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.
Terry M. Therneau, and Patricia M. Grambsch. 2000. Modeling Survival Data: Extending the Cox Model. New York: Springer.
Therneau, Terry M. 2023. Survival: Survival Analysis. https://github.com/therneau/survival.