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Nelson-Aalen kumulatīvaisais riska novērtējums×Koksas proporcionālās bīstamības regresija×Kopīgā trausluma modelis (Shared Frailty Model) grupētiem izdzīvošanas datiem×Kaplana-Meiera izdzīvošanas novērtētājs×
NozareDzīvildzeDzīvildzeDzīvildzeDzīvildze
SaimeSurvival analysisSurvival analysisSurvival analysisSurvival analysis
Izcelsmes gads1972197219791958
AutorsWayne Nelson & Odd AalenCox, D. R.Vaupel, J.W., Manton, K.G. & Stallard, E.Kaplan, E. L. & Meier, P.
TipsNon-parametric cumulative hazard estimatorSemi-parametric hazard regression modelRandom effects survival modelNon-parametric survival estimator
PirmavotsNelson, W. (1972). Theory and applications of hazard plotting for censored failure data. Technometrics, 14(4), 945–966. DOI ↗Cox, 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 ↗
Citi nosaukumiNelson-Aalen cumulative hazard, Aalen estimator, empirical cumulative hazard, Nelson-Aalen kümülatif hazard tahmincisicox 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 analizi
Saistītās5332
KopsavilkumsThe Nelson-Aalen estimator is a non-parametric estimator of the cumulative hazard function from right-censored time-to-event data. Developed by Wayne Nelson for reliability hazard plotting in 1972 and placed on a rigorous counting-process foundation by Odd Aalen in 1978, it accumulates the ratio of observed events to the number at risk at each event time, providing the natural hazard-scale companion to the Kaplan-Meier survival curve.Cox 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.
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ScholarGateSalīdzināt metodes: Nelson-Aalen Estimator · Cox Regression · Frailty Model · Kaplan-Meier. Izgūts 2026-06-19 no https://scholargate.app/lv/compare