Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Mfumo wa Kuongeza kasi ya Kushindwa kwa Wakati (AFT)× | Kipimo cha Log-Rank cha Kulinganisha Milia ya Uhai× | |
|---|---|---|
| Nyanja | Uchanganuzi wa Uhai | Uchanganuzi wa Uhai |
| Familia | Survival analysis | Survival analysis |
| Mwaka wa asili≠ | 1992 | 1966 |
| Mwanzilishi≠ | Wei, L. J. (seminal review 1992); origins in parametric survival literature | Mantel, N. |
| Aina≠ | Parametric survival regression model | Non-parametric hypothesis test |
| Chanzo asilia≠ | 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 ↗ | 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 ↗ |
| Majina mbadala≠ | AFT model, parametric survival regression, Hızlandırılmış Başarısızlık Zamanı Modeli (AFT) | Mantel log-rank test, Mantel-Cox test, log-rank sağkalım testi, Log-Rank Testi |
| Zinazohusiana≠ | 3 | 2 |
| Muhtasari≠ | 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 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. |
| ScholarGateSeti ya data ↗ |
|
|