Bsta 514 Statistical Analysis of Time-to-Event Data
This course introduces students to analysis of time-to-event (i.e. survival) data, covering methods for estimation, hypothesis testing, and regression methods for censored data with covariates. Methods widely used in the health sciences are covered, including Kaplan-Meier (empirical) estimate of the survival function and its associated statistical tests. The Cox proportional hazards regression model is presented in detail, along with some extensions of this model. As time allows, other topics will be introduced including parametric survival models, frailty models and/or models incorporating competing risks. Power and sample size computations for time-to-event data will also be introduced. Most assignments will be completed using statistical computing software. Contextualizing results in the context of health sciences problems and research questions is stressed throughout the course.
Prerequisite
A standard pre-calculus course in probability & statistics (e.g. Bsta 511), a course in applied linear regression models (e.g. Bsta 512).