Comparer des méthodes

	Analyse de puissance pour les études de survie	Test du Log-Rank pour la Comparaison des Courbes de Survie
Domaine	Statistique	Analyse de survie
Famille	Hypothesis test	Survival analysis
Année d'origine	1981	1966
Auteur d'origine	—	Mantel, N.
Type	Sample size determination for survival outcomes	Non-parametric hypothesis test
Source fondatrice	Schoenfeld, D. A. (1981). The asymptotic properties of nonparametric tests for comparing survival distributions. Biometrika, 68(1), 316–319.	Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170.
Alias	log-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç Analizi	Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
Apparentées	6	2
Résumé	Power analysis for survival studies determines how many participants — and how many observed events — are required so that a log-rank test or Cox regression has a sufficient probability of detecting a clinically meaningful difference in survival between groups. The foundational formulas were derived by Schoenfeld (1981) and Lachin (1981) and remain the standard approach in clinical trial planning.	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.