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 is great book for long. data analysis, I will definitely use this book for my students.
excellent companion to primary book selected.
this book is too difficult for any students
Easy to use text - provides the essentials for researchers who are not primarily methodologists, making it excellent for students.
The text is very technical and difficult for the hons and M level students
Good introductory and advanced text on SEM. Use of R for supplemental analyses is good choice.
The students found it difficult to understand, it is suitable for PhD research or higher
Although the course will be held in English, students wanted some literature to be in German and the book "Strukturgleichungsmodellierung" by Weiber and Mühlhaus was chosen instead.
An excellent, accessible book. The structure is clear, the maths are well explained and progressed throughout the book. With the book it is possible to embark on SEM without floundering.
This is an excellent introduction into Structural Equation Modelling. I liked the historical approach detailing from which ideas SEM actually emerged, which helped in getting the overall idea. Moreover, having studied mathematics, I appreciated the connection that is established between the conceptual ideas behind and the mathematics of SEM. In the end the book helped me to understand SEM beyond the mere use of a software.
