Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Estimatorul de Supraviețuire Kaplan-Meier× | Regresia Parametrică de Supraviețuire Weibull× | |
|---|---|---|
| Domeniu | Supraviețuire | Supraviețuire |
| Familie | Survival analysis | Survival analysis |
| Anul apariției≠ | 1958 | 1951 |
| Autorul original≠ | Kaplan, E. L. & Meier, P. | Waloddi Weibull |
| Tip≠ | Non-parametric survival estimator | Fully parametric survival regression model |
| Sursa seminală≠ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ | Kalbfleisch, J. D. & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. DOI ↗ |
| Denumiri alternative≠ | product-limit estimator, km curve, kaplan-meier sağkalım analizi | weibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma |
| Înrudite≠ | 2 | 4 |
| Rezumat≠ | The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups. | 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. |
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