Feature screening under missing indicator imputation with non-ignorable missing response

Jing Zhang, Qihua Wang and Jian Kang

Computational Statistics & Data Analysis, 2020, vol. 149, issue C

Abstract: This article develops a model-free variable screening technique with the non-ignorable missing response in ultrahigh-dimensional data analysis. Based on the common logistic model assumption of the propensity function, a novel screening procedure is proposed by borrowing hidden information of missingness indicator such that any variable screening method for ultrahigh-dimensional covariates with full data can be applied to the non-ignorable missing response case. And it is shown that the sure screening property can be kept as long as the corresponding screening method for full data is of sure screening property. The finite sample performances of the proposed method are demonstrated via some simulations and analysis of functional neuroimaging data.

Keywords: Model-free; Non-ignorable nonresponse; Sure screening property; Ultrahigh dimensionality; Variable screening (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:149:y:2020:i:c:s0167947320300669

DOI: 10.1016/j.csda.2020.106975

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