Message/Author 

Anonymous posted on Tuesday, June 07, 2005  8:30 pm



Dear Prof. Muthen I have a question regarding fitting multilevel SEM in mplus. I read the manual and see examples with random factor loadings (in CFA) and random path coefficients (in path analysis). Is it possible using Mplus to fit a multilevel SEM model with random factor loadings and paths between latent variables to be random as well? Thanks a lot. 

bmuthen posted on Wednesday, June 08, 2005  6:55 am



Yes to both. We include examples of that in our annual November Mplus course. But, the computations are heavy and very much so as soon as you have more than a few random coefficients. Random factor loadings is harder because there are many loadings, but perhaps you can hold sets of them equal. Let me know if you have an interesting application. 

Anonymous posted on Thursday, June 09, 2005  3:05 pm



hi Prof. Muthen A followup question, I overlooked and thought the manual has examples on random factor loading but maybe I'm wrong. I tried to use something like (from example 9.9 in manual) and try to include random factor loading (not just random intercept) %WITHIN% s fw by y1y4 but it doesn't work. if I tricked it by:  TITLE: this is an example of a twolevel SEM with continuous factor indicators and a random slope for a factor DATA: FILE IS ex9.10.dat; VARIABLE: NAMES ARE y1y5 w clus; BETWEEN = w; CLUSTER = clus; ANALYSIS: TYPE = TWOLEVEL RANDOM; ALGORITHM = INTEGRATION; INTEGRATION = 10; MODEL: %WITHIN% s y1y5 ON fw; %BETWEEN% y1y5 s ON fb w; OUTPUT: TECH1 TECH8;  Still doesn't work (program complained fw and fb were not defined. How can I fit this manual example to have random factor loadings from f to y1y5? Thanks a lot for your help. 

bmuthen posted on Thursday, June 09, 2005  6:31 pm



You have to first name the factor in a BY statement even if by a dummy statement like f by y1@0; And then do the random slope specification: s1  y1 on f; Note that you have to specify a random slope for each loading that you want to be random. 

Back to top 