ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

生存研究的功效分析×Cox比例风险模型×
领域统计学流行病学
方法族Hypothesis testProcess / pipeline
起源年份19811972
提出者Sir David Roxbee Cox
类型Sample size determination for survival outcomesSemi-parametric regression model
开创性文献Schoenfeld, 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 ↗
别名log-rank power analysis, cox regression power analysis, survival power analysis, Sağkalım Analizi Güç AnaliziCox regression, Cox PH model, proportional hazards model, CPH
相关65
摘要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.
ScholarGate数据集
  1. v1
  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Survival Analysis Power Analysis · Cox proportional hazards. 于 2026-06-20 检索自 https://scholargate.app/zh/compare