Prediction approaches for partly missing multi-omics covariate data: a literature review and an empirical comparison study
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Publication:6604324
DOI10.1002/wics.1626zbMath1545.62063MaRDI QIDQ6604324
Roman Hornung, Frederik Ludwigs, Anne-Laure Boulesteix, Jonas Hagenberg
Publication date: 12 September 2024
Published in: Wiley Interdisciplinary Reviews. WIREs Computational Statistics (Search for Journal in Brave)
Cites Work
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- Adjusting batch effects in microarray expression data using empirical Bayes methods
- On the necessity and design of studies comparing statistical methods
- Statistical Analysis with Missing Data, Third Edition
- Imputed Factor Regression for High-dimensional Block-wise Missing Data
- Integrating Multisource Block-Wise Missing Data in Model Selection
- Random forests
- Imputations for High Missing Rate Data in Covariates Via Semi-supervised Learning Approach
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