Comparer des méthodes

	Modèle d'accélération du temps de défaillance (AFT)	Régression proportionnelle des risques de Cox
Domaine	Analyse de survie	Analyse de survie
Famille	Survival analysis	Survival analysis
Année d'origine	1992	1972
Auteur d'origine	Wei, L. J. (seminal review 1992); origins in parametric survival literature	Cox, D. R.
Type	Parametric survival regression model	Semi-parametric hazard regression model
Source fondatrice	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.	Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202.
Alias	AFT model, parametric survival regression, Hızlandırılmış Başarısızlık Zamanı Modeli (AFT)	cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Apparentées	3	3
Résumé	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.	Cox proportional hazards regression, introduced by D. R. Cox in 1972, is a semi-parametric model that estimates how one or more covariates affect the hazard — the instantaneous rate of experiencing an event — while leaving the baseline hazard function unspecified. It is the standard multivariable method in survival analysis and produces hazard ratios that quantify the relative risk associated with each predictor.