Victor Medina-Olivares Headshot

Research Topic

Bayesian Joint Models for Longitudinal and Survival Data
@vmedina Twitter

Research Summary

The inclusion of time-varying covariates into survival analysis has led to better predictions of the time to default in credit scoring models. When these time-varying covariates strictly depend on the debtor (internal), the estimation of the survival model can be biased if the time to default is not jointly estimated with the internal time-varying covariates, obtaining less accurate predictions. Joint models for longitudinal and survival data are a suitable framework to jointly model the survival time and the internal time-varying covariates.

Research Area


  • MSc Statistics and Operational Research
  • Industrial Engineer
  • BSc Engineering Sciences
  • BSc Physics