Developing and Comparing Structural Equation Models (SEM) in R using lavaan

This video goes over developing SEM models in R. We start with basic measurement models which are similar to EFA, then I go on to test which models have the best fit, and lastly go over how to use SEM models with latent variables to predict measured outcomes.

[@kerstin1912]

I started my homework with pure horror and finished it with a feeling of satisfaction thanks to your explanations. It's actually quite fun digging through those models :-) It really helps that you also take your time interpreting the results!

[@marca7419]

Great video, exactly what I needed right now.
for model 4 I think you mix up outcome and predictor --> Before tilde is outcome, after = predictors

[@PsychEDD]

Thanks for pointing that out!

[@frankantonio4394]

This was a great video. I am an organizational psychologist in the US and I will definitely use this lesson! I look forward to reviewing your previous and upcoming videos.
subscribed and liked!

[@ldsharma6546]

Sir, this is a wonderful video, thank you

[@annmariedunne4495]

Thank you. This video gives a really clear explanation of the process.

[@PsychEDD]

Glad it was helpful!

[@hustlerg451]

Very useful. Thank you.

[@yangyang6008]

Thank you for the tutorial. Can we have access to the dataset in the example?

[@LlewellynVanZyl]

My favourite South African ;-) Thanks for the video!

[@ricardoveiga007]

Thank you for your great content!

[@YTChannel_fun]

Thank you so much for the tutorial. Just a question where I can download the data set.

[@nguyentho9467]

Thanks

[@sajadabdullahpur8513]

Thanks for your video, but I have a problem here.
I am going to run the SEM model by using lavaan function. Before doing the SEM, I used exploratory factor analysis to find out the number of factors, and which variables can be related for each factor. 5 factors were extracted by using the EFA model. As you know, the first step for SEM is to define the model, and this is my problem. Once I try to explain the model according to the following script:
> Model1

[@alessandrocupolo9843]

Hi, great video! do you have any sources to back up the levels of CFI RMSEA and SRMR that you suggest? I am writing a thesis and need to justify my model : )

[@PsychEDD]

Here are a few good ones:
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
Schumacker, R. E., and Lomax, R. G. (2004). A beginner's guide to structural equation modeling, Second edition. Mahwah, NJ: Lawrence Erlbaum Associates.

[@chiaras2274]

When you use it to estimate a mediation model, should you exclude some of the covariates from one of the two equations?

[@PsychEDD]

If there is a strong rationale to include covariates, they should probably not be excluded.

[@chiaras2274]

@@PsychEDD using lavaan though i get an error that says that the model is not identified, Do you have some suggestions?

[@PsychEDD]

Hard to say without looking at the code/data and I don't frequently use mediation models (more of a moderator type of person) - i'd recommend just having a look through the syntax on the lavaan tutorial site to see if there is perhaps something you've missed: lavaan.ugent.be/tutorial/sem.html

[@sourabhsharma9830]

Hi, could you please also share tje glimpse of data or questionnaire? It will be more clear to grasp the analysis if we can see the data and how it was collected.

[@PsychEDD]

The data were all scored Likert scale responses if I remember correctly.

[@alwaysbanan]

I have a question! I'm wondering why the first observed variables under each latent variable in the summary don't have standard error or p-values? I have the same issue for my model!

[@PsychEDD]

If i remember correctly, it's because all other observed variables are 'weighted' against that initial variable - ideally, the weighted variable has some theoretical reasoning for being selected as the weight - i.e., the most valid score, or a specific reference category.

[@Cjstistajh]

I wonder what if it’s a non recursive model?

[@roiad876]

Can you make a video on higher order latent variable models?

[@PsychEDD]

Sure, I can have a look at that

[@hooldhooldy4766]

Great vidoe, please could you share the codes

[@bayuhasmamawhailu1407]

1

[@PsychEDD]

2

[@TheCyberklutz]

Unfortunately your video quality is terrible. Can't see any of the code. Learn to zoom in when walking through specific sections.

[@PsychEDD]

*shrug* - i didn't account for potato resolution viewing