I have a mixture model with 7 variables: three from a single day of data and four from an entire year. I have successfully identified five classes where each of the seven indicator variables were weighted equally.
However, a reviewer noted that I should weight the long-term data more heavily than short-term data. Is there a way to do that in Mplus? In other words, can I make some of the indicator variables "count more" in the model?
To be clear, I am NOT trying to use a complex survey design or sample weights.
I don't see how you can do that. But perhaps you can do a confirmatory LCA with 2 latent class variables - one for the 3 items and one for the 4 items - and see how highly those 2 latent class variables correlate; if highly correlated, the question is moot.