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| Bayes'sche Regression× | Cox-Proportional-Hazards-Regression× | |
|---|---|---|
| Fachgebiet≠ | Bayes-Statistik | Überlebenszeitanalyse |
| Familie≠ | Bayesian methods | Survival analysis |
| Entstehungsjahr≠ | — | 1972 |
| Urheber≠ | — | Cox, D. R. |
| Typ≠ | Bayesian linear model | Semi-parametric hazard regression model |
| Wegweisende Quelle≠ | Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955 | Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗ |
| Aliasnamen≠ | bayesian linear regression, probabilistic regression, bayesian regresyon | cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu |
| Verwandt≠ | 2 | 3 |
| Zusammenfassung≠ | Bayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off. | 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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