Sammenlign metoder

	Cox Proportional Hazards	Accelerated Failure Time (AFT) model
Fagområde	Epidemiologi	Overlevelsesanalyse
Familie	Process / pipeline	Survival analysis
Oprindelsesår	1972	1992
Ophavsperson	Sir David Roxbee Cox	Wei, L. J. (seminal review 1992); origins in parametric survival literature
Type	Semi-parametric regression model	Parametric survival regression model
Oprindelig kilde	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.	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.
Aliasser	Cox regression, Cox PH model, proportional hazards model, CPH	AFT model, parametric survival regression, Hızlandırılmış Başarısızlık Zamanı Modeli (AFT)
Relaterede	5	3
Resumé	The Cox proportional hazards model is a semi-parametric regression method that estimates the effect of one or more covariates on the hazard — the instantaneous rate of an event such as death, relapse, or failure — while making no assumption about the shape of the baseline hazard function. Introduced by David Cox in 1972, it is the dominant tool for multivariable survival analysis in clinical and epidemiological research.	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.