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Methods for Contrasting Gap Time Hazard Functions: Application to Repeat Liver Transplantation

Author

Listed:
  • Xu Shu

    (Novartis Pharmaceuticals)

  • Douglas E. Schaubel

    (University of Michigan)

Abstract

In studies featuring a sequence of ordered events, gap times between successive events are often of interest. Despite the rich literature in this area, very few methods for comparing gap times have been developed. We propose methods for estimating a hazard ratio connecting the first and second gap times. Specifically, a two-stage procedure is developed based on estimating equations. At the first stage, a proportional hazards model is fitted for the first gap time. Weighted estimating equations are then solved at the second stage to estimate the hazard ratio between the first and second gap times. The proposed estimator has a closed form and, being analogous to a standardized mortality ratio, is easy to interpret. Large sample properties of the proposed estimators are derived, with simulation studies used to evaluate finite sample characteristics. Extension of the approach to accommodate a piecewise constant hazard ratio is considered. The proposed methods are applied to contrast repeat (second) versus primary (first) liver transplants with respect to graft failure, based on national registry data.

Suggested Citation

  • Xu Shu & Douglas E. Schaubel, 2017. "Methods for Contrasting Gap Time Hazard Functions: Application to Repeat Liver Transplantation," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 470-488, December.
  • Handle: RePEc:spr:stabio:v:9:y:2017:i:2:d:10.1007_s12561-016-9168-6
    DOI: 10.1007/s12561-016-9168-6
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    References listed on IDEAS

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    1. Robert L. Strawderman, 2005. "The accelerated gap times model," Biometrika, Biometrika Trust, vol. 92(3), pages 647-666, September.
    2. Huang Y., 2002. "Calibration Regression of Censored Lifetime Medical Cost," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 318-327, March.
    3. Adin-Cristian Andrei & Susan Murray, 2006. "Estimating the quality-of-life-adjusted gap time distribution of successive events subject to censoring," Biometrika, Biometrika Trust, vol. 93(2), pages 343-355, June.
    4. Pang Du & Yihua Jiang & Yuedong Wang, 2011. "Smoothing Spline ANOVA Frailty Model for Recurrent Event Data," Biometrics, The International Biometric Society, vol. 67(4), pages 1330-1339, December.
    5. Strawderman Robert L, 2006. "A Regression Model for Dependent Gap Times," The International Journal of Biostatistics, De Gruyter, vol. 2(1), pages 1-34, January.
    6. Xuelin Huang & Lei Liu, 2007. "A Joint Frailty Model for Survival and Gap Times Between Recurrent Events," Biometrics, The International Biometric Society, vol. 63(2), pages 389-397, June.
    7. van der Laan M.J. & Hubbard A.E. & Robins J.M., 2002. "Locally Efficient Estimation of a Multivariate Survival Function in Longitudinal Studies," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 494-507, June.
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