Comments on: Latent Markov models: a review of the general framework for the analysis of longitudinal data with covariates

Abstract

We heartily congratulate Bartolucci, Farcomeni, and Pennoni for their review of latent Markov (LM) models (Bartolucci et al. 2014). Not only have they provided a succinct and thorough guide that will benefit researchers seeking to employ LM models for many years to come, but they also have offered their suggestions on a number of further developments to extend the basic LM framework that provide direction for future research. In this comment, we would like to pick up on the suggested developments concerningmore flexible temporal structures by highlighting two approaches that have proved useful in related domains; we do not view this as criticism of the proposed LM framework but rather as extensions of the review that are advantageous in terms of parsimony and scalability.