GPH-GU 2368
Applied Survival Analysis
This course will provide an introduction to the analysis of survival data, i.e., data subject to incomplete observation due to censoring. Topics include estimation via the Kaplan Meier estimator, comparison of survival data via the log rank and related tests, and regression modeling of survival data using the Cox proportional hazards model and accelerated failure time model. Parametric modeling of survival data will also be covered. Additional topics may include left truncation, competing risks, and multivariate survival data. Examples in Stata, SAS and R will be provided and assignments will involve analysis of survival data.
Topics
- estimation via the Kaplan Meier estimator
- comparison of survival data via the log rank and related tests
- and regression modeling of survival data using the Cox proportional hazards model and accelerated failure time model
Topics explicitly listed in official catalogue description
Sources
- Course catalogue ↗2026-2027