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Compositional PLS biplot based on pivoting balances: an application to explore the association between 24-h movement behaviours and adiposity

Author

Listed:
  • Nikola Štefelová

    (Palacký University
    Palacký University)

  • Javier Palarea-Albaladejo

    (University of Girona
    Biomathematics and Statistics Scotland)

  • Karel Hron

    (Palacký University)

  • Aleš Gába

    (Palacký University)

  • Jan Dygrýn

    (Palacký University)

Abstract

Movement behaviour data are compositional in nature, therefore the logratio methodology has been demonstrated appropriate for their statistical analysis. Compositional data can be mapped into the ordinary real space through new sets of variables (orthonormal logratio coordinates) representing balances between the original compositional parts. Geometric rotation between orthonormal logratio coordinates systems can be used to extract relevant information from any of them. We exploit this idea to introduce the concept of pivoting balances, which facilitates the construction and use of interpretable balances according to the purpose of the data analysis. Moreover, graphical representation through ternary diagrams has been ordinarily used to explore time-use compositions consisting of, or being amalgamated into, three parts. Data dimension reduction techniques can however serve well for visualisation and facilitate understanding in the case of larger compositions. We here develop suitable pivoting balance coordinates that in combination with an adapted formulation of compositional partial least squares regression biplots enable meaningful visualisation of more complex time-use patterns and their relationships with an outcome variable. The use and features of the proposed method are illustrated in a study examining the association between movement behaviours and adiposity from a sample of Czech school-aged girls. The results suggest that an adequate strategy for obesity prevention in this group would be to focus on achieving a positive balance of vigorous physical activity in combination with sleep against the other daily behaviours.

Suggested Citation

  • Nikola Štefelová & Javier Palarea-Albaladejo & Karel Hron & Aleš Gába & Jan Dygrýn, 2024. "Compositional PLS biplot based on pivoting balances: an application to explore the association between 24-h movement behaviours and adiposity," Computational Statistics, Springer, vol. 39(2), pages 835-863, April.
  • Handle: RePEc:spr:compst:v:39:y:2024:i:2:d:10.1007_s00180-023-01324-w
    DOI: 10.1007/s00180-023-01324-w
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    References listed on IDEAS

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    1. Jiajia Chen & Xiaoqin Zhang & Karel Hron, 2021. "Partial least squares regression with compositional response variables and covariates," Journal of Applied Statistics, Taylor & Francis Journals, vol. 48(16), pages 3130-3149, December.
    2. Opeoluwa F. Oyedele & Sugnet Lubbe, 2015. "The construction of a partial least-squares biplot," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(11), pages 2449-2460, November.
    3. Peter Filzmoser & Karel Hron, 2019. "Comments on: Compositional data: the sample space and its structure," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 639-643, September.
    4. Mevik, Björn-Helge & Wehrens, Ron, 2007. "The pls Package: Principal Component and Partial Least Squares Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 18(i02).
    5. Juan José Egozcue & Vera Pawlowsky-Glahn, 2019. "Rejoinder on: Compositional data: the sample space and its structure," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 658-663, September.
    6. Nikola Štefelová & Jan Dygrýn & Karel Hron & Aleš Gába & Lukáš Rubín & Javier Palarea-Albaladejo, 2018. "Robust Compositional Analysis of Physical Activity and Sedentary Behaviour Data," IJERPH, MDPI, vol. 15(10), pages 1-18, October.
    7. Dorothea Dumuid & Željko Pedišić & Javier Palarea-Albaladejo & Josep Antoni Martín-Fernández & Karel Hron & Timothy Olds, 2020. "Compositional Data Analysis in Time-Use Epidemiology: What, Why, How," IJERPH, MDPI, vol. 17(7), pages 1-17, March.
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