Methoden vergleichen

	Risikoadjustierte Kaplan-Meier-Analyse	Cox-Proportional-Hazards-Modell
Fachgebiet	Epidemiologie	Epidemiologie
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	2001–2004 (formal statistical framework for weighted KM curves)	1972
Urheber	Conceptual basis: Kaplan & Meier (1958); risk-adjustment via IPTW formalised by Hernán, Brumback & Robins (2001), with practical implementation by Cole & Hernán (2004)	Sir David Roxbee Cox
Typ	Adjusted non-parametric survival method	Semi-parametric regression model
Wegweisende Quelle	Cole, S. R., & Hernan, M. A. (2004). Adjusted survival curves with inverse probability weights. Computer Methods and Programs in Biomedicine, 75(1), 45–49.	Cox, D. R. (1972). Regression models and life-tables. Journal of the Royal Statistical Society: Series B (Methodological), 34(2), 187–202.
Aliasnamen	weighted Kaplan-Meier, IPTW-adjusted Kaplan-Meier, propensity-score-weighted survival curves, adjusted survival curves	Cox regression, Cox PH model, proportional hazards model, CPH
Verwandt	5	5
Zusammenfassung	Risk-adjusted Kaplan-Meier analysis combines the non-parametric Kaplan-Meier estimator with inverse probability of treatment weighting (IPTW) or similar risk-adjustment procedures to produce survival curves that are comparable across groups as if the groups had identical distributions of baseline confounders. It is the observational-study analogue of plotting survival curves from a randomised trial.	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.