Is it possible to do conditional logistic regression in MPlus? I'm analysing an individually matched case-control study and need to account for the matching.
Before extending the model to add in possible mediators, I'm trying to simply replicate a conditional logistic regression which I first fitted in Stata.
The WinBUGS manual gives me an idea: conditional logistic regression is equivalent to a standard logistic regression with fixed effect intercepts that are specific to each pair. So e.g. in Stata clogit case_control x, strata(id) gives exactly the same results as poisson case_control i.id x where case_control = 1 if case, 0 if control, x is some covariate and id = an id number specific to the pair.
But is there any way that I can force MPlus to do a Poisson regression instead of logistic when it sees a 0/1 outcome?
An alternative trick (also in the WinBUGS manual) is to do a standard logistic regression of a vector of 1's on the DIFFERENCE in covariate values between cases and controls. But if taking differences like this then I don't think it'd be possible to later add in possible mediators.
However, for the trick to work, I need a fixed intercept in the Poisson model specific to each of 432 case-control pairs. So I tried regressing my (Poisson) case control indicator on the variable ID, telling MPlus that ID is a categorical variable.
I then get the error message "Categorical variable ID contains 432 categories. This exceeds the maximum allowed of 10."