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A new nonparametric quantile estimate for length-biased data with competing risks

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  • Zhang, Feipeng
  • Tan, Zhong

Abstract

The paper aims to propose a new nonparametric quantile estimate for length-biased data with competing risks. A new EM-algorithm for directly estimating nonparametric cumulative incidence function of competing risks is presented. The good performance of the proposed estimator is investigated through simulation studies. A real data example is also provided.

Suggested Citation

  • Zhang, Feipeng & Tan, Zhong, 2015. "A new nonparametric quantile estimate for length-biased data with competing risks," Economics Letters, Elsevier, vol. 137(C), pages 10-12.
    • Handle: RePEc:eee:ecolet:v:137:y:2015:i:c:p:10-12
    DOI: 10.1016/j.econlet.2015.10.023
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    References listed on IDEAS

    as
    1. L. Peng & J. P. Fine, 2007. "Nonparametric quantile inference with competing–risks data," Biometrika, Biometrika Trust, vol. 94(3), pages 735-744.
    2. Dauxois, Jean-Yves & Guilloux, Agathe, 2008. "Nonparametric inference under competing risks and selection-biased sampling," Journal of Multivariate Analysis, Elsevier, vol. 99(4), pages 589-605, April.
    3. Lancaster,Tony, 1992. "The Econometric Analysis of Transition Data," Cambridge Books, Cambridge University Press, number 9780521437899.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Shi, Jianhua & Ma, Huijuan & Zhou, Yong, 2018. "The nonparametric quantile estimation for length-biased and right-censored data," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 150-158.
    2. Zhang, Feipeng & Yang, Jiejing & Ye, Min, 2020. "A nonparametric maximum likelihood estimation for biased-sampling data with zero-inflated truncation," Economics Letters, Elsevier, vol. 194(C).

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    More about this item

    Keywords

    Competing risks; Quantile; EM algorithm; Length-biased data;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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