Robust Variable Selection in Linear Mixed Models |
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Authors: | Yali Fan Guoyou Qin |
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Institution: | 1. College of Science, University of Shanghai for Science and Technology, Shanghai, China;2. Department of Biostatistics, School of Public Health, Fudan University, Shanghai, China;3. Key Laboratory of Public Health Safety, Ministry of Education of China (Fudan University), Shanghai, China |
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Abstract: | In this article, we develop a robust variable selection procedure jointly for fixed and random effects in linear mixed models for longitudinal data. We propose a penalized robust estimator for both the regression coefficients and the variance of random effects based on a re-parametrization of the linear mixed models. Under some regularity conditions, we show the oracle properties of the proposed robust variable selection method. Simulation study shows the robustness of the proposed method against outliers. In the end, the proposed methods is illustrated in the analysis of a real data set. |
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Keywords: | Linear mixed models Robust method Variable selection |
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