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Daudzstāvokļu izdzīvošanas modelis×Kaplana-Meiera izdzīvošanas novērtētājs×
NozareDzīvildzeDzīvildze
SaimeSurvival analysisSurvival analysis
Izcelsmes gads19781958
AutorsAndersen, P.K. & Keiding, N. (foundational framework); popularised by Putter, Fiocco & Geskus (2007)Kaplan, E. L. & Meier, P.
TipsSemi-parametric hazard modelNon-parametric survival estimator
PirmavotsPutter, H., Fiocco, M. & Geskus, R.B. (2007). Tutorial in Biostatistics: Competing Risks and Multi-State Models. Statistics in Medicine, 26(11), 2389–2430. DOI ↗Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗
Citi nosaukumiillness-death model, multi-state transition model, Çok Durumlu Model (Multi-State / Illness-Death)product-limit estimator, km curve, kaplan-meier sağkalım analizi
Saistītās42
KopsavilkumsThe multi-state model is a generalised survival framework, formalised in the work of Andersen and Keiding and brought to wide biostatistical practice by Putter, Fiocco and Geskus (2007), that models individuals moving through multiple distinct health states — for example, healthy, ill and dead — over time. A separate hazard function is estimated for each possible transition, and transition probabilities are recovered via the product-integral of the cumulative transition intensities.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: Multi-State Model · Kaplan-Meier. Izgūts 2026-06-15 no https://scholargate.app/lv/compare