I'm using Stata 15. I have four continuous and normally distributed variables, which I'll call y, x1, x2, and x3. 20% of the cases have missing values on x3, and I suspect missingness is MAR. I'd like to fit a regression model using FIML, i.e.,
This part isn't a problem. The problem is, after fitting the model, I'd like to use the -margins- command to obtain predictive margins, i.e.,
When I do so, margins defaults to the subset of cases with non-missing values, producing what I believe to be biased estimates. I suspect there's no way around this issue, but I thought I'd ask here in case anyone has ideas on how to proceed.
Thanks in advance,
IYH
Code:
sem(y <- x1 x2 x3), method(mlmv)
Code:
margins, at(x3=(50(10)50))
Thanks in advance,
IYH
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