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Analýza síly pro studie přežití×Coxův model proporcionálních rizik×
OborStatistikaEpidemiologie
RodinaHypothesis testProcess / pipeline
Rok vzniku19811972
TvůrceSir David Roxbee Cox
TypSample size determination for survival outcomesSemi-parametric regression model
Původní zdrojSchoenfeld, D. A. (1981). The asymptotic properties of nonparametric tests for comparing survival distributions. Biometrika, 68(1), 316–319. DOI ↗Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202. DOI ↗
Další názvylog-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç AnaliziCox regression, Cox PH model, proportional hazards model, CPH
Příbuzné65
ShrnutíPower 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 Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research.
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ScholarGatePorovnat metody: Survival Analysis Power Analysis · Cox proportional hazards. Získáno 2026-06-19 z https://scholargate.app/cs/compare