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May 10, 2026Open Access

A Bayesian location-scale joint model for time-to-event and multivariate longitudinal data with association based on within-individual variability

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Authors

MPMarco A. PalmaOMOmar El MakkaouiRKRuth H Keogh

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Overview

Randomized trial evaluates association between lung function and mortality in women, indicating improved modeling of health indicators.

Key Points

  • The study aims to develop a Bayesian joint model that evaluates the association between longitudinal data and time-to-event outcomes by addressing the limitations of existing methods.
  • Developed a joint model for time-to-event and multivariate longitudinal data.
  • Employed a mixed-effect location-scale model to analyze longitudinal biomarkers and their within-individual variability.
  • Applied the model on a dataset from the UK cystic fibrosis registry to evaluate associations.
  • Demonstrated improved hazard ratio estimates compared to traditional models due to reduced regression dilution.
  • The joint model effectively quantified within-individual variability, showing significant associations between lung function, malnutrition, and mortality.

Cite This Study

Palma et al. (2026) studied this question.

synapsesocial.com/papers/6a002222c8f74e3340f9d12bhttps://doi.org/10.17863/cam.129980
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