Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Гнучка параметрична модель виживаності (Royston-Parmar)× | Лог-ранговий критерій для порівняння кривих виживаності× | |
|---|---|---|
| Галузь | Аналіз виживаності | Аналіз виживаності |
| Родина | Survival analysis | Survival analysis |
| Рік появи≠ | 2002 | 1966 |
| Автор методу≠ | Royston, P. & Parmar, M.K.B. | Mantel, N. |
| Тип≠ | Parametric survival regression model | Non-parametric hypothesis test |
| Основоположне джерело≠ | 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 ↗ | Mantel, N. (1966). Evaluation of Survival Data and Two New Rank Order Statistics Arising in Its Consideration. Cancer Chemotherapy Reports, 50(3), 163–170. link ↗ |
| Інші назви | flexible parametric model, restricted cubic spline survival model, stpm2, Esnek Parametrik Survival Modeli (Royston-Parmar) | Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi |
| Пов'язані≠ | 8 | 2 |
| Підсумок≠ | 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 log-rank test, developed by Nathan Mantel in 1966, is a non-parametric hypothesis test that compares the overall survival experience of two or more groups throughout the entire follow-up period. It is the standard companion to Kaplan-Meier curves and determines whether observed differences between curves are statistically meaningful. |
| ScholarGateНабір даних ↗ |
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