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Additive Hazard Regression for the Analysis of Clustered Survival Data from Case-Cohort Studies

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  • June Liu
  • Yi Zhang
  • Antonio Di Crescenzo

Abstract

The case-cohort design is an effective and economical method in large cohort studies, especially when the disease rate is low. Case-cohort design in most of the existing literature is mainly used to analyze the univariate failure time data. But in practice, multivariate failure time data are commonly encountered in biomedical research. In this paper, we will propose methods based on estimating equation method for case-cohort designs for clustered survival data. By introducing the event failure rate, three different weight functions are constructed. Then, three estimating equations and parameter estimators are presented. Furthermore, consistency and asymptotic normality of the proposed estimators are established. Finally, the simulation results show that the proposed estimation procedure has reasonable finite sample behaviors.

Suggested Citation

  • June Liu & Yi Zhang & Antonio Di Crescenzo, 2020. "Additive Hazard Regression for the Analysis of Clustered Survival Data from Case-Cohort Studies," Journal of Mathematics, Hindawi, vol. 2020, pages 1-10, July.
    • Handle: RePEc:hin:jjmath:9587870
    DOI: 10.1155/2020/9587870
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