Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Kopīgā trausluma modelis (Shared Frailty Model) grupētiem izdzīvošanas datiem× | Modelis atkārtotu notikumu izdzīvošanai× | |
|---|---|---|
| Nozare | Dzīvildze | Dzīvildze |
| Saime | Survival analysis | Survival analysis |
| Izcelsmes gads≠ | 1979 | 1981 |
| Autors≠ | Vaupel, J.W., Manton, K.G. & Stallard, E. | Andersen & Gill (AG, 1982); Prentice, Williams & Peterson (PWP, 1981); Wei, Lin & Weissfeld (WLW, 1989) |
| Tips≠ | Random effects survival model | Semi-parametric hazard model for repeated events |
| Pirmavots≠ | 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 ↗ | Cook, R.J. & Lawless, J.F. (2007). The Statistical Analysis of Recurrent Events. Springer. DOI ↗ |
| Citi nosaukumi≠ | shared frailty model, random effects survival model, Frailty Modeli (Paylaşılan Kırılganlık) | Tekrarlayan Olay Modeli (Recurrent Events), Andersen-Gill model, AG model, Wei-Lin-Weissfeld model |
| Saistītās≠ | 3 | 4 |
| Kopsavilkums≠ | 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. | A recurrent event model is a survival analysis extension, formalised through the landmark contributions of Prentice, Williams and Peterson (1981), Andersen and Gill (1982), and Wei, Lin and Weissfeld (1989), that models time-to-event data when the same event — such as a hospital readmission, disease relapse, or equipment failure — can occur multiple times in the same individual. The three principal frameworks are the Andersen-Gill (AG) model, the Prentice-Williams-Peterson (PWP) stratified model, and the Wei-Lin-Weissfeld (WLW) marginal model, each making different assumptions about within-subject dependence. |
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