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Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

Poweranalyse voor overlevingsstudies×Cox Proportional Hazards×
VakgebiedStatistiekEpidemiologie
FamilieHypothesis testProcess / pipeline
Jaar van ontstaan19811972
GrondleggerSir David Roxbee Cox
TypeSample size determination for survival outcomesSemi-parametric regression model
Oorspronkelijke bronSchoenfeld, 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 ↗
Aliassenlog-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç AnaliziCox regression, Cox PH model, proportional hazards model, CPH
Verwant65
SamenvattingPower 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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ScholarGateMethoden vergelijken: Survival Analysis Power Analysis · Cox proportional hazards. Geraadpleegd op 2026-06-20 via https://scholargate.app/nl/compare