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Estimating the Cumulative incidence Functions under Length-biased Sampling

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  • Jean-Yves Dauxois

    (Crest)

  • Agathe Guilloux

    (Crest)

Abstract

Consider a population of individuals who experience K different causes of death.We observe the ones alive at time t0 and follow them until death or possiblecensoring time. Given this length biased sample, we introduce estimators ofthe cumulative incidence functions of "initial survival times" (i.e. for the entirepopulation) in a competing risks setup. The large sample behavior of our estimatorsis studied and tests for equality of cumulative incidence functions aredeveloped.

Suggested Citation

  • Jean-Yves Dauxois & Agathe Guilloux, 2004. "Estimating the Cumulative incidence Functions under Length-biased Sampling," Working Papers 2004-01, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2004-01
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    References listed on IDEAS

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    1. Dauxois, Jean-Yves, 2000. "A new method for proving weak convergence results applied to nonparametric estimators in survival analysis," Stochastic Processes and their Applications, Elsevier, vol. 90(2), pages 327-334, December.
    2. Jens Lund, 2000. "Sampling Bias in Population Studies—How to Use the Lexis Diagram," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(4), pages 589-604, December.
    3. Ying, Zhiliang, 1989. "A note on the asymptotic properties of the product-limit estimator on the whole line," Statistics & Probability Letters, Elsevier, vol. 7(4), pages 311-314, February.
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    Cited by:

    1. Jean-Yves Dauxois & Agathe Guilloux & Syed N. U. A. Kirmani, 2004. "Estimation in a Competing Risks Proportional Hazards Model Under Length-biased Sampling with Censoring," Working Papers 2004-02, Center for Research in Economics and Statistics.

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