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Inference of a time-varying coefficient regression model for multivariate panel count data

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  • Guo, Yuanyuan
  • Sun, Dayu
  • Sun, Jianguo

Abstract

Panel count data consist of the numbers of event occurrences between two consecutive observation times and are prevalent in many areas. Correspondingly a bulk of literature has been developed for the analysis of panel count data with time-independent or time-dependent covariates but assuming time-invariant covariate effects. However, the time-invariant coefficient assumption is too restrictive in reality and fails to represent the time-dynamic association between the covariates and event occurrence rates. In this paper, we discuss regression analysis of multivariate panel count data where both the covariates and their effects may be time-varying. We propose a marginal estimating equation approach combined with the B-splines that approximate the functional forms of the regression coefficients. The asymptotic properties of the proposed estimators are rigorously established. A simulation study is conducted to assess the performance of the proposed estimation procedure and suggests that it works well for practical situations. The proposed methodology is applied to a real dataset that motivated this study.

Suggested Citation

  • Guo, Yuanyuan & Sun, Dayu & Sun, Jianguo, 2022. "Inference of a time-varying coefficient regression model for multivariate panel count data," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:jmvana:v:192:y:2022:i:c:s0047259x22000604
    DOI: 10.1016/j.jmva.2022.105047
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    References listed on IDEAS

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    1. Lu, Minggen & Zhang, Ying & Huang, Jian, 2009. "Semiparametric Estimation Methods for Panel Count Data Using Monotone B-Splines," Journal of the American Statistical Association, American Statistical Association, vol. 104(487), pages 1060-1070.
    2. Zhang, Haixiang & Zhao, Hui & Sun, Jianguo & Wang, Dehui & Kim, KyungMann, 2013. "Regression analysis of multivariate panel count data with an informative observation process," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 71-80.
    3. Jia Yu & Yu Xie, 2021. "Recent trends in the Chinese family: National estimates from 1990 to 2010," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(25), pages 595-608.
    4. X. Joan Hu & Jianguo Sun & Lee‐Jen Wei, 2003. "Regression Parameter Estimation from Panel Counts," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(1), pages 25-43, March.
    5. Hui Zhao & Yang Li & Jianguo Sun, 2013. "Semiparametric analysis of multivariate panel count data with dependent observation processes and a terminal event," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 25(2), pages 379-394, June.
    6. Huadong Zhao & Wanzhu Tu & Zhangsheng Yu, 2018. "A nonparametric time-varying coefficient model for panel count data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(3), pages 640-661, July.
    7. Xin He & Xuenan Feng & Xingwei Tong & Xingqiu Zhao, 2017. "Semiparametric partially linear varying coefficient models with panel count data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(3), pages 439-466, July.
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    Cited by:

    1. Dayu Sun & Yuanyuan Guo & Yang Li & Jianguo Sun & Wanzhu Tu, 2024. "A flexible time-varying coefficient rate model for panel count data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 30(4), pages 721-741, October.

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