This course aims to educate students about estimation procedures needed for time to event and other right-censored data.  It will begin with examples of such data and then describe types of censoring and truncation, distributions relevant for time to event data, and assumptions commonly made in conjunction with their analysis.  Students will then learn about estimation techniques for univariate survival curves and common summaries of them such as medians, other quantiles, and restricted means.  The course will then discuss models for multivariate situations with time to event outcomes including those with accelerated life and proportional hazards assumptions.  These will begin by making parametric restrictions which are then relaxed to the nonparametric cases.  Finally, frailty and other models for multivariate outcomes will be described.  The R statistical software package is used throughout the course to analyze survival data examples and enable students, on completing the course, to analyze and interpret real time to event data arising from observational studies, clinical trials, and other sources.

Continuous Assessment: 60%

Examination: 40%

Examination Duration: 3 hours