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Nonparametric estimation of competing risks models with covariates

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  • Fermanian, Jean-David

Abstract

In competing risks model, several failure times arise potentially. The smallest failure time and its index only are observed. Without specific assumptions, the joint or even the marginal distribution functions of the underlying failure times are not identifiable (A. Tsiatis, Proc. Natl. Acad. Sci. USA 72 (1975) 20). Nonetheless, if each individual is characterized by a "sufficiently informative" set of covariates, these distributions are identifiable under some conditions of regularity (J.J. Heckman and B. Honoré, Biometrika 76 (1989) 325). In this paper, nonparametric kernel estimators of the joint distribution function of failure times conditional on the covariates are proposed. Their weak and strong consistency are discussed.

Suggested Citation

  • Fermanian, Jean-David, 2003. "Nonparametric estimation of competing risks models with covariates," Journal of Multivariate Analysis, Elsevier, vol. 85(1), pages 156-191, April.
  • Handle: RePEc:eee:jmvana:v:85:y:2003:i:1:p:156-191
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    References listed on IDEAS

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    1. McCall, Brian P, 1996. "Unemployment Insurance Rules, Joblessness, and Part-Time Work," Econometrica, Econometric Society, vol. 64(3), pages 647-682, May.
    2. Flinn, Christopher J & Heckman, James J, 1983. "Are Unemployment and Out of the Labor Force Behaviorally Distinct Labor Force States?," Journal of Labor Economics, University of Chicago Press, vol. 1(1), pages 28-42, January.
    3. Sueyoshi, Glenn T., 1992. "Semiparametric proportional hazards estimation of competing risks models with time-varying covariates," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 25-58.
    4. Omori, Yoshiaki, 1998. "The Identifiability of Independent Competing Risks Models with Multiple Spells," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 60(1), pages 107-116, February.
    5. Han, Aaron & Hausman, Jerry A, 1990. "Flexible Parametric Estimation of Duration and Competing Risk Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 5(1), pages 1-28, January-M.
    6. Dario Gasbarra, 2000. "Analysis of Competing Risks by Using Bayesian Smoothing," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(4), pages 605-617.
    7. Powell, James L & Stock, James H & Stoker, Thomas M, 1989. "Semiparametric Estimation of Index Coefficients," Econometrica, Econometric Society, vol. 57(6), pages 1403-1430, November.
    8. Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
    9. Sherman, Robert P, 1993. "The Limiting Distribution of the Maximum Rank Correlation Estimator," Econometrica, Econometric Society, vol. 61(1), pages 123-137, January.
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    Cited by:

    1. Sokbae Lee, 2006. "Identification of a competing risks model with unknown transformations of latent failure times," Biometrika, Biometrika Trust, vol. 93(4), pages 996-1002, December.
    2. Ruixuan Liu, 2016. "A Competing Risks Model with Time-varying Heterogeneity and Simultaneous Failure," Emory Economics 1603, Department of Economics, Emory University (Atlanta).
    3. repec:spr:metrik:v:81:y:2018:i:7:d:10.1007_s00184-018-0662-3 is not listed on IDEAS
    4. 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.

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