Gene selection for survival data under dependent censoring: a copula-based approach

Takeshi Emura and Yi-Hau Chen

MPRA Paper from University Library of Munich, Germany

Abstract: Dependent censoring arises in biomedical studies when the survival outcome of interest is censored by competing risks. In survival data with microarray gene expressions, gene selection based on the univariate Cox regression analyses has been used extensively in medical research, which however, is only valid under the independent censoring assumption. In this paper, we first consider a copula-based framework to investigate the bias caused by dependent censoring on gene selection. Then, we utilize the copula-based dependence model to develop an alternative gene selection procedure. Simulations show that the proposed procedure adjusts for the effect of dependent censoring and thus outperforms the existing method when dependent censoring is indeed present. The non-small-cell lung cancer data is analyzed to demonstrate the usefulness of our proposal. We implemented the proposed method in an R “compound.Cox” package.

Keywords: Bivariate survival distribution; Competing risk; Compound covariate prediction; Cox regression; Cross validation; Frailty, Kendall’s tau (search for similar items in EconPapers)
JEL-codes: C12 C13 C14 C34 (search for similar items in EconPapers)
Date: 2014-05-17
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:58043

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