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Estimating a Survival Distribution with Current Status Data and High-Dimensional Covariates

Author

Listed:
  • Mark van der Laan

    (Division of Biostatistics, School of Public Health, University of California, Berkeley)

  • Aad van der Vaart

    (Free University, Amsterdam, The Netherlands)

Abstract

We consider the inverse problem of estimating a survival distribution when the survival times are only observed to be in one of the intervals of a random bisection of the time axis. We are particularly interested in the case that high-dimensional and/or time-dependent covariates are available, and/or the survival events and censoring times are only conditionally independent given the covariate process. The method of estimation consists of regularizing the survival distribution by taking the primitive function or smoothing, estimating the regularized parameter by using estimating equations, and finally recovering an estimator for the parameter of interest.

Suggested Citation

  • Mark van der Laan & Aad van der Vaart, 2004. "Estimating a Survival Distribution with Current Status Data and High-Dimensional Covariates," U.C. Berkeley Division of Biostatistics Working Paper Series 1156, Berkeley Electronic Press.
    • Handle: RePEc:bep:ucbbio:1156
    Note: oai:bepress.com:ucbbiostat-1156
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