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Estimated quadratic inference function for correlated failure time data

Author

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  • Feifei Yan
  • Yanyan Liu
  • Jianwen Cai
  • Haibo Zhou

Abstract

An estimated quadratic inference function method is proposed for correlated failure time data with auxiliary covariates. The proposed method makes efficient use of the auxiliary information for the incomplete exposure covariates and preserves the property of the quadratic inference function method that requires the covariates to be completely observed. It can improve the estimation efficiency and easily deal with the situation when the cluster size is large. The proposed estimator which minimizes the estimated quadratic inference function is shown to be consistent and asymptotically normal. A chi‐squared test based on the estimated quadratic inference function is proposed to test hypotheses about the regression parameters. The small‐sample performance of the proposed method is investigated through extensive simulation studies. The proposed method is then applied to analyze the Study of Left Ventricular Dysfunction (SOLVD) data as an illustration.

Suggested Citation

  • Feifei Yan & Yanyan Liu & Jianwen Cai & Haibo Zhou, 2023. "Estimated quadratic inference function for correlated failure time data," Biometrics, The International Biometric Society, vol. 79(2), pages 1145-1158, June.
    • Handle: RePEc:bla:biomet:v:79:y:2023:i:2:p:1145-1158
    DOI: 10.1111/biom.13633
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    References listed on IDEAS

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    1. Yanyan Liu & Haibo Zhou & Jianwen Cai, 2009. "Estimated Pseudopartial-Likelihood Method for Correlated Failure Time Data with Auxiliary Covariates," Biometrics, The International Biometric Society, vol. 65(4), pages 1184-1193, December.
    2. Liu, Yanyan & Wu, Yuanshan & Zhou, Haibo, 2010. "Multivariate failure times regression with a continuous auxiliary covariate," Journal of Multivariate Analysis, Elsevier, vol. 101(3), pages 679-691, March.
    3. L. Xue & L. Wang & A. Qu, 2010. "Incorporating Correlation for Multivariate Failure Time Data When Cluster Size Is Large," Biometrics, The International Biometric Society, vol. 66(2), pages 393-404, June.
    4. Wendy F. Greene & Jianwen Cai, 2004. "Measurement Error in Covariates in the Marginal Hazards Model for Multivariate Failure Time Data," Biometrics, The International Biometric Society, vol. 60(4), pages 987-996, December.
    5. Annie Qu & Runze Li, 2006. "Quadratic Inference Functions for Varying-Coefficient Models with Longitudinal Data," Biometrics, The International Biometric Society, vol. 62(2), pages 379-391, June.
    6. Zhaozhi Fan & Xiao-Feng Wang, 2009. "Marginal hazards model for multivariate failure time data with auxiliary covariates," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(7), pages 771-786.
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