Bandingkan kaedah
Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.
| Regresi Kelangsungan Parametrik Weibull× | Penganggar Kemandirian Kaplan-Meier× | |
|---|---|---|
| Bidang | Analisis Survival | Analisis Survival |
| Keluarga | Survival analysis | Survival analysis |
| Tahun asal≠ | 1951 | 1958 |
| Pengasas≠ | Waloddi Weibull | Kaplan, E. L. & Meier, P. |
| Jenis≠ | Fully parametric survival regression model | Non-parametric survival estimator |
| Sumber perintis≠ | 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 ↗ |
| Alias≠ | weibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| Berkaitan≠ | 4 | 2 |
| Ringkasan≠ | 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. |
| ScholarGateSet data ↗ |
|
|