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Võimsusanalüüs elulemusuuringutele×Coxi proportsionaalne riskimudel×
ValdkondStatistikaEpidemioloogia
PerekondHypothesis testProcess / pipeline
Tekkeaasta19811972
LoojaSir David Roxbee Cox
TüüpSample size determination for survival outcomesSemi-parametric regression model
AlgallikasSchoenfeld, 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 ↗
Rööpnimetusedlog-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç AnaliziCox regression, Cox PH model, proportional hazards model, CPH
Seotud65
KokkuvõtePower 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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ScholarGateVõrdle meetodeid: Survival Analysis Power Analysis · Cox proportional hazards. Loetud 2026-06-20 aadressilt https://scholargate.app/et/compare