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A homoscedasticity test for the accelerated failure time model

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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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Acknowledgements

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

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Authors and Affiliations

  1. Department of Biostatistics, Jiann-Ping Hsu college of Public Health, Georgia Southern University, Statesboro, GA, 30460, USA

    Lili Yu

  2. Department of Statistics, University of Georgia, Athens, GA, 30602, USA

    Liang Liu

  3. School of Social Work, UNC-Chapel Hill, Chapel Hill, NC, 27599, USA

    Ding-Geng Chen

Authors
  1. Lili Yu
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  2. Liang Liu
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  3. Ding-Geng Chen
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Corresponding author

Correspondence to Lili Yu.

Electronic supplementary material

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Supplementary Materials

The R-code for the new test is available on request from the corresponding author.

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Yu, L., Liu, L. & Chen, DG. A homoscedasticity test for the accelerated failure time model. Comput Stat 34, 433–446 (2019). https://doi.org/10.1007/s00180-018-0840-9

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  • DOI: https://doi.org/10.1007/s00180-018-0840-9

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