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| 유연 모수 생존 모형 (Royston-Parmar)× | Kaplan-Meier 생존 추정량× | |
|---|---|---|
| 분야 | 생존분석 | 생존분석 |
| 계열 | Survival analysis | Survival analysis |
| 기원 연도≠ | 2002 | 1958 |
| 창시자≠ | Royston, P. & Parmar, M.K.B. | Kaplan, E. L. & Meier, P. |
| 유형≠ | Parametric survival regression model | Non-parametric survival estimator |
| 원전≠ | Royston, 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 ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| 별칭≠ | flexible parametric model, restricted cubic spline survival model, stpm2, Esnek Parametrik Survival Modeli (Royston-Parmar) | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| 관련≠ | 8 | 2 |
| 요약≠ | The 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 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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