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클러스터링된 생존 데이터에 대한 공유 취약성 모형×Kaplan-Meier 생존 추정량×생존 곡선 비교를 위한 로그-순위 검정×
분야생존분석생존분석생존분석
계열Survival analysisSurvival analysisSurvival analysis
기원 연도197919581966
창시자Vaupel, J.W., Manton, K.G. & Stallard, E.Kaplan, E. L. & Meier, P.Mantel, N.
유형Random effects survival modelNon-parametric survival estimatorNon-parametric hypothesis test
원전Vaupel, J.W., Manton, K.G. & Stallard, E. (1979). The Impact of Heterogeneity in Individual Frailty on the Dynamics of Mortality. Demography, 16(3), 439–454. DOI ↗Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170. link ↗
별칭shared frailty model, random effects survival model, Frailty Modeli (Paylaşılan Kırılganlık)product-limit estimator, km curve, kaplan-meier sağkalım analiziMantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
관련322
요약The shared frailty model, introduced by Vaupel, Manton, and Stallard in 1979, extends standard survival regression by incorporating a random effect — the 'frailty' — that captures unobserved heterogeneity among subjects or clusters. When survival outcomes are measured on individuals who share a common environment (patients in the same hospital, members of the same family, animals in the same litter), a frailty term accounts for the within-cluster dependence that ordinary Cox regression ignores.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.The log-rank test, developed by Nathan Mantel in 1966, is a non-parametric hypothesis test that compares the overall survival experience of two or more groups throughout the entire follow-up period. It is the standard companion to Kaplan-Meier curves and determines whether observed differences between curves are statistically meaningful.
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