Stata's new estimation command xtmlogit fits panel-data multinomial logit (MNL) models to categorical outcomes observed over time. Suppose that we have data on choices of restaurants from individuals collected over several weeks. Restaurant choices are categorical outcomes that have no natural ordering, so we could use the existing mlogit command (with cluster–robust standard errors). But xtmlogit models individual characteristics directly and thus may produce more efficient results. And it can properly account for characteristics that might be correlated with covariates.