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文章基本信息

  • 标题:Censored count data regression with missing censoring information
  • 本地全文:下载
  • 作者:Bilel Bousselmi ; Jean-François Dupuy ; Abderrazek Karoui
  • 期刊名称:Electronic Journal of Statistics
  • 印刷版ISSN:1935-7524
  • 出版年度:2021
  • 卷号:15
  • 期号:2
  • 页码:4343-4383
  • DOI:10.1214/21-EJS1897
  • 语种:English
  • 出版社:Institute of Mathematical Statistics
  • 摘要:We investigate estimation in Poisson regression model when the count response is right-censored and the censoring indicators are missing at random. We propose several estimators based on the regression calibration, multiple imputation and augmented inverse probability weighting methods. Under appropriate regularity conditions, we prove the consistency of our estimators and we derive their asymptotic distributions. Simulation experiments are carried out to investigate the finite sample behaviour and relative performance of the proposed estimates. These estimates are illustrated on a real data set.
  • 关键词:62F12; 62J12; asymptotic properties; Augmented inverse probability weighting; missing data; multiple imputation; Poisson regression; regression calibration; simulations
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