قارن الطرق

	انحدار كوكس للمخاطر النسبية	نموذج الهشاشة المشتركة للبيانات البقائية المجمعة	اختبار لوغاريتم الرتب للمقارنة بين منحنيات البقاء
المجال	تحليل البقاء	تحليل البقاء	تحليل البقاء
العائلة	Survival analysis	Survival analysis	Survival analysis
سنة النشأة	1972	1979	1966
صاحب الطريقة	Cox, D. R.	Vaupel, J.W., Manton, K.G. & Stallard, E.	Mantel, N.
النوع	Semi-parametric hazard regression model	Random effects survival model	Non-parametric hypothesis test
المصدر التأسيسي	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.	Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170.
الأسماء البديلة	cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu	shared frailty model, random effects survival model, Frailty Modeli (Paylaşılan Kırılganlık)	Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
ذات صلة	3	3	2
الملخص	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.