Mplus Version 5 has multilevel EFA. See Examples 4.5 and 4.6 in the Mplus Version 5 User's Guide which is on the website.
EFried posted on Thursday, June 07, 2012 - 7:57 pm
We are running ordinal EFA and CFA using WLSMV estimator to see how many factors to extract. N in this sample =550.
In >15 samples we looked at, we found either 1 or 2 factor solution, fit indices for both solutions being close to good, eigenvalue for third factor <.4 and bad fit.
This sample proves problematic, however.
EFA 1-3: STANDARD ERRORS COULD NOT BE COMPUTED. PROBLEM OCCURRED IN EXPLORATORY FACTOR ANALYSIS WITH 3 FACTOR(S). THE CONDITION NUMBER OF THE ROTATED SOLUTION IS 0.162D-11. THE OPTIMAL ROTATION IS NOT SUFFICIENTLY IDENTIFIED. CHANGING THE ROTATION METHOD MAY RESOLVE THIS PROBLEM.
Eigenvalue for third factor >1 so we're interested to extract it.
CFA: Testing 1 through 3 factor solutions with CFA shows abysmal fit indices, and this warning in 2 and 3 factor solution:
WARNING: THE RESIDUAL COVARIANCE MATRIX (THETA) IS NOT POSITIVE DEFINITE. THIS COULD INDICATE A NEGATIVE VARIANCE/RESIDUAL VARIANCE FOR AN OBSERVED VARIABLE, A CORRELATION GREATER OR EQUAL TO ONE BETWEEN TWO OBSERVED VARIABLES, OR A LINEAR DEPENDENCY AMONG MORE THAN TWO OBSERVED VARIABLES. CHECK THE RESULTS SECTION FOR MORE INFORMATION. PROBLEM INVOLVING VARIABLE PHQ4.
Thank you Linda. Using quartimin in EFA I get the error message that variance for PHQ4 is negative.
Using promax the EFA runs, but the results are bogus. I tried CATPCA in SPSS and checked the data twice (frequencies), there are no problems in the data, and N~500 should also be ok. Again, on the other 15 datasets both the EFA and CFA syntax in MPLUS worked very well.
You are right about the negative residual variance in the CFA. Could you recommend a way to solve this? PHQ4 Undefined 0.22316E+01 -1.232
It's way to large to just fix it to zero. Using a 1 factor solution doesn't fit at all (4 out of 9 items don't even load significantly on the one factor in that case), that's why we're trying to extract 2 or 3 factors.
To constrain residual variances to be positive in EFA, you can use ESEM, label the residual variances, and use Model Constraint to require each to be >0. That, however, may mask an important misspecification such as using too many factors or omitting correlated residuals (which can also be included in ESEM). The ESEM EFA is specified like