Journal of Guangxi Normal University(Natural Science Edition) ›› 2022, Vol. 40 ›› Issue (1): 139-149.doi: 10.16088/j.issn.1001-6600.2021060906

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Semiparametric Rate Models for Recurrent Event Data with Cure Rate via Empirical Likelihood

LIU Yu, ZHOU Wen, LI Ni*   

  1. School of Mathematics and Statistics, Hainan Normal University, Haikou Hainan 571158, China
  • Received:2021-06-09 Revised:2021-08-03 Online:2022-01-25 Published:2022-01-24

Abstract: With the continuous development of medical science, recently some diseases that have been considered impossible to be cured before, are found to be possibly cured and will not recur after a certain period. This paper proposes an empirical likelihood method based on semiparametric rate model for recurrent event data with cure rate. An empirical likelihood ratio statistic is introduced for the regression parameters and the Wilk’s theorem is established. By comparing the proposed empirical likelihood method with normal approximation method when the sample size is small, simulation studies are given. Finally, this method is applied to a bladder cancer dataset.

Key words: semiparametric rate model, cure rate, Wilk’s theorem, empirical likelihood

CLC Number: 

  • O212.1
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