A homoscedasticity test for the accelerated failure time model
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The semiparametric accelerated failure time (AFT) model is a popular linear model in survival analysis. AFT model and its associated inference methods assume homoscedasticity of the survival data. It is shown that violation of this assumption will lead to inefficient parameter estimation and anti-conservative confidence interval estimation, and thus, misleading conclusions in survival data analysis. However, there is no valid statistical test proposed to test the homoscedasticity assumption. In this paper, we propose the first novel quasi-likelihood ratio test for the homoscedasticity assumption in the AFT model. Simulation studies show the test performs well. A real dataset is used to demonstrate the usefulness of the developed test.
KeywordsAccelerated failure time model Homoscedasticity test Quasi-likelihood ratio test Right censoring Survival analysis
We are grateful to the editor, associate editor, and two referees for their insightful comments, which significantly improved this manuscript.