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1)The items I am using for model identification and selection in my LCA have no missing values. Unfortunately, the variables I want to use for covariates have about 20% to 30% missing. What would you recommend I do in this case? Obviously when then attempting to add covariates, the gamma and rho estimates change from the initial model identification. I have a nice sample of about 1100 future teachers. I’m afraid if I go back and drop observations with missing values across the covariates, I’ll lose a huge portion of my data.
2) If I am able to get that resolved, is there a way I could ask “Conditional on [some covariates], does class membership predict [some outcome]?
I believe the outcomes I am thinking about also have missing issues at about the same percentage as above |
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| Try Auxiliary R3STEP. It doesn't resolve the missing on covariates issue but at least the covariates - and the lowered sample size their missingness causes - don't affect the class formation. |
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