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Anàlisi de potència per a estudis de supervivència×Cox Proportional Hazards×
CampEstadísticaEpidemiologia
FamíliaHypothesis testProcess / pipeline
Any d'origen19811972
Autor originalSir David Roxbee Cox
TipusSample size determination for survival outcomesSemi-parametric regression model
Font seminalSchoenfeld, 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 ↗
Àlieslog-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç AnaliziCox regression, Cox PH model, proportional hazards model, CPH
Relacionats65
ResumPower 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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ScholarGateCompara mètodes: Survival Analysis Power Analysis · Cox proportional hazards. Recuperat el 2026-06-19 de https://scholargate.app/ca/compare