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Non‐parametric Maximum‐Likelihood Estimation in a Semiparametric Mixture Model for Competing‐Risks Data

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  • I‐SHOU CHANG
  • CHAO A. HSIUNG
  • CHI‐CHUNG WEN
  • YUH‐JENN WU
  • CHE‐CHI YANG

Abstract

. This paper describes our studies on non‐parametric maximum‐likelihood estimators in a semiparametric mixture model for competing‐risks data, in which proportional hazards models are specified for failure time models conditional on cause and a multinomial model is specified for the marginal distribution of cause conditional on covariates. We provide a verifiable identifiability condition and, based on it, establish an asymptotic profile likelihood theory for this model. We also provide efficient algorithms for the computation of the non‐parametric maximum‐likelihood estimate and its asymptotic variance. The success of this method is demonstrated in simulation studies and in the analysis of Taiwan severe acute respiratory syndrome data.

Suggested Citation

  • I‐Shou Chang & Chao A. Hsiung & Chi‐Chung Wen & Yuh‐Jenn Wu & Che‐Chi Yang, 2007. "Non‐parametric Maximum‐Likelihood Estimation in a Semiparametric Mixture Model for Competing‐Risks Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 870-895, December.
    • Handle: RePEc:bla:scjsta:v:34:y:2007:i:4:p:870-895
    DOI: 10.1111/j.1467-9469.2007.00567.x
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    Cited by:

    1. Sangbum Choi & Xuelin Huang, 2014. "Maximum likelihood estimation of semiparametric mixture component models for competing risks data," Biometrics, The International Biometric Society, vol. 70(3), pages 588-598, September.
    2. Chia-Hui Huang, 2019. "Mixture regression models for the gap time distributions and illness–death processes," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(1), pages 168-188, January.
    3. Wycinka Ewa, 2019. "Competing Risk Models of Default in the Presence of Early Repayments," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(2), pages 99-120, June.

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