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A class of box-cox transformation models for recurrent event data with a terminal event

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Abstract

In this article, we study a class of Box-Cox transformation models for recurrent event data in the presence of terminal event, which includes the proportional means models as special cases. Estimating equation approaches and the inverse probability weighting technique are used for estimation of the regression parameters. The asymptotic properties of the resulting estimators are established. The finite sample behavior of the proposed methods is examined through simulation studies, and an application to a heart failure study is presented to illustrate the proposed method.

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Acknowledgements

We thank the referees for their time and comments.

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Authors and Affiliations

  1. School of Mathematics, Capital Normal University, Beijing, 100048, P. R. China

    Jie Zhou

  2. Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, P. R. China

    Jun Zhu & Liu Quan Sun

Authors
  1. Jie Zhou
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  2. Jun Zhu
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  3. Liu Quan Sun
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Corresponding author

Correspondence to Jie Zhou.

Additional information

Supported by National Natural Science Foundation of China (Grant Nos. 11301355, 11671275, 11231010 and 11690015), Key Laboratory of RCSDS, CAS (Grant No. 2008DP173182), BCMIIS

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Zhou, J., Zhu, J. & Sun, L.Q. A class of box-cox transformation models for recurrent event data with a terminal event. Acta. Math. Sin.-English Ser. 33, 1048–1060 (2017). https://doi.org/10.1007/s10114-017-6221-4

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  • DOI: https://doi.org/10.1007/s10114-017-6221-4

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