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Semiparametric regression analysis of multivariate longitudinal data with informative observation times

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  • Deng, Shirong
  • Liu, Kin-yat
  • Zhao, Xingqiu

Abstract

Multivariate longitudinal data arises when subjects under study may experience several possible related response outcomes. This article proposed a new class of flexible semiparametric models for multivariate longitudinal data with informative observation times through latent variables and completely unspecified link functions, which allows for any functional forms of covariate effects on the intensity functions for the observation processes. A novel estimating equation approach that does not rely on forms of link functions and distributions of frailties is developed. The asymptotic properties for the resulting estimators and the model checking technique for the overall fit of the proposed models are established. The simulation results show that the proposed approach works well. The analysis of skin cancer chemoprevention trial data is provided for illustration.

Suggested Citation

  • Deng, Shirong & Liu, Kin-yat & Zhao, Xingqiu, 2017. "Semiparametric regression analysis of multivariate longitudinal data with informative observation times," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 120-130.
    • Handle: RePEc:eee:csdana:v:107:y:2017:i:c:p:120-130
    DOI: 10.1016/j.csda.2016.10.006
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    References listed on IDEAS

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    1. Sun, Jianguo & Sun, Liuquan & Liu, Dandan, 2007. "Regression Analysis of Longitudinal Data in the Presence of Informative Observation and Censoring Times," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1397-1406, December.
    2. D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
    3. Sun, Jianguo & Park, Do-Hwan & Sun, Liuquan & Zhao, Xingqiu, 2005. "Semiparametric Regression Analysis of Longitudinal Data With Informative Observation Times," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 882-889, September.
    4. Yu Liang & Wenbin Lu & Zhiliang Ying, 2009. "Joint Modeling and Analysis of Longitudinal Data with Informative Observation Times," Biometrics, The International Biometric Society, vol. 65(2), pages 377-384, June.
    5. 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.
    6. Lin D Y & Ying Z, 2001. "Semiparametric and Nonparametric Regression Analysis of Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 103-126, March.
    7. Welsh A.H. & Lin X. & Carroll R.J., 2002. "Marginal Longitudinal Nonparametric Regression: Locality and Efficiency of Spline and Kernel Methods," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 482-493, June.
    8. 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.
    9. 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.
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