provides 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 only stands at the back of modeling examples. Then, the authors explain how to use different measurements for goodness of fit and quality of the model. They also discuss events when these measurements exceed the expected range and how to treat such cases. I am using the Mplus examples and they save time usually necessary for experimenting with the program before building the final model. Beyond these advantages, my experience with directly asking the authors more complex questions on topics which do not appear in the book, receives immediate clear answers. I recommend the book warmly for those who'd like to get into SEM and those who 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