Comparison of two approaches in multichannel analysis

Sequence analysis is an established approach to study life courses. In this context, multichannel sequence analysis (MSA) and the extended alphabet (EA) approach are the most frequently used strategies when multiple life domains are considered simultaneously. We compare these two methods using real data composed of four life domains. We focus on clustering since sequence analysis usually aims to identify typical patterns in sequences. The analysis is first done on the full dataset. Then, since at least professional status trajectories proved to be different between men and women and, potentially, their link with the other domains, the same analyses are run separately by sex. Finally, two extreme cases of optimal matching, namely Levenstein and Hamming distance, are explored. Neither of the approaches is clearly superior. Indeed, the results of both methods are often close. Although MSA is generally easier to use and applies to a broader range of situations, EA can provide original typologies in some cases.