Feature screening and FDR control with knockoff features for ultrahigh-dimensional right-censored data

Yingli Pan

Computational Statistics & Data Analysis, 2022, vol. 173, issue C

Abstract: A model-free feature screening method for ultrahigh-dimensional right-censored data is advocated. A two-step approach, with the help of knockoff features, is proposed to specify the threshold for feature screening such that the false discovery rate (FDR) is controlled under a prespecified level. The proposed two-step approach enjoys both a sure screening property with high probability and FDR control simultaneously if the prespecified FDR level is greater than or equal to 1/s, where s is the number of active features. The finite sample properties of the newly suggested method are assessed through simulation studies. An application to the mantle cell lymphoma (MCL) study demonstrates the utility of the proposed method in practice.

Keywords: Ultrahigh-dimensional survival data; Feature screening; Knockoff features; FDR control (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:173:y:2022:i:c:s0167947322000846

DOI: 10.1016/j.csda.2022.107504

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