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Efficient estimation for additive hazards regression with bivariate current status data

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Abstract

This paper discusses efficient estimation for the additive hazards regression model when only bivariate current status data are available. Current status data occur in many fields including demographical studies and tumorigenicity experiments (Keiding, 1991; Sun, 2006) and several approaches have been proposed for the additive hazards model with univariate current status data (Lin et al., 1998; Martinussen and Scheike, 2002). For bivariate data, in addition to facing the same problems as those with univariate data, one needs to deal with the association or correlation between two related failure time variables of interest. For this, we employ the copula model and an efficient estimation procedure is developed for inference. Simulation studies are performed to evaluate the proposed estimates and suggest that the approach works well in practical situations. An illustrative example is provided.

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Authors and Affiliations

  1. School of Mathematical Sciences, Beijing Normal University, Beijing, 100875, China

    XingWei Tong

  2. School of Mathematical Sciences, Capital Normal University, Beijing, 100048, China

    Tao Hu

  3. School of Mathematics, Jilin University, Changchun, 130012, China

    JianGuo Sun

  4. Department of Statistics, University of Missouri, Columbia, MO, 65211, USA

    JianGuo Sun

Authors
  1. XingWei Tong
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  2. Tao Hu
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  3. JianGuo Sun
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Correspondence to XingWei Tong.

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Tong, X., Hu, T. & Sun, J. Efficient estimation for additive hazards regression with bivariate current status data. Sci. China Math. 55, 763–774 (2012). https://doi.org/10.1007/s11425-012-4381-3

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  • DOI: https://doi.org/10.1007/s11425-012-4381-3

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