Longitudinal clustering in kinesiology 2: the longclust package in R

Authors

DOI:

https://doi.org/10.63750/rr27aa25

Keywords:

longitudinal clustering, multivariate repeated measures, cluster analysis, longitudinal model-based clustering, R

Abstract

High variation is common in longitudinal kinesiology studies, as participants may respond differently to interventions. In the previous article, implementation of longitudinal k-means in R is used in tandem with repeated measures (multivariate) analysis of variance to understand overall change, and to discover hidden trajectories. The purpose of this article is to demonstrate how to analyze data using model-based clustering. The same synthetic dataset is analyzed,  using the longclust package in R. Comparison with the kml and kml3d packages is discussed.

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Author Biography

  • Keston Lindsay, University of Colorado Colorado Springs

    Helen and Arthur Johnson Beth-El College of Nursing and Health Sciences, University of Colorado Colorado Springs, Colorado Springs, USA

References

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Published

2026-03-31

How to Cite

Lindsay, K. (2026). Longitudinal clustering in kinesiology 2: the longclust package in R. Global Journal of Sport and Exercise Science (GJSES), 2(1). https://doi.org/10.63750/rr27aa25

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