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Dynamic regression with recurrent events

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  • J. E. Soh
  • Yijian Huang

Abstract

Recurrent events often arise in follow‐up studies where a subject may experience multiple occurrences of the same event. Most regression models with recurrent events tacitly assume constant effects of covariates over time, which may not be realistic in practice. To address time‐varying effects, we develop a dynamic regression model to target the mean frequency of recurrent events. We propose an estimation procedure which fully exploits observed data. Consistency and weak convergence of the proposed estimator are established. Simulation studies demonstrate that the proposed method works well, and two real data analyses are presented for illustration.

Suggested Citation

  • J. E. Soh & Yijian Huang, 2019. "Dynamic regression with recurrent events," Biometrics, The International Biometric Society, vol. 75(4), pages 1264-1275, December.
    • Handle: RePEc:bla:biomet:v:75:y:2019:i:4:p:1264-1275
    DOI: 10.1111/biom.13105
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