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Nonparametric Estimation of Cumulative Incidence Functions for Competing Risks Data with Missing Cause of Failure

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In this paper, we develop a fully nonparametric approach for the estimation of the cumulative incidence function with Missing At Random right-censored competing risks data. We obtain results on the pointwise asymptotic normality as well as the uniform convergence rate of the proposed nonparametric estimator. A simulation study that serves two purposes is provided. First, it illustrates in details how to implement our proposed nonparametric estimator. Secondly, it facilitates a comparison of the nonparametric estimator to a parametric counterpart based on the estimator of Lu and Liang (2008). The simulation results are generally very encouraging.

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  • Effraimidis, Georgios & Dahl, Christian M., 2013. "Nonparametric Estimation of Cumulative Incidence Functions for Competing Risks Data with Missing Cause of Failure," Discussion Papers on Economics 21/2013, University of Southern Denmark, Department of Economics.
    • Handle: RePEc:hhs:sdueko:2013_021
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    1. Bordes, Laurent & Gneyou, Kossi Essona, 2011. "Uniform convergence of nonparametric regressions in competing risk models with right censoring," Statistics & Probability Letters, Elsevier, vol. 81(11), pages 1654-1663, November.
    2. Zonghui Hu & Dean A. Follmann & Jing Qin, 2010. "Semiparametric dimension reduction estimation for mean response with missing data," Biometrika, Biometrika Trust, vol. 97(2), pages 305-319.
    3. Hansen, Bruce E., 2008. "Uniform Convergence Rates For Kernel Estimation With Dependent Data," Econometric Theory, Cambridge University Press, vol. 24(3), pages 726-748, June.
    4. Li, Qi & Racine, Jeffrey S, 2008. "Nonparametric Estimation of Conditional CDF and Quantile Functions With Mixed Categorical and Continuous Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 423-434.
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    More about this item

    Keywords

    Cumulative incidence function; Inverse probability weighting; Kernel estimation; Local linear estimation; Martingale central limit theorem;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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