Chapter 13 Survival Analysis
Survival analysis models time to event. Whereas linear regression outcomes are assumed to have a normal distribution, time-to-event outcomes have a Weibull or unknown distribution. Survival analysis models also deal with censoring (unknown starting event and/or ending event). These factors make survival analysis more complicated than linear regression.
Most survival analyses use the
survival package for modeling and the
survminer package for visualization.
A typical survival analysis uses Kaplan-Meier plots to visualize survival curves, log-rank tests to compare survival curves among groups, and Cox proportional hazards regression to describe the effect of variables on survival.
Moore, Dirk F. 2016. Applied Survival Analysis Using R. 1st ed. New York, NY: Springer. https://eohsi.rutgers.edu/eohsi-directory/name/dirk-moore/.