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Análisis de Kaplan-Meier×Prueba Log-Rank para Comparar Curvas de Supervivencia×
CampoEpidemiologíaSupervivencia
FamiliaProcess / pipelineSurvival analysis
Año de origen19581966
Autor originalEdward L. Kaplan and Paul MeierMantel, N.
TipoNonparametric survival estimatorNon-parametric hypothesis test
Fuente seminalKaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. 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 ↗
AliasKM analysis, KM estimator, product-limit estimator, Kaplan-Meier curveMantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
Relacionados52
ResumenKaplan-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.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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ScholarGateComparar métodos: Kaplan-Meier Analysis · Log-Rank Test. Recuperado el 2026-06-18 de https://scholargate.app/es/compare