Comparer des méthodes

	Modèle de fragilité partagée pour données de survie groupées	Estimateur de survie de Kaplan-Meier
Domaine	Analyse de survie	Analyse de survie
Famille	Survival analysis	Survival analysis
Année d'origine	1979	1958
Auteur d'origine	Vaupel, J.W., Manton, K.G. & Stallard, E.	Kaplan, E. L. & Meier, P.
Type	Random effects survival model	Non-parametric survival estimator
Source fondatrice	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.	Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481.
Alias	shared frailty model, random effects survival model, Frailty Modeli (Paylaşılan Kırılganlık)	product-limit estimator, km curve, kaplan-meier sağkalım analizi
Apparentées	3	2
Résumé	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 Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups.