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Multiple Imputation: An Iterative Regression Imputation
International Journal of Mathematical Sciences and Optimization: Theory and Applications, 2023Multiple imputation (MI) is a commonly applied method of statistically handling missing data. It involves imputing missing values repeatedly to account for the variability due to imputations. There are different techniques of MI that have proven to be effective and available in many statistical software packages.
Bintou, T., Ismaila, A. A.
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Retail and Distribution Management, 1973
From time to time we have had occasion to refer to earnings per share in terms of the new ‘imputation’ system of company taxation. This is a somewhat complex system and we have asked our Financial Correspondent to explain in some detail what is involved.
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From time to time we have had occasion to refer to earnings per share in terms of the new ‘imputation’ system of company taxation. This is a somewhat complex system and we have asked our Financial Correspondent to explain in some detail what is involved.
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2018 IEEE 12th International Symposium on Applied Computational Intelligence and Informatics (SACI), 2018
Missing data is challenging enough without the added complexities posed by a lack of research in evaluating imputation. Not only could we potentially increase the impact and validity of studies from many different sectors (research, public and private), we also believe that by creating evaluation software, more researchers may be willing to use and ...
Anthony Chapman +2 more
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Missing data is challenging enough without the added complexities posed by a lack of research in evaluating imputation. Not only could we potentially increase the impact and validity of studies from many different sectors (research, public and private), we also believe that by creating evaluation software, more researchers may be willing to use and ...
Anthony Chapman +2 more
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Computational Biology and Chemistry, 2009
Single imputation methods have been wide-discussed topics among researchers in the field of bioinformatics. One major shortcoming of methods proposed until now is the lack of robustness considerations. Like all data, gene expression data can possess outlying values.
vanden Branden, Karlien +1 more
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Single imputation methods have been wide-discussed topics among researchers in the field of bioinformatics. One major shortcoming of methods proposed until now is the lack of robustness considerations. Like all data, gene expression data can possess outlying values.
vanden Branden, Karlien +1 more
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Statistical Methods in Medical Research, 1999
In recent years, multiple imputation has emerged as a convenient and flexible paradigm for analysing data with missing values. Essential features of multiple imputation are reviewed, with answers to frequently asked questions about using the method in practice.
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In recent years, multiple imputation has emerged as a convenient and flexible paradigm for analysing data with missing values. Essential features of multiple imputation are reviewed, with answers to frequently asked questions about using the method in practice.
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Multiple imputation with missing data indicators
Statistical Methods in Medical Research, 2021Lauren J Beesley +2 more
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An Experimental Survey of Missing Data Imputation Algorithms
IEEE Transactions on Knowledge and Data Engineering, 2022Xiaoye Miao, Yangyang Wu, Lu Chen
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Review: A gentle introduction to imputation of missing values
Journal of Clinical Epidemiology, 2006Geert J M G Van Der Heijden +1 more
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