手法を比較

	生存時間解析における検出力分析	Cox Proportional Hazards
分野	統計学	疫学
系統	Hypothesis test	Process / pipeline
提唱年	1981	1972
提唱者	—	Sir David Roxbee Cox
種類	Sample size determination for survival outcomes	Semi-parametric regression model
原典	Schoenfeld, D. A. (1981). The asymptotic properties of nonparametric tests for comparing survival distributions. Biometrika, 68(1), 316–319.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
別名	log-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç Analizi	Cox regression, Cox PH model, proportional hazards model, CPH
関連	6	5
概要	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 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.