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| Accelerated Failure Time (AFT) Modell× | Weibull Parametrische Überlebensregression× | |
|---|---|---|
| Fachgebiet | Überlebenszeitanalyse | Überlebenszeitanalyse |
| Familie | Survival analysis | Survival analysis |
| Entstehungsjahr≠ | 1992 | 1951 |
| Urheber≠ | Wei, L. J. (seminal review 1992); origins in parametric survival literature | Waloddi Weibull |
| Typ≠ | Parametric survival regression model | Fully parametric survival regression model |
| Wegweisende Quelle≠ | Wei, L. J. (1992). The Accelerated Failure Time Model: A Useful Alternative to the Cox Regression Model in Survival Analysis. Statistics in Medicine, 11(14–15), 1871–1879. DOI ↗ | Kalbfleisch, J. D. & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. DOI ↗ |
| Aliasnamen≠ | AFT model, parametric survival regression, Hızlandırılmış Başarısızlık Zamanı Modeli (AFT) | weibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma |
| Verwandt≠ | 3 | 4 |
| Zusammenfassung≠ | The Accelerated Failure Time model is a parametric regression approach to survival analysis — formally reviewed and advocated by L. J. Wei in 1992 — in which covariates act as multiplicative factors that directly stretch or compress the time-to-event scale. Unlike the Cox proportional-hazards model, which models how covariates shift the hazard rate, AFT models express the covariate effect as an acceleration or deceleration of the time axis itself. | Weibull regression is a fully parametric survival model, formalised by Kalbfleisch and Prentice, that assumes survival times follow a Weibull distribution. A shape parameter controls whether the hazard increases, decreases, or remains constant over time, while covariates shift the scale of the distribution to express how predictors affect survival. |
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