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베이지안 생존 분석×Kaplan-Meier 생존 추정량×Weibull 모수 생존 회귀분석×
분야베이지안생존분석생존분석
계열Bayesian methodsSurvival analysisSurvival analysis
기원 연도200119581951
창시자Ibrahim, Chen & SinhaKaplan, E. L. & Meier, P.Waloddi Weibull
유형Bayesian time-to-event modelNon-parametric survival estimatorFully parametric survival regression model
원전Ibrahim, 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 ↗Kalbfleisch, J. D. & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. DOI ↗
별칭bayesian sağkalım analizi, bayesian time-to-event analysis, bayesian hazard modelproduct-limit estimator, km curve, kaplan-meier sağkalım analiziweibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma
관련424
요약Bayesian 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.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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ScholarGate방법 비교: Bayesian Survival Analysis · Kaplan-Meier · Weibull Regression. 2026-06-18에 다음에서 검색함: https://scholargate.app/ko/compare