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

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 are analyzed to demonstrate the usefulness of our proposal. We implemented the proposed method in an R "compound.Cox" package.

journal_name

Stat Methods Med Res

authors

Emura T,Chen YH

doi

10.1177/0962280214533378

subject

Has Abstract

pub_date

2016-12-01 00:00:00

pages

2840-2857

issue

6

eissn

0962-2802

issn

1477-0334

pii

0962280214533378

journal_volume

25

pub_type

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