Salīdzināt metodes

	Robustā Koksa regresija	Koksas proporcionālās bīstamības regresija
Nozare	Statistika	Dzīvildze
Saime	Regression model	Survival analysis
Izcelsmes gads	1989	1972
Autors	Lin & Wei	Cox, D. R.
Tips	Semi-parametric survival regression with robust variance	Semi-parametric hazard regression model
Pirmavots	Lin, D. Y., & Wei, L. J. (1989). The robust inference for the Cox proportional hazards model. Journal of the American Statistical Association, 84(408), 1074–1078.	Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202.
Citi nosaukumi	Cox model with robust standard errors, sandwich-variance Cox regression, Lin-Wei robust Cox model, robust partial likelihood regression	cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Saistītās	3	3
Kopsavilkums	Robust Cox regression fits the standard Cox proportional hazards model but replaces the model-based variance estimate with a sandwich (Huber-White) estimator. This yields valid standard errors and confidence intervals even when observations are clustered, the independence assumption is mildly violated, or the working model is slightly misspecified, without discarding the familiar hazard-ratio interpretation.	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.