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| Modello del Tempo di Fallimento Accelerato (AFT)× | Stima di Kaplan-Meier della Sopravvivenza× | |
|---|---|---|
| Campo | Analisi di sopravvivenza | Analisi di sopravvivenza |
| Famiglia | Survival analysis | Survival analysis |
| Anno di origine≠ | 1992 | 1958 |
| Ideatore≠ | Wei, L. J. (seminal review 1992); origins in parametric survival literature | Kaplan, E. L. & Meier, P. |
| Tipo≠ | Parametric survival regression model | Non-parametric survival estimator |
| Fonte seminale≠ | 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 ↗ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| Alias | AFT model, parametric survival regression, Hızlandırılmış Başarısızlık Zamanı Modeli (AFT) | product-limit estimator, km curve, kaplan-meier sağkalım analizi |
| Correlati≠ | 3 | 2 |
| Sintesi≠ | 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. | The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups. |
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