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| 加速故障時間(AFT)モデル× | ワイブル生存回帰 (Weibull Parametric Survival Regression)× | |
|---|---|---|
| 分野 | 生存時間解析 | 生存時間解析 |
| 系統 | Survival analysis | Survival analysis |
| 提唱年≠ | 1992 | 1951 |
| 提唱者≠ | Wei, L. J. (seminal review 1992); origins in parametric survival literature | Waloddi Weibull |
| 種類≠ | Parametric survival regression model | Fully parametric survival regression model |
| 原典≠ | Wei, L. J. (1992). The Accelerated Failure Time Model: A Useful Alternative to the Cox Regression Model in Survival Analysis. Statistics in Medicine, 11(14–15), 1871–1879. DOI ↗ | Kalbfleisch, J. D. & Prentice, R. L. (2002). The Statistical Analysis of Failure Time Data (2nd ed.). Wiley. DOI ↗ |
| 別名≠ | AFT model, parametric survival regression, Hızlandırılmış Başarısızlık Zamanı Modeli (AFT) | weibull aft model, weibull survival model, parametric survival regression, Weibull Regresyonu — Parametrik Hayatta Kalma |
| 関連≠ | 3 | 4 |
| 概要≠ | The Accelerated Failure Time model is a parametric regression approach to survival analysis — formally reviewed and advocated by L. J. Wei in 1992 — in which covariates act as multiplicative factors that directly stretch or compress the time-to-event scale. Unlike the Cox proportional-hazards model, which models how covariates shift the hazard rate, AFT models express the covariate effect as an acceleration or deceleration of the time axis itself. | Weibull regression is a fully parametric survival model, formalised by Kalbfleisch and Prentice, that assumes survival times follow a Weibull distribution. A shape parameter controls whether the hazard increases, decreases, or remains constant over time, while covariates shift the scale of the distribution to express how predictors affect survival. |
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