Accelerated failure time model

Analyzing Toxicity Data Using Statistical Models for Time-To-Death: An Introduction

Published in Michael C. Newman, Alan W. McIntosh, Metal Ecotoxicology, 2020

Any statistical model makes assumptions that should be checked as part of a careful analysis. If Weibull or exponential distributions are used in an accelerated failure time model, we assume that: Hazards are proportional.Then an accelerated failure time model makes three major assumptions:Baseline hazard distribution is correctly specified.Response to the covariates is correctly specified.Observations are independent.

Reliability aspects of a series load–sharing system

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Published in Stein Haugen, Anne Barros, Coen van Gulijk, Trond Kongsvik, Jan Erik Vinnem, Safety and Reliability – Safe Societies in a Changing World, 2018

V.V. Krivtsov, S.V. Amari, V.I. Gurevich

Let h(t;L) be the load–dependent failure rate of a component. Two commonly used models relating failure time to a load level are: the Proportional Hazard Model (PHM) and the Accelerated Failure Time Model (AFTM).

The impact of speech-based texting on drivers' braking reaction and deceleration duration in the car-following scenario

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Published in Journal of Transportation Safety & Security, 2019

Hui Zhang, Dalin Qian, Xiaobao Yang, Chunfu Shao

The accelerated failure time model (AFT) is often used to analyze the effect covariates in hazard-based duration models (Washington, Karlaftis, & Mannering, 2011). In the AFT model, the assumption is that the relationship of logarithm of survival time and the covariates is linear, and yielding the linear model:Where, is a vector of covariates, is a vector of estimable parameters and is the error term. The AFT model is expressed as:

Accelerated failure time model

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