Structural Equation Modeling
Foundations and Extensions
- David Kaplan - University of Wisconsin - Madison, USA
- the foundations of SEM, including path analysis and factor analysis
- traditional SEM for continuous latent variables, including assumption issues as well as latent growth curve modeling for continuous growth factors
- SEM for categorical latent variables, including latent class analysis, Markov models (latent and mixed latent), and growth mixture modeling.
Through the use of detailed, empirical examples, Kaplan demonstrates how SEM can provide a unique lens on the problems social and behavioural scientists face. The book has been enhanced with certain features that will guide the student and researcher through the foundations and critical assumptions of SEM.
It provides a great foundation to SEM in a way that students will understand
This book is too technical for my students. It is not user friendly.
This is a very up to date guide to structural equation modeling with a good balance of technical statistical aspects and practical applications. In clinical psychology these tools to approach multiple and complex data sets become more and more important.
