Comparer des méthodes

	Analyse de Kaplan-Meier	Étude de cohorte
Domaine	Épidémiologie	Épidémiologie
Famille	Process / pipeline	Process / pipeline
Année d'origine	1958	Mid-20th century (formal epidemiological design codified ~1950s)
Auteur d'origine	Edward L. Kaplan and Paul Meier	Doll & Hill (British Doctors Study, 1951); Snow (cholera, 1854)
Type	Nonparametric survival estimator	Observational longitudinal study design
Source fondatrice	Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481.	Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641
Alias	KM analysis, KM estimator, product-limit estimator, Kaplan-Meier curve	longitudinal study, follow-up study, panel study, incidence study
Apparentées	5	6
Résumé	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.	A cohort study assembles a group of individuals who share a common starting point — typically freedom from the outcome of interest — and follows them over time to observe who develops the outcome. By comparing incidence rates between exposed and unexposed subgroups, researchers can estimate relative risk and absolute risk differences. Cohort studies are the gold-standard observational design for measuring disease incidence and establishing temporal relationships between exposure and outcome.