A hierarchical INLA approach decomposes non-linear biomarker scaling in joint longitudinal-survival models into a parametric baseline and data-driven smooth deviation via second-order random walk basis, enabling fast inference and linearity checks.
Journal of the Royal Statistical Society Series C: Applied Statistics , volume=
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Efficient Bayesian inference for non-linear association structures in joint models: A hierarchical approach via INLA
A hierarchical INLA approach decomposes non-linear biomarker scaling in joint longitudinal-survival models into a parametric baseline and data-driven smooth deviation via second-order random walk basis, enabling fast inference and linearity checks.