Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse de Kaplan-Meier× | Test du Log-Rank pour la Comparaison des Courbes de Survie× | |
|---|---|---|
| Domaine≠ | Épidémiologie | Analyse de survie |
| Famille≠ | Process / pipeline | Survival analysis |
| Année d'origine≠ | 1958 | 1966 |
| Auteur d'origine≠ | Edward L. Kaplan and Paul Meier | Mantel, N. |
| Type≠ | Nonparametric survival estimator | Non-parametric hypothesis test |
| Source fondatrice≠ | Kaplan, 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 ↗ |
| Alias | KM analysis, KM estimator, product-limit estimator, Kaplan-Meier curve | Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi |
| Apparentées≠ | 5 | 2 |
| 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. | 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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