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A nonparametric test for the equality of counting processes with panel count data

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  • Balakrishnan, N.
  • Zhao, Xingqiu

Abstract

This paper considers the problem of nonparametric comparison of counting processes with panel count data, which arise naturally when recurrent events are considered. For the problem considered, we construct a new nonparametric test statistic based on the nonparametric maximum likelihood estimator of the mean function of the counting processes over observation times. The asymptotic distribution of the proposed statistic is derived and its finite-sample property is examined through Monte Carlo simulations. The simulation results show that the proposed method is good for practical use and also more powerful than the existing nonparametric tests based on the nonparametric maximum pseudo-likelihood estimator. A set of panel count data from a floating gallstone study is analyzed and presented as an illustrative example.

Suggested Citation

  • Balakrishnan, N. & Zhao, Xingqiu, 2010. "A nonparametric test for the equality of counting processes with panel count data," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 135-142, January.
  • Handle: RePEc:eee:csdana:v:54:y:2010:i:1:p:135-142
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    References listed on IDEAS

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    1. Jianguo Sun, 2003. "A nonparametric test for panel count data," Biometrika, Biometrika Trust, vol. 90(1), pages 199-208, March.
    2. Jianguo Sun & Xingwei Tong & Xin He, 2007. "Regression Analysis of Panel Count Data with Dependent Observation Times," Biometrics, The International Biometric Society, vol. 63(4), pages 1053-1059, December.
    3. Ying Zhang, 2006. "Nonparametric k-sample tests with panel count data," Biometrika, Biometrika Trust, vol. 93(4), pages 777-790, December.
    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. Anton Schick & Qiqing Yu, 2000. "Consistency of the GMLE with Mixed Case Interval‐Censored Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(1), pages 45-55, March.
    6. J. Sun & L. J. Wei, 2000. "Regression analysis of panel count data with covariate‐dependent observation and censoring times," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(2), pages 293-302.
    7. Ying Zhang, 2002. "A semiparametric pseudolikelihood estimation method for panel count data," Biometrika, Biometrika Trust, vol. 89(1), pages 39-48, March.
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    Cited by:

    1. Li, Yang & Zhao, Hui & Sun, Jianguo & Kim, KyungMann, 2014. "Nonparametric tests for panel count data with unequal observation processes," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 103-111.
    2. 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.
    3. 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.
    4. Jie Zhou & Haixiang Zhang & Liuquan Sun & Jianguo Sun, 2017. "Joint analysis of panel count data with an informative observation process and a dependent terminal event," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(4), pages 560-584, October.

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