Confirmatory Factor Analysis in R with lavaan

UCLA Office of Advanced Research Computing (OARC)

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Confirmatory Factor Analysis in R with lavaan workshop given at UCLA on May 17, 2021 by Johnny Lin, Ph.D.
This is the first seminar in a three-part series.
1. Confirmatory Factor Analysis (CFA) in R with lavaan
stats.idre.ucla.edu/r/seminar...
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/seminar...
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/seminar...
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.

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3 июн 2021

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Комментарии : 27

@sixzero7445 8 месяцев назад

Still can't believe this is free to watch for everyone. Thank you so much.

@AogNubJoshh 2 года назад

Dr Lin, you are an exceptional teacher. I have found many sources to explain CFA in a very inaccessible way. Here, you have explained CFA in an accessible way to those new to CFA, and made it free for all to benefit from. Thank you!

@j83lin 2 года назад

You're welcome Josh. Glad you enjoyed the content.

@RRL0402 9 месяцев назад

This is the resource I needed for my Dissertation. As someone with no strong stat and R background, this really helped me. Thank you very much Dr. Lin!

@jakeoblockm Год назад

Wow, this was an absolute lifesaver. Such a complex topic, presented so simply and clearly, and freely available on RU-vid. I definitely owe you a beer. Thank you so much!

@Jjlafa 2 года назад

This is, hands down, the most accessible explanation of CFA I have seen/read. Thank you SO much!

@j83lin 2 года назад

You're welcome! Thanks for watching!

@n3Toii 2 года назад

The most useful source I've found for my thesis, thank you!

@margaultsacre2744 2 года назад

Best video on CFA ever. I understood almost everything. Thank you.

@barbarawaloszek7317 Год назад

Hei, I really wanted to say THANK YOU. This video really helped out with CFA. And I have never learnt about it before! You excel as an educator!

@mustafanasiri6247 8 месяцев назад

Thank you very much for an excellent lecture on CFA. Just a small comment/correction on the very final exercise: the Test statistic for the User Model, is 554.191. In your solution, it is 562.790. and the Degree of Freedom is 20, not 21. By putting these numbers in the formula, we get the correct CFI, which is 0.871 (rounded).

@sivaratnakumari570 2 года назад

I am very grateful to you for clearly explaining with all the details. Thank you so much. Stay blessed!

@user-ub9wr6vo3m Год назад

These videos are fantastic. Thank you!

@arturocdb 2 года назад

Thank you doctor Lin, really a simple explanation its very important…, you did it excellent!…

@Abhorsenification 2 года назад

This is awesome, thank you!

@rafaelpentiadopoerschke2681 2 года назад

great job mah man

@grungehead12 Год назад

Thank you for this beautiful explanation! You have made my life so much easier! Quick question, do you think the poor fit (as indicated by the fit indices) was due to the fact that some items were not reverse-coded?

@will74lsn 5 месяцев назад

great video! Thanks. What do you think of using the estimation method DWLS instead of ML for ordinal items (such as those in the video "strongly disagree to strongly agree")? I have just read a paper (Reimann et al. 2024) where they used DWLS in a 2-factor CFA and got a great RMSEA (0.01). Their rationale was that the responses are ordinal and not continuous. Interestingly, I could run the same data set with ML and got an RMSEA = 0.13. Obviously a big difference. In papers, authors often do not even mention their estimation method.

@hamidshams2926 2 года назад

Thank you for the great seminar. Would you please tell me where I can find materials about the following items:Two-item factor analysis Uncorrelated factor analysis with two items

@anunieminen1553 2 года назад

Hello, thank you for the video. Very insightful. Please, how can I get factor scores for the latent factors?

@a.sparkle5157 Год назад

Really great lecture! It helped me a lot with writing my thesis. One question though: If you use your full data, what is the default calculation running in the background? Does lavaan calculate a covariance matrix or a correlation matrix? Thank you :)

@fatematuzzahrasaqui2732 Год назад

Dr. Lin, is there any video on your seminar on EFA?

@nickmillican22 2 года назад

Is the advanced seminar available online?

@m...7570 Год назад

Thank you for this video. I followed the steps but I got an error message "covariance matrix of latent variables is not positive definite". There aren't any negative values in the covariance matrix though and also not in the correlation matrix. Grateful for any help to fix this issue.