Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Daudzstāvokļu izdzīvošanas modelis× | Konkurējošo risku izdzīvošanas analīze× | |
|---|---|---|
| Nozare | Dzīvildze | Dzīvildze |
| Saime | Survival analysis | Survival analysis |
| Izcelsmes gads≠ | 1978 | 1999 |
| Autors≠ | Andersen, P.K. & Keiding, N. (foundational framework); popularised by Putter, Fiocco & Geskus (2007) | Fine, J.P. & Gray, R.J. |
| Tips≠ | Semi-parametric hazard model | Competing risks survival model |
| Pirmavots≠ | Putter, H., Fiocco, M. & Geskus, R.B. (2007). Tutorial in Biostatistics: Competing Risks and Multi-State Models. Statistics in Medicine, 26(11), 2389–2430. DOI ↗ | Fine, J.P. & Gray, R.J. (1999). A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association, 94(446), 496–509. DOI ↗ |
| Citi nosaukumi≠ | illness-death model, multi-state transition model, Çok Durumlu Model (Multi-State / Illness-Death) | Rekabet Eden Riskler Analizi, cumulative incidence function, CIF analysis, cause-specific survival analysis |
| Saistītās≠ | 4 | 5 |
| Kopsavilkums≠ | The multi-state model is a generalised survival framework, formalised in the work of Andersen and Keiding and brought to wide biostatistical practice by Putter, Fiocco and Geskus (2007), that models individuals moving through multiple distinct health states — for example, healthy, ill and dead — over time. A separate hazard function is estimated for each possible transition, and transition probabilities are recovered via the product-integral of the cumulative transition intensities. | Competing risks analysis, formalized by Fine and Gray in 1999, is a survival analysis framework for settings where a subject can experience one of several mutually exclusive event types. The key quantity is the cumulative incidence function (CIF), which estimates the probability of a specific event occurring by time t in the presence of the other competing events. |
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