Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Weibull parametrische overlevingsregressie× | Kaplan-Meier Overlevingsschatter× | |
|---|---|---|
| Vakgebied | Overlevingsanalyse | Overlevingsanalyse |
| Familie | Survival analysis | Survival analysis |
| Jaar van ontstaan≠ | 1951 | 1958 |
| Grondlegger≠ | Waloddi Weibull | Kaplan, E. L. & Meier, P. |
| Type≠ | Fully parametric survival regression model | Non-parametric survival estimator |
| Oorspronkelijke bron≠ | Kalbfleisch, J. D. & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. DOI ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| Aliassen≠ | weibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| Verwant≠ | 4 | 2 |
| Samenvatting≠ | 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. | 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. |
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