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 Resjournal_title
Statistical methods in medical researchauthors
Emura T,Chen YHdoi
10.1177/0962280214533378subject
Has Abstractpub_date
2016-12-01 00:00:00pages
2840-2857issue
6eissn
0962-2802issn
1477-0334pii
0962280214533378journal_volume
25pub_type
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