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Analysis of Survival Data with Dependent CensoringCopula Models for Dependent Censoring

Analysis of Survival Data with Dependent Censoring: Copula Models for Dependent Censoring [This chapter provides mathematical infrastructures for copula models, focusing on applications to survival analysis involving dependent censoring. After reviewing the concept of copulas, we introduce measures of dependence, including Kendall’s tau and the cross-ratio function. We also introduce the idea of residual dependence that explains how dependence between event times arises and how it can be modeled by copulas. Finally, we apply copulas for modeling the effect of dependent censoring and analyze the bias of the Cox regression analysis owing to dependent censoring.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Analysis of Survival Data with Dependent CensoringCopula Models for Dependent Censoring

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Publisher
Springer Singapore
Copyright
© The Author(s) 2018
ISBN
978-981-10-7163-8
Pages
27 –40
DOI
10.1007/978-981-10-7164-5_3
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter provides mathematical infrastructures for copula models, focusing on applications to survival analysis involving dependent censoring. After reviewing the concept of copulas, we introduce measures of dependence, including Kendall’s tau and the cross-ratio function. We also introduce the idea of residual dependence that explains how dependence between event times arises and how it can be modeled by copulas. Finally, we apply copulas for modeling the effect of dependent censoring and analyze the bias of the Cox regression analysis owing to dependent censoring.]

Published: Apr 6, 2018

Keywords: Archimedean copula; Clayton’s copula; Cox regression; Cross-ratio function; Gumbel’s copula; Kendall’s tau; Residual dependence; Univariate Cox regression

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