Using a multigroup model, I am testing invariance across two groups where
3 items are shared 2 items are assessed only for Group 1 3 items are assessed only for Group 2
I obviously am only interested in the invariance for the shared items, but want the latent construct to be informed by the additional info available in both groups.
Is there a workaround for this? Mplus does not like items to be missing for everyone in a group.
My current workaround is to generate random values from a N(0,1) for the missing items and fix the loading to 0, intercept to 0, residual variance to 1 for those items. Not sure if this makes sense or not.
I am interested in loadings and the factor variance in addition to means and intercepts, so the MIMIC model is not a good option.
There is a FAQ called Different number of variables in different groups" that suggests what to do. Another approach is to use Type=Mixture, letting the groups be represented by Knownclass.
Jen posted on Wednesday, April 16, 2014 - 11:41 am
Thank you for referring me to that note. TYPE=MIXTURE seems problematic because of the lack of fit indices, but with continuous outcomes, setting the residual variances to .0001 (along with supplying some starting values) seemed to work well.
I wondered if you had any suggestion about what to do when the variables missing in one group are ordinal (resulting in a "less than two categories" warning). Do I do something with the thresholds?