Process / pipelineClinical / epidemiology
Kaplan-Meier Analysis — Nonparametric Survival Estimation
Kaplan-Meier (KM) analysis is a nonparametric method for estimating the survival function from time-to-event data. Introduced by Kaplan and Meier in 1958, it produces the classic step-function survival curve that shows the probability of surviving beyond each observed event time, correctly accounting for censored observations — participants who left the study or had not yet experienced the event by the end of follow-up. It is one of the most widely used techniques in clinical and epidemiological research.
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Sources
- Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI: 10.2307/2281868 ↗
- Kaplan–Meier estimator. Wikipedia. link ↗
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Bayesian Cox Proportional HazardsBayesian Kaplan-Meier analysisCox proportional hazardsMatched Cox Proportional HazardsMatched Kaplan-Meier AnalysisMeta-analytic competing risks analysisMeta-analytic Kaplan-Meier analysisMeta-analytic survival analysisMulticenter Competing Risks AnalysisMulticenter Cox proportional hazardsMulticenter Kaplan-Meier analysisPragmatic Kaplan-Meier analysisPragmatic survival analysisProspective Competing Risks AnalysisProspective Cox proportional hazardsProspective Survival AnalysisRetrospective competing risks analysisRetrospective Cox proportional hazardsRetrospective Kaplan-Meier AnalysisRetrospective survival analysisRisk-adjusted Kaplan-Meier analysisRisk-adjusted survival analysisScreening Test Evaluation