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Title: | Recent advances in copula-based methods for dependent censoring | Authors: | Crommen, Gilles Deresa, Negera Wakgari D'HAEN, Myrthe Ding, Jie Willems, Ilias VAN KEILEGOM, Ingrid |
Issue Date: | 2025 | Source: | Sort (Barcelona), 49 (1) , p. 3 -42 | Status: | Early view | Abstract: | When modeling time-to-event data that are subject to right censoring, it is commonly assumed that the survival time T and the censoring time C are independent. However, this assumption frequently fails in practice, leading to biased estimators and testing procedures having invalid type 1 error rates. To overcome this issue, several models relaxing the independent censoring assumption have been proposed in the literature. Among these, copula-based approaches have become popular due to their ability to separately model the marginal distributions of T and C and their dependence structure. This review paper gives a comprehensive overview of recent advances in copula-based methods for dependent censoring, along with a discussion of the most important historical papers on this topic. As it is well known that the distribution of (T,C) (and hence of T) is not identifed in a fully nonparametric way, we examine different strategies to achieve model identifability. These strategies consist of imposing assumptions on either the copula or the marginal distributions of T and C. Both of these approaches will be discussed, with and without covariates. We also consider the case where a dependent censoring time is accompanied by an additional latent independent censoring time. Lastly, we briefy explain alternative approaches that are not based on copulas. MSC: 62Nxx, 62-02. | Keywords: | Copula;Dependent censoring;Identifability;Survival analysis. | Document URI: | http://hdl.handle.net/1942/46331 | ISSN: | 1696-2281 | e-ISSN: | 2013-8830 | DOI: | 10.57645/20.8080.02.21 | ISI #: | 001510030900001 | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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49.1.1.Crommen-etal.pdf Restricted Access | Early view | 1.3 MB | Adobe PDF | View/Open Request a copy |
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