Validating Sequence Analysis Typologies Using Parametric Bootstrap

In this article, the author proposes a methodology for the validation of sequence analysis typologies on the basis of parametric bootstraps following the framework proposed by Hennig and Lin (2015). The method works by comparing the cluster quality of an observed typology with the quality obtained by clustering similar but nonclustered data. The author proposes several models to test the different structuring aspects of the sequences important in life-course research, namely, sequencing, timing, and duration. This strategy allows identifying the key structural aspects captured by the observed typology. The usefulness of the proposed methodology is illustrated through an analysis of professional and coresidence trajectories in Switzerland. The proposed methodology is available in the WeightedCluster R library.

Automated summary

This article proposes a methodology for validating sequence analysis typologies and suggests several models to test important structural aspects of sequences. The effectiveness of the proposed methodology is demonstrated through an analysis of professional and coresidence trajectories in Switzerland.