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Survival Regression×Cox-Proportional-Hazards-Regression×
FachgebietStatistikÜberlebenszeitanalyse
FamilieRegression modelSurvival analysis
Entstehungsjahr1980s1972
UrheberKalbfleisch & Prentice; Cox & OakesCox, D. R.
TypParametric survival modelSemi-parametric hazard regression model
Wegweisende QuelleKalbfleisch, J. D., & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. ISBN: 978-0471363576Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗
Aliasnamenaccelerated failure time model, AFT model, parametric survival model, time-to-event regressioncox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Verwandt33
ZusammenfassungSurvival regression models the time until an event occurs — such as death, failure, or relapse — as a function of covariates. Unlike ordinary regression, it properly accounts for censored observations (cases where the event had not yet occurred at the end of follow-up) by specifying a parametric distribution for the survival time and estimating covariate effects via maximum likelihood.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.
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ScholarGateMethoden vergleichen: Survival Regression · Cox Regression. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare