Latent growth models (LGM) and Measurement Invariance with R in lavaan
Workshop given on August 16, 2021 by Johnny Lin, PhD
UCLA OARC IDRE Statistical Consulting
This is the third seminar in a three-part series.
1. Confirmatory Factor Analysis (CFA) in R with lavaan
stats.idre.ucla.edu/r/seminars/rcfa/
The first seminar introduces the confirmatory factor analysis model, and discusses model identification, degrees of freedom and model fit.
2. Introduction to Structural Equation Modeling (SEM) in R with lavaan
stats.idre.ucla.edu/r/seminars/rsem/
The second seminar explores structural equation models which is an umbrella term that encompass linear regression, multivariate regression, path analysis, CFA and structural regression.
3. Latent Growth Models (LGM) and Measurement Invariance with R in lavaan
stats.idre.ucla.edu/r/seminars/lgm/
The third seminar introduces latent growth modeling and how it relates to hierarchical linear models (HLM) and 2) measurement invariance in CFA and how to compare model fit between invariance models.
Пікірлер: 5
You have no idea how USEFUL these seminars have been for my SEM thesis I'm in the midst of writing! So much material relates to mplus, and there is such a dearth of information for lavaan examples, so thank you very much!
you are an amazing instructor!
Thanks for uploading! Such a great help for my current master thesis. Best regards from Germany!
Excellent. Do you have a video for latent variable means comparison please?
Hi, this video was helpfull to my work with SEM. I would like to ask about CFI delta or CFI diff, is it possible to do in a table like a chi comparison? Thanks!!!