مقایسهٔ روشها
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| مدل پارامتریک انعطافپذیر بقا (رویستون-پارمار)× | مدل آمیخته درمان× | |
|---|---|---|
| حوزه | تحلیل بقا | تحلیل بقا |
| خانواده | Survival analysis | Survival analysis |
| سال پیدایش≠ | 2002 | 1949 |
| پدیدآور≠ | Royston, P. & Parmar, M.K.B. | Boag, J. W. |
| نوع≠ | Parametric survival regression model | Parametric mixture survival model |
| منبع بنیادین≠ | 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 ↗ | Boag, J. W. (1949). Maximum Likelihood Estimates of the Proportion of Patients Cured. Journal of the Royal Statistical Society B, 11(1), 15–53. link ↗ |
| نامهای دیگر | flexible parametric model, restricted cubic spline survival model, stpm2, Esnek Parametrik Survival Modeli (Royston-Parmar) | cure fraction model, cure rate model, bounded cumulative hazard model, İyileşme Modeli (Mixture Cure Model) |
| مرتبط≠ | 8 | 2 |
| خلاصه≠ | 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 mixture cure model, first proposed by Boag in 1949 for cancer survival data, is a parametric survival model that explicitly accounts for a fraction of subjects who will never experience the event of interest — the so-called cured or immune fraction. It is the appropriate tool whenever the Kaplan-Meier curve levels off into a long, stable plateau rather than continuing to decline, indicating that a proportion of subjects are permanently event-free. |
| ScholarGateمجموعهداده ↗ |
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