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  • 标题:A new copula model-based method for regression analysis of dependent current status data
  • 本地全文:下载
  • 作者:Cui, Qi ; Zhao, Hui ; Sun, Jianguo
  • 期刊名称:Statistics and Its Interface
  • 印刷版ISSN:1938-7989
  • 电子版ISSN:1938-7997
  • 出版年度:2018
  • 卷号:11
  • 期号:3
  • 页码:463-471
  • DOI:10.4310/SII.2018.v11.n3.a9
  • 语种:English
  • 出版社:International Press
  • 摘要:This paper discusses regression analysis of current status data, which arise when the occurrence of the failure event of interest is observed only once or the occurrence time is either left- or right-censored [5, 11]. Many authors have investigated the problem, however, most of the existing methods are parametric or apply only to limited situations such that the failure time and the observation time have to be independent. In particular, Ma et al. [7] recently proposed a copula-based procedure for the situation where the failure time and the observation time are allowed to be dependent but their association needs to be known. To address this restriction, we present a new two-step estimation procedure that allows one to estimate the association parameter in addition to estimation of other unknown parameters. The asymptotic properties of the resulting estimators are established and a simulation study is conducted and suggests that the proposed method performs well for practical situations. Also an illustrative example is provided.
  • 关键词:copula model; current status data; informative censoring; proportional hazards model
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