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A new linear regression-like residual for survival analysis, with application to genome wide association studies of time-to-event data

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  • Veronica J Vieland
  • Sang-Cheol Seok
  • William C L Stewart

Abstract

In linear regression, a residual measures how far a subject's observation is from expectation; in survival analysis, a subject's Martingale or deviance residual is sometimes interpreted similarly. Here we consider ways in which a linear regression-like interpretation is not appropriate for Martingale and deviance residuals, and we develop a novel time-to-event residual which does have a linear regression-like interpretation. We illustrate the utility of this new residual via simulation of a time-to-event genome-wide association study, motivated by a real study seeking genetic modifiers of Duchenne Muscular Dystrophy. By virtue of its linear regression-like characteristics, our new residual may prove useful in other contexts as well.

Suggested Citation

  • Veronica J Vieland & Sang-Cheol Seok & William C L Stewart, 2020. "A new linear regression-like residual for survival analysis, with application to genome wide association studies of time-to-event data," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-15, May.
    • Handle: RePEc:plo:pone00:0232300
    DOI: 10.1371/journal.pone.0232300
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