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Analysis of Survival Data with Dependent Censoring pp 41–55Cite as

Analysis of Survival Data Under an Assumed Copula

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Abstract

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.

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Authors and Affiliations

  1. Graduate Institute of Statistics, National Central University, Taoyuan, Taiwan

    Takeshi Emura

  2. Institute of Statistical Science, Academia Sinica, Taipei, Taiwan

    Yi-Hau Chen

Authors
  1. Takeshi Emura
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  2. Yi-Hau Chen
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Emura, T., Chen, YH. (2018). Analysis of Survival Data Under an Assumed Copula. In: Analysis of Survival Data with Dependent Censoring. SpringerBriefs in Statistics(). Springer, Singapore. https://doi.org/10.1007/978-981-10-7164-5_4

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