SEM Episode 4: The Structural Equation Model

In this episode of Office Hours, Patrick combines elements of path analysis and factor analysis to define the general structural equation model. ...
He begins by briefly reviewing path analysis and the assumption of perfect measurement reliability. He then briefly reviews the confirmatory factor analysis model and highlights that latent variables are allowed to covary with one another, but no directed (or structural) relations are estimated. Next, he brings these two concepts together to define the general SEM that allows for manifest variables, latent variables, and regression structures. He describes the six core steps in model building and concludes with some of the challenges faced when defining and evaluating more complex models.
Bollen, K. A. (1989). Structural Equations with Latent Variables John Wiley & Sons New York.
Hoyle, R. H. (Ed.). (2012). Handbook of structural equation modeling. Guilford Press.
Schumacker, R. E., & Lomax, R. G. (2004). A beginner's guide to structural equation modeling. Psychology Press.

[@taehyunalisonlee6766]

Thank you !! :) It is my honor to listen to your lecture at home. Look forward to another amazing ones.

[@dracalys]

Thank you, Prof. Curran. This is really the life-saving office hour!!!

[@ririrustam4991]

You've just saved the life of a stat dummy who's gonna use SEM for her dissertation.. thanks for such concise yet complete explanation!

[@centerstat]

You are so welcome -- thanks for the nice note. If you're truly a glutton for punishment, Dan Bauer and I have a completely free 3-day online workshop on SEM -- see centerstat.org for details.
Good luck with your work -- Patrick

[@dejohnam]

You are single-handedly saving my dissertation

[@centerstat]

ha! what a great comments at the end of a Friday. I'm so glad these might be of some use. Good luck with your work....patrick

[@mikojavier2435]

Thank you. You are clear and concise. You have helped me with my need for further understanding SEM

[@davidz6828]

Great explanation! Thanks for the good work!

[@AElias409]

These videos are amazingly useful - thank you!

[@user-ni4tv6xq7f]

This is great lecture. Thank you for making these videos.
BTW, you look like Buffon, the Italian goalkeeper.

[@anakagung7613]

Multivariate model with latent variables

[@addisugasheneit5944]

Usefull