Confirmatory factor analysis in Mplus
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- Опубликовано: 11 сен 2024
- Dr. Christian Geiser shows how to specify a confirmatory factor analysis (CFA) model in the structural equation modeling (SEM) software Mplus.
#Mplus #Mplusforbeginners #statistics #CFA #SEM #geiser #quantfish #statisticstutorials
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Dear Christan, thank you for all your helpful videos.
Thank you for watching! Best, Christian Geiser
Your videos are so helpful! Thank you!!
Thanks so much for watching, Karina.
Your videos are fantastic. Thank you!!!!
Thanks so much for watching! Best, Christian Geiser
great job, sir!
Please share video on how to calculate convergent and divergent validity of binary data using M plus
Thanks for your amazing explanation first :) I could not imagine meeting the author of the book I have referred for learning Mplus by myself 😛
I watched two of your short lectures on CFA and Model Constraint. Still I could not find an answer how I make my syntax when I have negative residual variances.
According to Dr. Muthen, he suggested as following: If the negative residual variances are large, this is a sign that your model is not appropriate for your data and you need to change your model. If they are small, you may want to fix them to zero. Residual variance are often small on the between level of multilevel models.
If residual variance are small, how do I fix them to zero? Is this following command right?
F_1 BY f1 f2 f2 (e1) ! e1 is residual error for f1.
I am very appreciated :)
In my experience, negative residual variances are almost always a sign that something is wrong with your model (model misspecification) or data (e.g., too small a sample). That being said, in multilevel CFA models, there are often good a priori reasons to constrain Level-2 measurement error variances to zero.
In Mplus, error/residual variances can be fixed to zero by specifying the name of the variables and @0. For example:
f by x1 x2;
x1@0; x2@0;
sets the error variances of x1 and x2 to zero.
Hi Christian,
I have a question related to CFA (sorry I have been asking a lot of questions below your videos). Let's say we have 5 variables (A, B, C, D, E) and each is measured by 3 indicators. Is there any difference among the following scenarios: #1 Run five separate CFAs (only 1 latent variable at a time); #2 Run two CFAs with A & B in the first CFA and C & D & E in the second CFA; #3 Run three CFAs with A by itself; B & C in the second CFA and D & E in the third CFA? How do these different scenarios impact the result? The reason I am asking is that I am currently running a study with a relatively small sample size (N = 400). If I put all my latent variables in one model to run CFA (I actually have 8 latent), the sample size doesn't meet the requirement. So I am thinking about running separate CFAs so not a lot of variables in the model at the same time. Thank you VERY MUCH!
This is a complex question to which there is no easy/general answer because the sample size requirements depend on many factors. This would require personal consulting to carefully review your data, variables, model, etc.
Best, Christian Geiser
Great video. Please do a video on Multigroup (i.e gender, SES) Analysis in Mplus.
Thanks for watching! A two-part series of multigroup analysis is in the works. :-) Stay tuned!
sir plz make a video on how to look for identifiers in actual data to improve the model fit..!
Dear Mehvish,
Thank you for your comment! Regarding misfit/model improvement: Have you checked out my videos on model residuals and modification indices?
ruclips.net/video/13Xm07Jf5aA/видео.html
ruclips.net/video/bjwhunQviJ0/видео.html
Those can be helpful for detecting sources of model misfit.
Best, Christian Geiser
In instances where my indicators are dichotomous, do I want to look at the loadings under STDYX, STDY, or STD?
How to conduct multilevel (2 level) CFA in MPLUS, please guide thank you. do we need to specify within and between and two level in syntex for the CFA or it only has to be specified for causal analysis such as in SEM
Yes, you would choose ANALYSIS: TYPE = TWOLEVEL and specify both a within and between level model. For an example, see
statmodel.com/usersguide/chap9/ex9.6.html
Best, Christian Geiser
i only have latent and observed variables in my model, I kept for WIF by Wf1 Wf2 Wf3 in %Within% and kept MR by Mr1 Mr2 under between and ran the analysis. It shows error that your between variable which is MR has variation in cluster. Although I checked the data and there is no variation at between levels of cluster. Do you have any video on TWO level CFA or can you guide me further with this?
Great thank you. I was sweating watching that battery Go from 5% to 4%. Is he going to make it 😂.
Today I learned what the residual variance output was Vs the Rsquared below. (How did I not know this before🤷🏻)
Anything you can teach about missing data in a short video?
Missing data content on the way!
I was sweating too while recording ;-) We have a missing data playlist under "Playlists" now. Best, Christian Geiser