Methoden vergelijken

	Poweranalyse voor overlevingsstudies	Kaplan-Meier Overlevingsschatter
Vakgebied	Statistiek	Overlevingsanalyse
Familie	Hypothesis test	Survival analysis
Jaar van ontstaan	1981	1958
Grondlegger	—	Kaplan, E. L. & Meier, P.
Type	Sample size determination for survival outcomes	Non-parametric survival estimator
Oorspronkelijke bron	Schoenfeld, D. A. (1981). The asymptotic properties of nonparametric tests for comparing survival distributions. Biometrika, 68(1), 316–319.	Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481.
Aliassen	log-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç Analizi	product-limit estimator, km curve, kaplan-meier sağkalım analizi
Verwant	6	2
Samenvatting	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 Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups.