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The Model and the Inference for the Clustered Recurrent Event

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  • Kang Fang Yuan

    (School of Applied Science, Beijing Information Science and Technology University, Beijing 100192, China)

Abstract

In medical studies, subjects may experience one event of interest repeatedly over a period of time, which is termed recurrent event. The examples include multiple infection episodes and tumor recurrences. In many other settings, the subjects may be clustered according to some property, because they are correlated owning to some common factors.

Suggested Citation

  • Kang Fang Yuan, 2018. "The Model and the Inference for the Clustered Recurrent Event," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 5(4), pages 106-107, February.
    • Handle: RePEc:adp:jbboaj:v:5:y:2018:i:4:p:106-107
    DOI: 10.19080/BBOAJ.2018.05.555667
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    References listed on IDEAS

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    1. 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.
    2. Dandan Liu & Douglas E. Schaubel & John D. Kalbfleisch, 2012. "Computationally Efficient Marginal Models for Clustered Recurrent Event Data," Biometrics, The International Biometric Society, vol. 68(2), pages 637-647, June.
    3. Robert L. Strawderman, 2005. "The accelerated gap times model," Biometrika, Biometrika Trust, vol. 92(3), pages 647-666, September.
    4. Donglin Zeng & D. Y. Lin, 2006. "Efficient estimation of semiparametric transformation models for counting processes," Biometrika, Biometrika Trust, vol. 93(3), pages 627-640, September.
    Full references (including those not matched with items on IDEAS)

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