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Keywords = Buckley James estimator

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11 pages, 624 KB  
Article
Estimating Covariances and Goodness of Fit Plots for Accelerated Failure Time Models
by David J. Olive and Sanjuka Johana Lemonge
Axioms 2026, 15(1), 15; https://doi.org/10.3390/axioms15010015 (registering DOI) - 25 Dec 2025
Abstract
Let the response variable Y be the time until an event such as death. Assume that there are p predictors x1,,xp and that the response variable is right censored. Several survival regression models, including accelerated failure time [...] Read more.
Let the response variable Y be the time until an event such as death. Assume that there are p predictors x1,,xp and that the response variable is right censored. Several survival regression models, including accelerated failure time models, have the form Z=log(Y)=αZ+xiTβZ+e. This paper gives a simple method for estimating the covariances Cov(xi,Z) for some of these models. Plots are given for checking the goodness of fit of accelerated failure time models. Plots for checking the proportional hazards regression model are often harder to use. Full article
(This article belongs to the Special Issue Probability Theory and Stochastic Processes: Theory and Applications)
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