পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| ফ্লেক্সিবল প্যারামেট্রিক সারভাইভাল মডেল (রয়স্টন-পার্মার)× | Cox Proportional Hazards Regression× | |
|---|---|---|
| ক্ষেত্র | উত্তরজীবিতা | উত্তরজীবিতা |
| পরিবার | Survival analysis | Survival analysis |
| উদ্ভবের বছর≠ | 2002 | 1972 |
| প্রবর্তক≠ | Royston, P. & Parmar, M.K.B. | Cox, D. R. |
| ধরন≠ | Parametric survival regression model | Semi-parametric hazard regression model |
| মৌলিক উৎস≠ | 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 ↗ | Cox, D. R. (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B, 34(2), 187–202. DOI ↗ |
| অপর নাম | flexible parametric model, restricted cubic spline survival model, stpm2, Esnek Parametrik Survival Modeli (Royston-Parmar) | cox ph model, proportional hazards model, cox ph regression, Cox Orantılı Tehlikeler Regresyonu |
| সম্পর্কিত≠ | 8 | 3 |
| সারসংক্ষেপ≠ | 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. | Cox proportional hazards regression, introduced by D. R. Cox in 1972, is a semi-parametric model that estimates how one or more covariates affect the hazard — the instantaneous rate of experiencing an event — while leaving the baseline hazard function unspecified. It is the standard multivariable method in survival analysis and produces hazard ratios that quantify the relative risk associated with each predictor. |
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