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Kaplan-Meieri elulemuse estimaator×Korduvate sündmuste ellujäämismudel×
ValdkondElukestusanalüüsElukestusanalüüs
PerekondSurvival analysisSurvival analysis
Tekkeaasta19581981
LoojaKaplan, E. L. & Meier, P.Andersen & Gill (AG, 1982); Prentice, Williams & Peterson (PWP, 1981); Wei, Lin & Weissfeld (WLW, 1989)
TüüpNon-parametric survival estimatorSemi-parametric hazard model for repeated events
AlgallikasKaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗Cook, R.J. & Lawless, J.F. (2007). The Statistical Analysis of Recurrent Events. Springer. DOI ↗
Rööpnimetusedproduct-limit estimator, km curve, kaplan-meier sağkalım analiziTekrarlayan Olay Modeli (Recurrent Events), Andersen-Gill model, AG model, Wei-Lin-Weissfeld model
Seotud24
KokkuvõteThe 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.A recurrent event model is a survival analysis extension, formalised through the landmark contributions of Prentice, Williams and Peterson (1981), Andersen and Gill (1982), and Wei, Lin and Weissfeld (1989), that models time-to-event data when the same event — such as a hospital readmission, disease relapse, or equipment failure — can occur multiple times in the same individual. The three principal frameworks are the Andersen-Gill (AG) model, the Prentice-Williams-Peterson (PWP) stratified model, and the Wei-Lin-Weissfeld (WLW) marginal model, each making different assumptions about within-subject dependence.
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ScholarGateVõrdle meetodeid: Kaplan-Meier · Recurrent Event Model. Loetud 2026-06-18 aadressilt https://scholargate.app/et/compare