Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Usanifu wa Cox wenye Vigezo Vinavyobadilika kwa Wakati× | Mfumo wa Kunusurika wa Parametrici Unyumbufu (Royston-Parmar)× | |
|---|---|---|
| Nyanja | Uchanganuzi wa Uhai | Uchanganuzi wa Uhai |
| Familia | Survival analysis | Survival analysis |
| Mwaka wa asili≠ | 1972 | 2002 |
| Mwanzilishi≠ | Cox, D. R. (extended formulation by Therneau & Grambsch) | Royston, P. & Parmar, M.K.B. |
| Aina≠ | Semi-parametric hazard regression model | Parametric survival regression model |
| Chanzo asilia≠ | Therneau, T. M. & Grambsch, P. M. (2000). Modeling Survival Data: Extending the Cox Model. Springer. 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 ↗ |
| Majina mbadala≠ | time-varying covariate Cox model, extended Cox model, Zamana Bağlı Kovaryatlı Cox Regresyonu | flexible parametric model, restricted cubic spline survival model, stpm2, Esnek Parametrik Survival Modeli (Royston-Parmar) |
| Zinazohusiana≠ | 4 | 8 |
| Muhtasari≠ | Time-dependent Cox regression is an extension of the standard Cox proportional hazards model, introduced through the counting-process formulation developed by Therneau and Grambsch (2000), that allows one or more predictor variables to take different values at different points in a subject's follow-up period. It is the method of choice whenever a covariate — such as a laboratory measurement, a medication dose, or a disease severity score — changes over time rather than remaining fixed from study entry. | 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. |
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