A homoscedasticity test for the accelerated failure time model

Authors

Lili Yu, Georgia Southern University, Jiann-Ping Hsu College of Public HealthFollow
Liang Liu, University of GeorgiaFollow
Ding-Geng Chen, University of North Carolina, Chapel HillFollow

Document Type

Article

Publication Date

9-27-2018

Publication Title

Computational Statistics

DOI

10.1007/s00180-018-0840-9

ISSN

1613-9658

Abstract

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.

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Recommended Citation

Yu, Lili, Liang Liu, Ding-Geng Chen. 2018. "A homoscedasticity test for the accelerated failure time model." Computational Statistics, 34: 433-446: Springer. doi: 10.1007/s00180-018-0840-9
https://digitalcommons.georgiasouthern.edu/bee-facpubs/206