Classifying life course trajectories: a comparison of latent class and sequence analysis

Nicola Barban, Università Bocconi
Francesco C. Billari, Università Bocconi

In this article we compare two techniques that are widely used in the analysis of life course trajectories, i.e. latent class analysis (LCA) and sequence analysis (SA). In particular, we focus on the use of these techniques as devices to obtain classes of individual life course trajectories. We first compare the consistency of the clas- sification obtained via the two techniques using an actual dataset on the life course trajectories of young adults. Then, we adopt a simulation approach to measure the ability of these two methods to correctly classify groups of life course trajecto- ries when specific forms of “random” variability are introduced within pre-specified classes in an artificial datasets. In order to do so, we introduce simulation opera- tors that have a life course and/or observational meaning. Our results contribute on the one hand to outline the usefulness and robustness of findings based on the classification of life course trajectories through LCA and SA, on the other hand to illuminate on the potential pitfalls of actual applications of these techniques.