

Scalar Invariance Testing 

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Dear Bengt and Linda: I have been running metric invariance models (with continuous indicators and latent variables) in Mplus for years, but I'm having trouble with scalar (intercept) invariance. From what I understand, in a multiplegroup model, factor loadings are constrained like this: f BY y1 y2 y3; y1 (1); y2 (2); y3 (3); And shouldn't intercepts be constrained like this: [y1] (4); [y2] (5); [y3] (6); However, that doesn't work. I get the SAME EXACT fit indices with intercept constraints imposed as I do without these constraints. And if I try it this way, I get an unidentifed model: MODEL WHITE: [y1]; [y2]; [y3]; MODEL BLACK: [y1]; [y2]; [y3]; What am I doing wrong? Thanks very much. Seth 


Please see the inputs under multiple group analysis in the Topic 1 course handout. The default in Mplus is to constrain the intercepts and factor loadings across groups. 


Hello, I learned that when testing for scalar invariance, on top of constraining the intercept to be equal across groups, one should also set the means of errors to be zero in all groups. Is this true, or is this your practice, Dr. Muthen? Aren't means of errors ALWAYS zero? Is this just some programming convention that SEM people do to make sure that the general rule that "means of errors are zero" does indeed hold in estimation? Have you ever heard of this programming technique? Thank you, Lisa 


As a followup question, Dr. Muthen: Is it even possible to set means of errors for measured variables to zero in Mplus? Would this be some sort of unusual modeling? 


Means of residuals are not parameters in the model. They cannot be fixed at zero. They are zero. 


Thank you! I agree. 

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