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Cox比例风险回归×簇生存数据共享脆弱性模型×对生存曲线进行比较的 Log-Rank 检验×
领域生存分析生存分析生存分析
方法族Survival analysisSurvival analysisSurvival analysis
起源年份197219791966
提出者Cox, D. R.Vaupel, J.W., Manton, K.G. & Stallard, E.Mantel, N.
类型Semi-parametric hazard regression modelRandom effects survival modelNon-parametric hypothesis test
开创性文献Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗Vaupel, J.W., Manton, K.G. & Stallard, E. (1979). The Impact of Heterogeneity in Individual Frailty on the Dynamics of Mortality. Demography, 16(3), 439–454. DOI ↗Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170. link ↗
别名cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonushared frailty model, random effects survival model, Frailty Modeli (Paylaşılan Kırılganlık)Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
相关332
摘要Cox proportional hazards regression, introduced by D. R. Cox in 1972, is a semi-parametric model that estimates how one or more covariates affect the hazard — the instantaneous rate of experiencing an event — while leaving the baseline hazard function unspecified. It is the standard multivariable method in survival analysis and produces hazard ratios that quantify the relative risk associated with each predictor.The shared frailty model, introduced by Vaupel, Manton, and Stallard in 1979, extends standard survival regression by incorporating a random effect — the 'frailty' — that captures unobserved heterogeneity among subjects or clusters. When survival outcomes are measured on individuals who share a common environment (patients in the same hospital, members of the same family, animals in the same litter), a frailty term accounts for the within-cluster dependence that ordinary Cox regression ignores.The log-rank test, developed by Nathan Mantel in 1966, is a non-parametric hypothesis test that compares the overall survival experience of two or more groups throughout the entire follow-up period. It is the standard companion to Kaplan-Meier curves and determines whether observed differences between curves are statistically meaningful.
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ScholarGate方法对比: Cox Regression · Frailty Model · Log-Rank Test. 于 2026-06-20 检索自 https://scholargate.app/zh/compare