1 citations · 1 across the 6 of their papers we have counts for
8 papers · 1 filter
Bayesian Causal Machine Learning for Cure Models
Antonio R. Linero, F. Javier Rubio, Piyali Basak
In survival studies, treatments can benefit patients through different mechanisms: a treatment may increase the probability of being cured or delay failure among patients who are n…
On harmonic oscillator hazard functions
J. A. Christen, F. J. Rubio
We propose a parametric hazard model obtained by enforcing positivity in the damped harmonic oscillator. The resulting model has closed-form hazard and cumulative hazard functions,…
Dynamic survival analysis: modelling the hazard function via ordinary differential equations
J. A. Christen, F. J. Rubio
The hazard function represents one of the main quantities of interest in the analysis of survival data. We propose a general approach for parametrically modelling the dynamics of t…
Extended Excess Hazard Models for Spatially Dependent Survival Data
André Victor Ribeiro Amaral, Francisco Javier Rubio, Manuela Quaresma +2
Relative survival represents the preferred framework for the analysis of population cancer survival data. The aim is to model the survival probability associated to cancer in the a…
MEGH: A parametric class of general hazard models for clustered survival data
Rubio, F. J., Drikvandi +1
In many applications of survival data analysis, the individuals are treated in different medical centres or belong to different clusters defined by geographical or administrative r…
A Unifying Framework for Flexible Excess Hazard Modeling with Applications in Cancer Epidemiology
A. Eletti, G. Marra, M. Quaresma +2
Excess hazard modeling is one of the main tools in population-based cancer survival research. Indeed, this setting allows for direct modeling of the survival due to cancer even in…