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| Többállapotú túlélési modell× | Royston-Parmar Model× | |
|---|---|---|
| Tudományterület | Túléléselemzés | Túléléselemzés |
| Módszercsalád | Survival analysis | Survival analysis |
| Keletkezés éve≠ | 1978 | 2002 |
| Megalkotó≠ | Andersen, P.K. & Keiding, N. (foundational framework); popularised by Putter, Fiocco & Geskus (2007) | Royston, P. & Parmar, M.K.B. |
| Típus≠ | Semi-parametric hazard model | Parametric survival regression model |
| Alapmű≠ | Putter, H., Fiocco, M. & Geskus, R.B. (2007). Tutorial in Biostatistics: Competing Risks and Multi-State Models. Statistics in Medicine, 26(11), 2389–2430. DOI ↗ | 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 ↗ |
| Alternatív nevek≠ | illness-death model, multi-state transition model, Çok Durumlu Model (Multi-State / Illness-Death) | flexible parametric model, restricted cubic spline survival model, stpm2, Esnek Parametrik Survival Modeli (Royston-Parmar) |
| Kapcsolódó≠ | 4 | 8 |
| Összefoglaló≠ | The 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 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. |
| ScholarGateAdatkészlet ↗ |
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