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Parametric estimation of association in bivariate failure-time data subject to competing risks: sensitivity to underlying assumptions

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Listed:
  • Jeongyong Kim

    (Johns Hopkins Bloomberg School of Public Health)

  • Karen Bandeen-Roche

    (Johns Hopkins Bloomberg School of Public Health)

Abstract

There has arisen a considerable body of research addressing the estimation of association between paired failure times in the presence of competing risks. In a 2002 paper, Bandeen-Roche and Liang proposed the conditional cause-specific hazard ratio (CCSHR) as a measure of this association and a parametric method by which to estimate it. The method features an interpretable decomposition of the CCSHR into factors describing the association between a pair’s times to first failure among multiple failure causes and the association in pair members’ propensities to fail due to a common cause. There were indications of sensitivity to model assumptions, however, in the 2002 work. Here we report a detailed study of the method’s sensitivity to its parametric assumptions. We conclude that the method’s performance is most sensitive to mis-specification of temporality in the association between pair members’ first-failure times and of correlation between propensity to fail early or late and the propensity to fail of a specific cause. Implications for methods development are highlighted.

Suggested Citation

  • Jeongyong Kim & Karen Bandeen-Roche, 2019. "Parametric estimation of association in bivariate failure-time data subject to competing risks: sensitivity to underlying assumptions," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(2), pages 259-279, April.
    • Handle: RePEc:spr:lifeda:v:25:y:2019:i:2:d:10.1007_s10985-018-9438-3
    DOI: 10.1007/s10985-018-9438-3
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    References listed on IDEAS

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