Salīdzināt metodes
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| Beiešiskā Koksa regresija× | Koksas proporcionālās bīstamības regresija× | |
|---|---|---|
| Nozare≠ | Statistika | Dzīvildze |
| Saime≠ | Regression model | Survival analysis |
| Izcelsmes gads≠ | 1972 (Cox PH); 2001 (Bayesian treatment) | 1972 |
| Autors≠ | Cox (1972) for the base model; Bayesian formulation by Sinha, Chen & Ghosh (1990s); comprehensive treatment by Ibrahim, Chen & Sinha (2001) | Cox, D. R. |
| Tips≠ | Survival regression | Semi-parametric hazard regression model |
| Pirmavots≠ | Ibrahim, J. G., Chen, M.-H., & Sinha, D. (2001). Bayesian Survival Analysis. Springer. ISBN: 978-0387952772 | Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗ |
| Citi nosaukumi | Bayesian Cox PH model, Bayesian proportional hazards model, Bayesian survival regression, BCox | cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu |
| Saistītās≠ | 6 | 3 |
| Kopsavilkums≠ | Bayesian Cox regression combines the Cox proportional hazards model for time-to-event data with Bayesian inference. Instead of point estimates, it produces full posterior distributions over the hazard ratios, naturally incorporating prior knowledge and providing coherent uncertainty quantification even with small samples or informative censoring. | 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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