Concepts, models and techniques in survival analysis including types of censoring and truncation, Kaplan-Meier estimators, log-rank statistics, parametric models, proportional hazards models, extended PH models, competing risks, recurrent events and frailty models.
Course Objectives
It is intended to provide an analytical foundation and to present current techniques for the statistical analysis of survival data.
General Requirements
Mathematical Statistics I (STA2112H) and II (2212H) or equivalent, taken concurrently or recently; experience using a statistical software package, such as SAS, SPLUS, R and/or STATA.