4 papers
Informative Distance-Based Priors for Correlation Matrices Centred on a Target Reference
Anna Freni-Sterrantino, Janet van Niekerk, Elias Teixeira Krainski +3
Specifying a prior over the space of correlation matrices is a persistent challenge in Bayesian analysis. The space is a curved manifold whose dimension grows quadratically with th…
Efficient Bayesian inference for non-linear association structures in joint models: A hierarchical approach via INLA
Denis Rustand, HÃ¥vard Rue, Lisa Le Gall +1
Joint models for longitudinal and time-to-event data are increasingly used in health research to characterize the association between biomarker trajectories and the risk of clinica…
A new approach for Bayesian joint modeling of longitudinal and cure-survival outcomes using the defective Gompertz distribution
Dionisio Silva Neto, Denis Rustand, Haavard Rue +2
In recent medical studies, the combination of longitudinal measurements with time-to-event data has increased the demand for more sophisticated models without unbiased estimates. J…
A graphical framework for interpretable correlation matrix models
Anna Freni Sterrantino, Denis Rustand, Janet van Niekerk +2
In this work, we present a new approach for constructing models for correlation matrices with a user-defined graphical structure. The graphical structure makes correlation matrices…