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Anyway, my issue is that I use the predicted probabilities to compute choice probabilities across alternatives in another dataset under different assumptions on the process consumers follow to select alternatives. I compare the individual LL for each choice process and then assign consumers to different types depending on the choice process that maximises their LL.
My issue is therefore that the individual LL I compute using the predicted probabilities from the mixlogit model are not correct. To drive the point further, it is not even useful for me to use gmnlpred of the gmnl command, by Gu, Hole and Knox (forthcoming in Stata Journal, available here: http://www.shef.ac.uk/economics/people/hole/stata.html), and compute the individual log-likelihood with it, because it will not be possible for me to compute similarly the individual log likelihood on the other dataset.
My question is then, should I therefore use the predicted probabilities from mixlogit with the panel specification rather than without the panel specification, just because the reported AIC of panel mixlogit is better? Or should I prefer the predicted probabilities from the non-panel version since the individual likelihood I would be calculating from this would at least be correct?
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