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Регрессия выживаемости×Регрессия пропорциональных рисков Кокса×
ОбластьСтатистикаАнализ выживаемости
СемействоRegression modelSurvival analysis
Год появления1980s1972
Автор методаKalbfleisch & Prentice; Cox & OakesCox, D. R.
ТипParametric survival modelSemi-parametric hazard regression model
Основополагающий источникKalbfleisch, 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 ↗
Другие названияaccelerated failure time model, AFT model, parametric survival model, time-to-event regressioncox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Связанные33
СводкаSurvival 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.
ScholarGateНабор данных
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  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Survival Regression · Cox Regression. Получено 2026-06-18 из https://scholargate.app/ru/compare