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Multiple Imputation for General Missing Data Patterns in the Presence of High-dimensional Data
Multiple imputation (MI) has been widely used for handling missing data in biomedical research. In the presence of high-dimensional data, regularized regression has been used as a natural strategy for building imputation models, but limited research has been conducted for handling general missing da...
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| 出版年: | Sci Rep |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Nature Publishing Group
2016
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4751511/ https://ncbi.nlm.nih.gov/pubmed/26868061 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/srep21689 |
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