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An additive hazards frailty model with semi-varying coefficients

Author

Listed:
  • Zhongwen Zhang

    (Binzhou Medical University)

  • Xiaoguang Wang

    (Dalian University of Technology)

  • Yingwei Peng

    (Queen’s University)

Abstract

Proportional hazards frailty models have been extensively investigated and used to analyze clustered and recurrent failure times data. However, the proportional hazards assumption in the models may not always hold in practice. In this paper, we propose an additive hazards frailty model with semi-varying coefficients, which allows some covariate effects to be time-invariant while other covariate effects to be time-varying. The time-varying and time-invariant regression coefficients are estimated by a set of estimating equations, whereas the frailty parameter is estimated by the moment method. The large sample properties of the proposed estimators are established. The finite sample performance of the estimators is examined by simulation studies. The proposed model and estimation are illustrated with an analysis of data from a rehospitalization study of colorectal cancer patients.

Suggested Citation

  • Zhongwen Zhang & Xiaoguang Wang & Yingwei Peng, 2022. "An additive hazards frailty model with semi-varying coefficients," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(1), pages 116-138, January.
    • Handle: RePEc:spr:lifeda:v:28:y:2022:i:1:d:10.1007_s10985-021-09540-6
    DOI: 10.1007/s10985-021-09540-6
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    References listed on IDEAS

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