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Semiparametric analysis of competing risks data with covariate measurement error

Author

Listed:
  • Akurathi Jayanagasri

    (University of Hyderabad)

  • S. Anjana

    (University of Hyderabad)

Abstract

This paper deals with the competing risks data with covariate measurement error. A semiparametric linear transformation model for the right-censored competing risks data when the covariates are measured with error is proposed. The parameters involved in the model are estimated using a set of estimating equations. An adaptable simulation extrapolation (SIMEX) technique is employed to handle the covariate measurement error. Simulation studies are conducted, to examine the finite sample properties of the estimators. Also, we demonstrated the proposed method using a real dataset.

Suggested Citation

  • Akurathi Jayanagasri & S. Anjana, 2025. "Semiparametric analysis of competing risks data with covariate measurement error," Computational Statistics, Springer, vol. 40(2), pages 651-682, February.
    • Handle: RePEc:spr:compst:v:40:y:2025:i:2:d:10.1007_s00180-024-01502-4
    DOI: 10.1007/s00180-024-01502-4
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    References listed on IDEAS

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