I am trying to model the selection of panel members from a bench of judges, where the number of choices is assumed to be fixed in advance. (In my application, it is common to pick five or seven judges from a bench of 12).
I am using (time-varying and case-specific) variables measured on the different judges to explain their selection.
I have seen other authors use conditional logit models to assess the effects of judge-specific variables.
However, the conditional logit model does not seem appropriate for cases where multiple choices must be made without replacement.
In simulations that I have carried out, I can recover known coefficients using the mclogit package in R when only one choice is made.
However, when the top two choices are chosen, the estimated coefficients are much, much smaller than their known values.
I therefore wanted to know:
- Am I right to think that the conditional logit model is inappropriate in situations of this type?
- What would be an appropriate model for the situation I have described?
- How (ideally) might it be estimated in R?