Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise de Sobrevivência Bayesiana× | Regressão Paramétrica de Sobrevivência de Weibull× | |
|---|---|---|
| Área≠ | Bayesiano | Análise de sobrevivência |
| Família≠ | Bayesian methods | Survival analysis |
| Ano de origem≠ | 2001 | 1951 |
| Autor original≠ | Ibrahim, Chen & Sinha | Waloddi Weibull |
| Tipo≠ | Bayesian time-to-event model | Fully parametric survival regression model |
| Fonte seminal≠ | Ibrahim, J.G., Chen, M.-H. & Sinha, D. (2001). Bayesian Survival Analysis. Springer. DOI ↗ | Kalbfleisch, J. D. & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. DOI ↗ |
| Outros nomes≠ | bayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard model | weibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma |
| Relacionados | 4 | 4 |
| Resumo≠ | Bayesian survival analysis applies Bayesian inference to time-to-event models — Cox proportional hazards, parametric (Weibull, exponential), and cure models. Formalised comprehensively by Ibrahim, Chen and Sinha (2001), the approach encodes prior knowledge about hazard rates and regression coefficients, then updates it with censored survival data to yield posterior hazard ratios and credible intervals rather than single point estimates. | Weibull regression is a fully parametric survival model, formalised by Kalbfleisch and Prentice, that assumes survival times follow a Weibull distribution. A shape parameter controls whether the hazard increases, decreases, or remains constant over time, while covariates shift the scale of the distribution to express how predictors affect survival. |
| ScholarGateConjunto de dados ↗ |
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