Kaplan-Meier Survival Analysis Explained
2026-05-02 • 8 min
Quick Answer
Kaplan-Meier analysis estimates survival probability over time while handling censored observations. It helps compare treatment groups visually and statistically through log-rank tests. Reliable interpretation requires checking censoring patterns, reporting median survival, and complementing curves with hazard modeling when covariate effects matter.
What Kaplan-Meier Estimates
The curve estimates cumulative survival through observed event times, adjusting risk sets as participants are censored or experience events.
Comparing Groups
Log-rank tests assess survival differences across groups under proportional hazards assumptions. Complement with Cox models when adjusting for covariates.
Reporting Standards
Include median survival, confidence bands, number at risk, and event counts. Explain censoring reasons and follow-up completeness.
Frequently Asked Questions
What does censoring mean in survival analysis?
Censoring means outcome timing is partially known, such as participants lost to follow-up or event-free at study end.
When should I use a Cox model with Kaplan-Meier?
Use Cox regression when you need adjusted hazard estimates for multiple predictors or confounders.