Linganisha mbinu

	Uchambuzi wa Nguvu kwa Ajili ya Tafiti za Usalama wa Maisha	Kikokotozi cha Kuishi cha Kaplan-Meier
Nyanja	Takwimu	Uchanganuzi wa Uhai
Familia	Hypothesis test	Survival analysis
Mwaka wa asili	1981	1958
Mwanzilishi	—	Kaplan, E. L. & Meier, P.
Aina	Sample size determination for survival outcomes	Non-parametric survival estimator
Chanzo asilia	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.
Majina mbadala	log-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç Analizi	product-limit estimator, km curve, kaplan-meier sağkalım analizi
Zinazohusiana	6	2
Muhtasari	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.