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| Shared Frailty Model för klustrade överlevnadsdata× | Kaplan-Meier-skattaren× | |
|---|---|---|
| Ämnesområde | Överlevnadsanalys | Överlevnadsanalys |
| Familj | Survival analysis | Survival analysis |
| Ursprungsår≠ | 1979 | 1958 |
| Upphovsperson≠ | Vaupel, J.W., Manton, K.G. & Stallard, E. | Kaplan, E. L. & Meier, P. |
| Typ≠ | Random effects survival model | Non-parametric survival estimator |
| Ursprungskälla≠ | 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 ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| Alias | shared frailty model, random effects survival model, Frailty Modeli (Paylaşılan Kırılganlık) | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| Närliggande≠ | 3 | 2 |
| Sammanfattning≠ | 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. |
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