Сравнение методов

	Регрессия пропорциональных рисков Кокса	Модель общего случайного эффекта для кластеризованных данных выживаемости
Область	Анализ выживаемости	Анализ выживаемости
Семейство	Survival analysis	Survival analysis
Год появления	1972	1979
Автор метода	Cox, D. R.	Vaupel, J.W., Manton, K.G. & Stallard, E.
Тип	Semi-parametric hazard regression model	Random effects survival model
Основополагающий источник	Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202.	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.
Другие названия	cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu	shared frailty model, random effects survival model, Frailty Modeli (Paylaşılan Kırılganlık)
Связанные	3	3
Сводка	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.