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Metrika

, Volume 81, Issue 5, pp 523–547 | Cite as

Joint analysis of recurrent event data with additive–multiplicative hazards model for the terminal event time

  • Miao Han
  • Liuquan Sun
  • Yutao Liu
  • Jun Zhu
Article
  • 114 Downloads

Abstract

Recurrent event data are often collected in longitudinal follow-up studies. In this article, we propose a semiparametric method to model the recurrent and terminal events jointly. We present an additive–multiplicative hazards model for the terminal event and a proportional intensity model for the recurrent events, and a shared frailty is used to model the dependence between the recurrent and terminal events. We adopt estimating equation approaches for inference, and the asymptotic properties of the resulting estimators are established. The finite sample behavior of the proposed estimators is evaluated through simulation studies. An application to a medical cost study of chronic heart failure patients from the University of Virginia Health System is illustrated.

Keywords

Additive–multiplicative hazard model Estimating equation Frailty Recurrent events Terminal event 

Notes

Acknowledgements

The authors would like to thank the reviewers for their constructive and insightful comments and suggestions that greatly improved the paper. This research was partly supported by the National Natural Science Foundation of China (Grant Nos. 11601307, 11771431 and 11690015) and Key Laboratory of RCSDS, CAS (No. 2008DP173182).

Compliance with ethical standards

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Statistics and ManagementShanghai University of Finance and EconomicsShanghaiPeople’s Republic of China
  2. 2.Institute of Applied Mathematics, Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijingPeople’s Republic of China
  3. 3.University of Chinese Academy of SciencesBeijingPeople’s Republic of China
  4. 4.School of Statistics and MathematicsCentral University of Finance and EconomicsBeijingPeople’s Republic of China

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