Module date/time: Tuesday, July 23, 8:30 a.m.-5 p.m.

Censored time-to-event data, where not all subjects experience the event of interest, are common in clinical and epidemiologic research. Examples include randomized controlled trials of therapies for cancer and other chronic diseases, comparative effectiveness research, and epidemiologic cohort studies. This module provides an introduction to censored time-to-event data and classical survival data analysis methods used in biomedical studies.

In this module, we will provide examples of studies where survival analysis is used and where it should not be used.  We will describe how incomplete data on time-to-event outcomes (censoring) occurs.   We will introduce important functions, including the survival function, the hazard function, and the median survival time, and show how censored data can be used to estimate them and compare the time-to-event experience between groups.

The module will explain key concepts unique to survival analysis such as risk sets and informative censoring. It will introduce the Cox regression model, and show how to examine the proportional hazards assumption.

The course will focus on application and understanding the concepts with examples from the biomedical literature; mathematical details will be kept to a minimum.

Access 2018 Course Materials (Links under Assets on right-hand side)