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Kaplan-Meier-Schätzer×Cox-Proportional-Hazards-Modell×Log-Rank-Test zum Vergleich von Überlebenskurven×
FachgebietStatistikEpidemiologieÜberlebenszeitanalyse
FamilieSurvival analysisProcess / pipelineSurvival analysis
Entstehungsjahr195819721966
UrheberEdward L. Kaplan and Paul MeierSir David Roxbee CoxMantel, N.
TypNonparametric estimatorSemi-parametric regression modelNon-parametric hypothesis test
Wegweisende QuelleKaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. DOI ↗Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170. link ↗
AliasnamenKM estimator, product-limit estimator, Kaplan-Meier curve, survival curve estimatorCox regression, Cox PH model, proportional hazards model, CPHMantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
Verwandt252
ZusammenfassungThe Kaplan-Meier estimator is a nonparametric method for estimating the survival function S(t) — the probability that an individual survives beyond time t — from data that include censored observations. Introduced by Edward L. Kaplan and Paul Meier in their landmark 1958 JASA paper, it is the standard first step in any survival analysis and is among the most-cited statistical methods in biomedical research.The Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research.The log-rank test, developed by Nathan Mantel in 1966, is a non-parametric hypothesis test that compares the overall survival experience of two or more groups throughout the entire follow-up period. It is the standard companion to Kaplan-Meier curves and determines whether observed differences between curves are statistically meaningful.
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ScholarGateMethoden vergleichen: Kaplan-Meier Estimator · Cox proportional hazards · Log-Rank Test. Abgerufen am 2026-06-20 von https://scholargate.app/de/compare