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Bayesian Survival Analysis×Kaplan-Meieri elulemuse estimaator×
ValdkondBayesi meetodidElukestusanalüüs
PerekondBayesian methodsSurvival analysis
Tekkeaasta20011958
LoojaIbrahim, Chen & SinhaKaplan, E. L. & Meier, P.
TüüpBayesian time-to-event modelNon-parametric survival estimator
AlgallikasIbrahim, J.G., Chen, M.-H. & Sinha, D. (2001). Bayesian Survival Analysis. Springer. DOI ↗Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗
Rööpnimetusedbayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard modelproduct-limit estimator, km curve, kaplan-meier sağkalım analizi
Seotud42
KokkuvõteBayesian 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.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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ScholarGateVõrdle meetodeid: Bayesian Survival Analysis · Kaplan-Meier. Loetud 2026-06-17 aadressilt https://scholargate.app/et/compare