Section outline

  • In Block 4 we focus on survival analysis, where time to event is the primary outcome. We will introduce core survival analysis techniques, beginning with the intuitive Kaplan-Meier (KM) curve, a non-parametric method for visualizing and estimating the survival probability over time.

    Then, we will delve into the Cox Proportional Hazards model, a powerful and widely used semi-parametric regression technique that allows us to investigate the influence of multiple covariates on the hazard rate. 

    Furthermore, we will introduce the concept of competing risks, situations where individuals are at risk of experiencing "first" multiple distinct events, and understanding how to properly analyze such data is crucial for obtaining unbiased estimates.

    Finally, we will touch upon the performance evaluation of estimated survival models, exploring metrics and approaches to assess how well our models fit the data and how reliably they can predict future event times.