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Регресія пропорційних небезпек Кокса×Модель спільної невидимості для кластеризованих даних виживаності×Оцінювач виживаності Каплана-Мейєра×Лог-ранговий критерій для порівняння кривих виживаності×
ГалузьАналіз виживаностіАналіз виживаностіАналіз виживаностіАналіз виживаності
РодинаSurvival analysisSurvival analysisSurvival analysisSurvival analysis
Рік появи1972197919581966
Автор методуCox, D. R.Vaupel, J.W., Manton, K.G. & Stallard, E.Kaplan, E. L. & Meier, P.Mantel, N.
ТипSemi-parametric hazard regression modelRandom effects survival modelNon-parametric survival estimatorNon-parametric hypothesis test
Основоположне джерелоCox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗Vaupel, 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 ↗
Інші назвиcox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonushared 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
Пов'язані3322
ПідсумокCox proportional hazards regression, introduced by D. R. Cox in 1972, is a semi-parametric model that estimates how one or more covariates affect the hazard — the instantaneous rate of experiencing an event — while leaving the baseline hazard function unspecified. It is the standard multivariable method in survival analysis and produces hazard ratios that quantify the relative risk associated with each predictor.The 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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ScholarGateПорівняння методів: Cox Regression · Frailty Model · Kaplan-Meier · Log-Rank Test. Отримано 2026-06-19 з https://scholargate.app/uk/compare