Chapter 7 Survival Analysis

In this chapter, you will learn how to:

• Identify a time-to-event outcome;
• Identify types and mechanisms of censoring;
• Interpret the survival and hazard functions;
• Use the Kaplan-Meier method to estimate the survival function;
• Use the log-rank test to compare survival between groups;
• Visualize the Kaplan-Meier estimate of the survival function;
• Visualize the estimated hazard function;
• Fit a Cox proportional hazards regression model, including the following:
  • Write and interpret the Cox regression equation;
  • Estimate unadjusted and adjusted hazard ratios;
  • Estimate the probability that an event has not yet occurred as of a given time;
  • Estimate the hazard of an event relative to a reference group;
  • Visualize the Cox regression estimate of the survival function;
  • Test interactions between predictors;
  • Incorporate time-varying predictors;
  • Check the proportional hazards assumption;
  • Allow non-proportional hazards using a time interaction or stratification;
  • Check the linearity assumption, examine outliers, and identify influential observations; and
  • Appropriately summarize the methods and results.

To use the code in this chapter, first load the tidyverse and survival (Grambsch and Therneau 2000; T. M. Therneau 2023) packages.

library(tidyverse)
library(survival)

References

———. 2000. Modeling Survival Data: Extending the Cox Model. New York: Springer.

Therneau, Terry M. 2023. Survival: Survival Analysis. https://github.com/therneau/survival.