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A flexible link for joint modelling longitudinal and survival data accounting for individual longitudinal heterogeneity

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  • Rui Martins

    (Universidade de Lisboa)

Abstract

This work aims at jointly modelling longitudinal and survival HIV data by considering the sharing of a set of parameters of interest. For the CD4 longitudinal stochastic process we propose a regression model where individual heterogeneity is allowed to vary in terms of the mean and the variance, relaxing the usual assumption of a common variance for the longitudinal residuals. Along, we will be considering a hazard regression model to analyse the time between HIV/AIDS diagnostic and death. For introducing enough flexibility in the structure linking the longitudinal and survival processes, we consider time-varying coefficients. That is achieved using Penalized Splines and allows the relationship to vary in time. The CD4 residuals standard deviation is considered as a covariate in the hazard model, thus enabling to study the effect of the CD4 counts’ stability on the survival. The proposed framework surpasses the performance of the most “traditional” joint models, which generally consider a common variance and a time-invariant link.

Suggested Citation

  • Rui Martins, 2022. "A flexible link for joint modelling longitudinal and survival data accounting for individual longitudinal heterogeneity," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(1), pages 41-61, March.
    • Handle: RePEc:spr:stmapp:v:31:y:2022:i:1:d:10.1007_s10260-021-00566-6
    DOI: 10.1007/s10260-021-00566-6
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    Cited by:

    1. Murray, James & Philipson, Pete, 2023. "Fast estimation for generalised multivariate joint models using an approximate EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).

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