Bayes-Pharma 2017

The Bayes Pharma conference focus on Bayesian approaches in pharmaceutical research.

Co-organized by VaBaR member Virgilio Gómez-Rubio, this year’s edition features a short course on Bayesian Survival Models by

Carmen Armero
Universitat de València, Spain

Elena Lázaro
Universitat de València, Spain

Survival analysis is one of the most important areas of applied and theoretical research in Statistics, with many important contributions in life sciences. This small course focuses on Bayesian reasoning in survival models. It contains the most basic elements and procedures in the subject without a strong theoretical approach but a conceptual and applied perspective that enables comprehensive modeling. Topics will be illustrated by means of real studies that will be subsequently worked with more depth in practical sessions.

Programme

1. Introduction.

2. Basic statistical concepts: survival function, hazard rate, censoring and truncation.

3. Time-to-event regression models: accelerated failure models and proportional hazards (Cox) models.

4. Frailty models.

5. Cure rate models.

6. Joint models of longitudinal and survival data.

Bibliography

R. Christensen, W.O. Johnson, A. J. Branscum and T. E. Hanson (2011). Bayesian Ideas and Data Analysis. Boca Raton: Chapman and Hall.

J. G. Ibrahim, M.-H. Chen, and D. Sinha (2001). Bayesian Survival Analysis. New York: Springer

J. P. Klein and M. L. Moeschberger (2003). Survival Analysis: Techniques for Censored and Truncated Data. Second Edition. New York: Springer-Verlag