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Analysis of Survival Data with Dependent CensoringAnalysis of Survival Data Under an Assumed Copula

Analysis of Survival Data with Dependent Censoring: Analysis of Survival Data Under an Assumed... [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.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Analysis of Survival Data with Dependent CensoringAnalysis of Survival Data Under an Assumed Copula

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Publisher
Springer Singapore
Copyright
© The Author(s) 2018
ISBN
978-981-10-7163-8
Pages
41 –55
DOI
10.1007/978-981-10-7164-5_4
Publisher site
See Chapter on Publisher Site

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.]

Published: Apr 6, 2018

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

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