Robustness assessment of regressions using cluster analysis typologies: a bootstrap procedure with application in state sequence analysis.

ABSTRACT:

Background

In standard Sequence Analysis, similar trajectories are clustered together to create a typology of trajectories, which is then often used to evaluate the association between sequence patterns and covariates inside regression models. The sampling uncertainty, which affects both the derivation of the typology and the associated regressions, is typically ignored in this analysis, an oversight that may lead to wrong statistical conclusions. We propose utilising sampling variation to derive new estimates that further inform on the association of interest.

Methods

We introduce a novel procedure to assess the robustness of regression results obtained from the standard analysis. Bootstrap samples are drawn from the data, and for each bootstrap, a new typology replicating

SUBMITTER: Roth L 

PROVIDER: S-EPMC11654397 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature