Thank you for looking at the great video, Dr. Zimermann, it is helpful to understand these statistical techniques. However, such instructions pertinent to Bifactor model, Bi-ESEM model in relation to CFA and EFA are still rare within RUclips, hope for more videos of technical operations using relevant software could happen here in your channel in future. It would be good to adopt these techniques into the practical studies then.
If you are using Mplus, we created a tool to help you generate the syntaxes for ESEM, B-ESEM, and H-ESEM. We also explain everything in the syntaxes that are generated: De Beer, L.T. & Van Zyl, L.E. (2019). ESEM code generator for Mplus. Retrieved from www.surveyhost.co.za/esem/ doi: 10.6084/m9.figshare.8320250
Thank you for this great video, you have an amazing way of explaining such a difficult subject! Could you please make a video on Exploratory Structural Equation Modelling (ESEM) theory and how to run the analysis in R? It's so difficult to find any videos dedicated to ESEM
I have an ESEM video on my list of things to do, but I am not sure when I will get to it because the list of things to do is fairly long. The video, like my other videos, will be about concepts and not how to apply it specifically with any software.
So you have a general factor G that you confirm with a bifactor CFA. How would you calculate a score for G? For example, in your bifactor model at 14:39, how would you estimate somebodies Verbal Intelligence score? I ask because I am interested in estimating these general scores for each person in my dataset, and then adding those estimates as columns in my dataframe. Curious whether you'd take the mean of the total 7 items *or* calculate separate means for Verbal Comprehension and Working memory, add them, and divide by two. Or maybe something else? Great content as always! It's the only content on youtube that really feels like a high quality grad-stats class. I've suggested to other students to look for the guy with the blue hoodie if they are looking for stats enlightenment :)
You can use factor scores or take a mean of all items to get a score for G. However, make sure you understand the challenges in using scores to represent factors: I have a video on factor scores that explains this issue. Whether you take the mean of all items or the mean of two subsets and then a meanwill not make a of these means meaningful difference. This is because taking a mean of all item vs the mean of subscale means approaches are just two different ways of calculating a weighted average. In practice, indicator weights rarely make a difference as long as the items are at least moderately correlated. Thanks for the compliments! These videos are actually a part of my doctoral level course and most of the content is something that I have also presented in class..
Dr Mikko, great video. I am wondering if it is possible to have two "general factors" in a bi-factor model (allowing some items to load on one and the remaining on the other). Or, is only one general factor allowed in a bi-factor model?
In the case of the bifactor model would the expectation be that, if it is indeed a bifactor model, all indicators load into the G factor? What if you fit the model and they do not? How would that be different from a three factor solution?
I would call it a bifactor model even if some of the loadings were small. But if there is not much evidence of a general factor (i.e. loadings are small), then I would conclude that perhaps a bifactor model is not needed. I am not sure if this answers your question.
In a CMV model, factors are allowed to be correlated with one another. However, in a Bi-factor model, factors are not allowed to be correlated with one another.
It is years since I last opened AMOS, but if I remember correctly the correlations between exogenous latent variables are constrained to be zero by default and you need to specifically add correlations if you want to remove this constraint.
SL is a rotation technique that rotates an exploratory factor analysis solution in to a bifactor model. I am talking mostly about confirmatory factor analysis, where researchers specifies and tests a factor solution.
Thank you for looking at the great video, Dr. Zimermann, it is helpful to understand these statistical techniques. However, such instructions pertinent to Bifactor model, Bi-ESEM model in relation to CFA and EFA are still rare within RUclips, hope for more videos of technical operations using relevant software could happen here in your channel in future. It would be good to adopt these techniques into the practical studies then.
@@mronkko So great !!! I will certainly expect them, Have a goo one.
If you are using Mplus, we created a tool to help you generate the syntaxes for ESEM, B-ESEM, and H-ESEM. We also explain everything in the syntaxes that are generated:
De Beer, L.T. & Van Zyl, L.E. (2019). ESEM code generator for Mplus. Retrieved from www.surveyhost.co.za/esem/ doi: 10.6084/m9.figshare.8320250
Thank you for this great video, you have an amazing way of explaining such a difficult subject! Could you please make a video on Exploratory Structural Equation Modelling (ESEM) theory and how to run the analysis in R? It's so difficult to find any videos dedicated to ESEM
I have an ESEM video on my list of things to do, but I am not sure when I will get to it because the list of things to do is fairly long. The video, like my other videos, will be about concepts and not how to apply it specifically with any software.
So you have a general factor G that you confirm with a bifactor CFA. How would you calculate a score for G? For example, in your bifactor model at 14:39, how would you estimate somebodies Verbal Intelligence score? I ask because I am interested in estimating these general scores for each person in my dataset, and then adding those estimates as columns in my dataframe. Curious whether you'd take the mean of the total 7 items *or* calculate separate means for Verbal Comprehension and Working memory, add them, and divide by two. Or maybe something else?
Great content as always! It's the only content on youtube that really feels like a high quality grad-stats class. I've suggested to other students to look for the guy with the blue hoodie if they are looking for stats enlightenment :)
You can use factor scores or take a mean of all items to get a score for G. However, make sure you understand the challenges in using scores to represent factors: I have a video on factor scores that explains this issue. Whether you take the mean of all items or the mean of two subsets and then a meanwill not make a of these means meaningful difference. This is because taking a mean of all item vs the mean of subscale means approaches are just two different ways of calculating a weighted average. In practice, indicator weights rarely make a difference as long as the items are at least moderately correlated.
Thanks for the compliments! These videos are actually a part of my doctoral level course and most of the content is something that I have also presented in class..
Thanks so much. You are my life saver!
Happy to help!
These videos are so good
Thanks!
Dr Mikko, great video. I am wondering if it is possible to have two "general factors" in a bi-factor model (allowing some items to load on one and the remaining on the other). Or, is only one general factor allowed in a bi-factor model?
You can specify that kind of model, but I would not call it a bifactor model.
What software did you use to make this video? Very professional!
Mikko Rönkkö Thanks! Very detailed and it sounds very professional :-)
In the case of the bifactor model would the expectation be that, if it is indeed a bifactor model, all indicators load into the G factor? What if you fit the model and they do not? How would that be different from a three factor solution?
I would call it a bifactor model even if some of the loadings were small. But if there is not much evidence of a general factor (i.e. loadings are small), then I would conclude that perhaps a bifactor model is not needed. I am not sure if this answers your question.
@@mronkko it does, thank you!
thank you
You're welcome
Dr Mikko, in your opinion what is the difference between common method variance models and bi-factor models?
In a CMV model, factors are allowed to be correlated with one another. However, in a Bi-factor model, factors are not allowed to be correlated with one another.
What is the procedure to set the correlations to zero, in AMOS?
It is years since I last opened AMOS, but if I remember correctly the correlations between exogenous latent variables are constrained to be zero by default and you need to specifically add correlations if you want to remove this constraint.
how does this relate to schmid leiman transformation?
SL is a rotation technique that rotates an exploratory factor analysis solution in to a bifactor model. I am talking mostly about confirmatory factor analysis, where researchers specifies and tests a factor solution.