Salīdzināt metodes

	Risku koriģēta Kaplana-Meijera analīze	Koksa proporcionālo risku modelis
Nozare	Epidemioloģija	Epidemioloģija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2001–2004 (formal statistical framework for weighted KM curves)	1972
Autors	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
Tips	Adjusted non-parametric survival method	Semi-parametric regression model
Pirmavots	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.
Citi nosaukumi	weighted Kaplan-Meier, IPTW-adjusted Kaplan-Meier, propensity-score-weighted survival curves, adjusted survival curves	Cox regression, Cox PH model, proportional hazards model, CPH
Saistītās	5	5
Kopsavilkums	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.