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Elastyczny model parametryczny przeżycia (Royston-Parmar)×Test log-rank do porównywania krzywych przeżycia×
DziedzinaAnaliza przeżyciaAnaliza przeżycia
RodzinaSurvival analysisSurvival analysis
Rok powstania20021966
TwórcaRoyston, P. & Parmar, M.K.B.Mantel, N.
TypParametric survival regression modelNon-parametric hypothesis test
Źródło pierwotneRoyston, P. & Parmar, M.K.B. (2002). Flexible Parametric Proportional-Hazards and Proportional-Odds Models for Censored Survival Data, with Application to Prognostic Modelling and Estimation of Treatment Effects. Statistics in Medicine, 21(15), 2175–2197. 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 ↗
Inne nazwyflexible parametric model, restricted cubic spline survival model, stpm2, Esnek Parametrik Survival Modeli (Royston-Parmar)Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi
Pokrewne82
PodsumowanieThe Royston-Parmar model, introduced by Royston and Parmar in 2002, is a modern parametric approach to survival analysis that replaces the rigid distributional assumptions of classical models with a restricted cubic spline fitted to the log-cumulative-hazard scale. It combines the interpretability of a fully parametric model with the flexibility to capture non-standard hazard shapes, and it supports proportional-hazards, accelerated failure-time, and proportional-odds link functions.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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ScholarGatePorównaj metody: Royston-Parmar Model · Log-Rank Test. Pobrano 2026-06-19 z https://scholargate.app/pl/compare