Comparer des méthodes

	Modèle de Cox proportionnel des dangers	Cox proportional hazards
Domaine	Épidémiologie	Épidémiologie
Famille	Process / pipeline	Process / pipeline
Année d'origine	1972 (Cox model); matched extension widely adopted 1970s–1980s	1972
Auteur d'origine	D. R. Cox (Cox model, 1972); stratification extension for matched designs by subsequent methodologists including D. C. Thomas	Sir David Roxbee Cox
Type	Semi-parametric survival regression for matched data	Semi-parametric regression model
Source fondatrice	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Alias	stratified Cox regression, conditional Cox model, matched survival analysis, Cox model for matched pairs	Cox regression, Cox PH model, proportional hazards model, CPH
Apparentées	4	5
Résumé	Matched Cox proportional hazards is a survival analysis method that extends the Cox regression model to appropriately handle data arising from matched study designs — matched cohorts or matched case-control studies with time-to-event outcomes. By stratifying the partial likelihood by matched set, the method eliminates confounding from matching factors without estimating their baseline hazard, yielding valid hazard ratio estimates that are free from matching-induced bias.	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.