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Joustava parametrinen eloonjäämismalli (Royston-Parmar)×Coxin hazard-suhteiden regressiomalli×
TieteenalaElinaika-analyysiElinaika-analyysi
MenetelmäperheSurvival analysisSurvival analysis
Syntyvuosi20021972
KehittäjäRoyston, P. & Parmar, M.K.B.Cox, D. R.
TyyppiParametric survival regression modelSemi-parametric hazard regression model
AlkuperäislähdeRoyston, 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 ↗Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗
Rinnakkaisnimetflexible parametric model, restricted cubic spline survival model, stpm2, Esnek Parametrik Survival Modeli (Royston-Parmar)cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu
Liittyvät83
TiivistelmäThe 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.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.
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