Live sessions will be held 8:30-noon, PT (11:30-3 p.m. ET) each day. Pre-recorded lectures, downloadable presentations, data sets and other course materials will be posted prior to the start of the module.

Censored time-to-event data, where not all subjects experience the event of interest, are common in biomedical research. This module introduces some essential statistical tools for analyzing censored time-to-event data and emphasizes methods for clinical trials. The module will:

• Introduce important functions, including survival curves, the hazard function, and the median survival time, in analyses of time-to-event data;
• Review life-table analysis, and introduce one-sample Kaplan-Meier estimation of survival curves;
• Introduce the two-sample log-rank test, and alternative testing procedures that weight group comparisons differently over the follow-up time interval;
• Introduce the Cox proportional hazards model for regression analysis of the association between an explanatory variable and a censored event-data outcome;
• Describe how information is accrued when there is group-sequential monitoring of a clinical trial, and
• Describe power and sample size calculation for a clinical trial with censored time-to-event outcomes;
• Discuss other topics, such as competing risks and biased sampling, arising from observational studies, if time permits.

The course will focus on application and understanding the concepts with examples from the literature; mathematical details will be kept to a minimum.  Working knowledge of basic probability and statistical concepts will be assumed.