Analysis of Survival Data Under an Assumed Copula

  • Takeshi Emura
  • Yi-Hau Chen
Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)


This chapter introduces statistical methods for analyzing survival data subject to dependent censoring. We review the copula-graphic estimator, parametric likelihood methods, and semi-parametric likelihood methods developed under a variety of copula models. All these approaches employ an assumed copula, a copula function that is completely specified including its parameter value to avoid the non-identifiability.


Burr distribution Competing risk Copula-graphic estimator Maximum likelihood estimator Spline Weibull distribution 


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Copyright information

© The Author(s) 2018

Authors and Affiliations

  • Takeshi Emura
    • 1
  • Yi-Hau Chen
    • 2
  1. 1.Graduate Institute of StatisticsNational Central UniversityTaoyuanTaiwan
  2. 2.Institute of Statistical ScienceAcademia SinicaTaipeiTaiwan

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