I am conducting a multi-group CFA (MCFA) in order to evaluate measurement invariance. I'm proceeding in order from equal form to equal factor loadings to equal indicator intercepts, etc. However, I'm unsure that I am correctly programming the MODEL statement in order to test each parameter correctly. I know there are to be two model statements (one general and one specific) for a two group comparison. However, I'm not clear on how you model the two statements and how those statements change to test for different parameter invariance.
Here is some code to test equal factor loadings:
GROUPING IS FR (0=No 1=Yes); ANALYSIS: MODEL=NOMEANSTRUCTURE; INFORMATION=EXPECTED; ESTIMATOR=ML; MODEL: f1 by H1@1*H3*H8*H9*H10*H13*H16*H17; f2 by H2@1*H5*H6*H7*H11*H12; H8 WITH H9; H6 WITH H12; MODEL YES: f1 by H3*H8*H9*H10*H13*H16*H17; f2 by H5*H6*H7*H11*H12; H8 WITH H9; H6 WITH H12;
Is this testing an equal model for yes/no? Can you explain the differences in the MODEL statements when testing for different invariant parameters?
The Topic1 short course handout on the website gives inputs for testing for measurement invariance and population heterogeneity. If the handout is not sufficient, there is also a video available that covers Topic1.