Salīdzināt metodes

	Jaudas analīze izdzīvošanas pētījumiem	Log-rank tests salīdzināšanai izdzīvošanas līknēm
Nozare	Statistika	Dzīvildze
Saime	Hypothesis test	Survival analysis
Izcelsmes gads	1981	1966
Autors	—	Mantel, N.
Tips	Sample size determination for survival outcomes	Non-parametric hypothesis test
Pirmavots	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.
Citi nosaukumi	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
Saistītās	6	2
Kopsavilkums	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.