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Regression analysis of clustered panel count data with additive mean models

Author

Listed:
  • Weiwei Wang

    (Zhejiang Gongshang University)

  • Zhiyang Cui

    (Zhejiang Gongshang University)

  • Ruijie Chen

    (Zhejiang Gongshang University)

  • Yijun Wang

    (Zhejiang Gongshang University)

  • Xiaobing Zhao

    (Zhejiang University of Finance and Economics)

Abstract

In biomedical studies, panel count data have been extensively investigated. Such data occur if study subjects are monitored or observed only at some discrete time points during observation periods. In addition, these data may be collected from multiple centers, and study subjects from the same center might be correlated. Limited literature exists for clustered panel count data. Ignoring such cluster effects could result in biased variance estimation. In this paper, two semiparametric additive mean models are proposed for clustered panel count data. The first model contains a common baseline function across all clusters, while the second model features cluster-specific baseline functions. Some estimation equations are derived to estimate the regression parameters of interest for the proposed two models. For the common baseline model, the baseline function is also estimated. Given some regularity conditions, the resulting estimators are shown to be consistent and asymptotically normal. Extensive simulation studies are carried out and indicate that the proposed approaches perform well in finite samples. An application of the China Health and Nutrition Study is also provided for illustration.

Suggested Citation

  • Weiwei Wang & Zhiyang Cui & Ruijie Chen & Yijun Wang & Xiaobing Zhao, 2024. "Regression analysis of clustered panel count data with additive mean models," Statistical Papers, Springer, vol. 65(5), pages 2915-2936, July.
    • Handle: RePEc:spr:stpapr:v:65:y:2024:i:5:d:10.1007_s00362-023-01511-3
    DOI: 10.1007/s00362-023-01511-3
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    References listed on IDEAS

    as
    1. Wang, Yijun & Wang, Weiwei & Zhao, Xiaobing, 2022. "Local logarithm partial likelihood estimation of panel count data model with an unknown link function," Computational Statistics & Data Analysis, Elsevier, vol. 166(C).
    2. 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.
    3. Liang Zhu & Sangbum Choi & Yimei Li & Xuelin Huang & Jianguo Sun & Leslie L. Robison, 2020. "Statistical analysis of clustered mixed recurrent-event data with application to a cancer survivor study," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 820-832, October.
    4. Li, Yang & He, Xin & Wang, Haiying & Zhang, Bin & Sun, Jianguo, 2015. "Semiparametric regression of multivariate panel count data with informative observation times," Journal of Multivariate Analysis, Elsevier, vol. 140(C), pages 209-219.
    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. Zhao, Xingqiu & Tong, Xingwei & Sun, Jianguo, 2013. "Robust estimation for panel count data with informative observation times," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 33-40.
    7. He, Haijin & Pan, Deng & Sun, Liuquan & Li, Yimei & Robison, Leslie L. & Song, Xinyuan, 2017. "Analysis of a fixed center effect additive rates model for recurrent event data," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 186-197.
    8. Liang Zhu & Hui Zhao & Jianguo Sun & Wendy Leisenring & Leslie L. Robison, 2015. "Regression analysis of mixed recurrent-event and panel-count data with additive rate models," Biometrics, The International Biometric Society, vol. 71(1), pages 71-79, March.
    9. Zhao, Xingqiu & Tong, Xingwei, 2011. "Semiparametric regression analysis of panel count data with informative observation times," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 291-300, January.
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