Yes, multilevel modeling is possible in SEM. See Muthén, B. (1994). Multilevel covariance structure analysis. In J. Hox & I. Kreft (eds.), Multilevel Modeling, a special issue of Sociological Methods & Research, 22, 376-398. You can request this paper from firstname.lastname@example.org.
See Examples 9.6 to 9.11 in the Mplus User's Guide which is available on the website.
robertav posted on Monday, September 03, 2007 - 9:29 am
Dear Authors, I'm carring on a SEM with both continuous and categorical(ordinal) indicators, with 5 continuous latent factors. I have 13428 observation. In order to save time I'm using the WLSMV estimator. How many observation I need to consider the WLSMV a good approximation of the ML estimator? Can you suggest me any reference?
And, as second step of my analysis, I’d like to add a multilevel structure. I have 5 continuous latent factors at the first level. Do you think it is feasible with Mplus? Any hints will be appreciate.
My data were collected for students nested within schools, but my primary interest is to do a single-level SEM model and not multilevel one. However, 7 out of 39 indicators showed significant school-level variance (which implies I need MLM). Since I am not interested in MLM I would like the dependence of the data to be taken into account, but not modeled.
1. Is type=complex appropriate analysis for this?
2. Does it produce the same info in the output as type=missing? I also have some missing data - how to account for that?
3. Do I have to grand-mean center those 7 variables first before using single-level SEM (and eliminate cluster-level variance)?
1. SEM models are typically not "aggregatable" in the sense of Muthen & Satorra (1995), which means that Type = Complex should not be used but instead Type = Twolevel. This happens if factor loadings are not the same on the two levels. I would recommend a simple random intercept twolevel SEM using the analysis steps of
Muthén, B. (1994). Multilevel covariance structure analysis. In J. Hox & I. Kreft (eds.), Multilevel Modeling, a special issue of Sociological Methods & Research, 22, 376-398. (#55)
2. The Mplus Twolevel analysis does do Type = Missing as the default, which uses the standard "MAR" under ML approach - using all available data (often called "FIML").
3. No. And grand-mean centering does not take care of clustering.
You will find a handout about Mplus multilevel factor analysis and SEM on our web site under Mplus Short Courses Topic 7, from the recent course at Johns Hopkins in March. The video of the course will soon be available for free watching on the web.
newuser posted on Monday, January 04, 2010 - 7:43 am
Hi, I am running a multi-level SEM mediation model (2-1-1), the M variable is a second order variable. I have successfully run similar (1-1(second order)-1) models with the same M and Y variables. However, running into problems when I try the (2-1-1) using a higher level X. I am wondering if the second order variable(M)is creating the problem, and if I should reduce it to a first order variable?
Here is how the 2-1-1 model looks %within% Y by y1 y2 y3 M by m1 m2 m3 (second order) M1 by ma mb mc (first order) M2 by md me mf (first order) M3by mg mh mi (first order) X by x1 x2 x3 Y on M %between% X by x1 x2 x3 Yb by y1 y2 y3 Mb by m1 m2 m3 (second order) M1b by ma mb mc (first order) M2b by md me mf (first order) M3b by mg mh mi (first order) Yb on Mb X Mb on X