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Computational Statistics

, Volume 34, Issue 1, pp 433–446 | Cite as

A homoscedasticity test for the accelerated failure time model

  • Lili YuEmail author
  • Liang Liu
  • Ding-Geng Chen
Original Paper
  • 45 Downloads

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.

Keywords

Accelerated failure time model Homoscedasticity test Quasi-likelihood ratio test Right censoring Survival analysis 

Notes

Acknowledgements

We are grateful to the editor, associate editor, and two referees for their insightful comments, which significantly improved this manuscript.

Supplementary material

180_2018_840_MOESM1_ESM.pdf (67 kb)
Supplementary Materials The R-code for the new test is available on request from the corresponding author.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Biostatistics, Jiann-Ping Hsu college of Public HealthGeorgia Southern UniversityStatesboroUSA
  2. 2.Department of StatisticsUniversity of GeorgiaAthensUSA
  3. 3.School of Social WorkUNC-Chapel HillChapel HillUSA

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