This paper reviews several “recent” advances in in modeling choice data that can estimates currently available software. The focus will be in two veins of thought: models that capture the heterogeneity in the consideration sets of respondents and advances in the field of latent class choice models. A few include MNL model using conjunctive screening rules; simultaneously performing a latent class choice model with choice and non-choice data; and tree based latent class choice models.
