Sammenlign metoder
Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.
| Overlevelsesregression× | Cox Proportional Hazards Regression× | |
|---|---|---|
| Fagområde≠ | Statistik | Overlevelsesanalyse |
| Familie≠ | Regression model | Survival analysis |
| Oprindelsesår≠ | 1980s | 1972 |
| Ophavsperson≠ | Kalbfleisch & Prentice; Cox & Oakes | Cox, D. R. |
| Type≠ | Parametric survival model | Semi-parametric hazard regression model |
| Oprindelig kilde≠ | Kalbfleisch, J. D., & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. ISBN: 978-0471363576 | Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗ |
| Aliasser | accelerated failure time model, AFT model, parametric survival model, time-to-event regression | cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu |
| Relaterede | 3 | 3 |
| Resumé≠ | Survival 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. |
| ScholarGateDatasæt ↗ |
|
|