Survival Analysis, Censoring and Time Scales

Survival analysis or time-to-event analyses have been popularized for making predictions about future events based on some exposure in the past. The methods are familiar to epidemiologists but also to actuarial scientists / insurance companies to estimate risk.

This presentation will give a quick overview of Cox proportional hazard models, covering the assumption of independence of censoring, as well as ways to address the lack of independence using inverse probability censor weighting. It will go into detail about what censoring entails, and how left-, right-, and interval-censoring relate to the observation window. Methods of addressing left and right censored events will be discussed by exploring the benefits of changing the time scale of investigation.

Some examples and cautionary tales from the literature will be highlighted. Sample code from SAS, R and (possibly) Stata will be provided.