Survival Analysis and Censored Data

Abstract: This seminar introduces the key concepts and methods of survival analysis. We begin by discussing the nature of survival (or time-to-event) data and the complications introduced by censoring - when the event of interest has not occurred for some subjects by study end or loss to follow-up. The talk then presents classical and modern tools for analyzing such data: we will cover the nonparametric estimation of survival curves (via the Kaplan-Meier estimator), compare survival experiences with the Log-Rank test, and introduce regression models for survival outcomes - in particular, the Cox proportional hazards model (hazard-based modeling), including discussion of the hazard function and handling of covariates. The talk also touches on more advanced considerations such as shrinkage for Cox models, time-dependent covariates, and diagnostic checks (e.g., verifying the proportional hazards assumption).

Computer scienceMathematics

Audience: general audience

Basic Notions and Applied Topology Seminar