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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

A Dynamic Method for the Evaluation and Comparison of Imputation Techniques

Solomon, Norman, Oatley, Giles and McGarry, Kenneth (2007) A Dynamic Method for the Evaluation and Comparison of Imputation Techniques. In: International Conference of Computational Statistics and Data Engineering, 2-4 July, 2007, London, U.K.

Item Type: Conference or Workshop Item (Paper)


Imputation of missing data is important in many
areas, such as reducing non-response bias in surveys and maintaining medical documentation. Estimating the uncertainty inherent in the imputed values is one way of evaluating the results of the imputation process. This paper presents a new method for the estimation of imputation uncertainty, which can be implemented as part of any imputation method, and which can be used to estimate the accuracy of the imputed values
generated by both parametric and non-parametric imputation techniques. The proposed approach can be used to assess the feasibility of the imputation process for large complex datasets, and to compare the effectiveness of candidate imputation methods when they are
applied to the same dataset. Current uncertainty estimation methods are described and their limitations are discussed. The ideas underpinning the proposed approach are explained in detail,and a case study is presented which shows how the new method has been applied in practice.


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Depositing User: Kenneth McGarry


Item ID: 6018
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Users with ORCIDS

ORCID for Kenneth McGarry: ORCID iD

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Date Deposited: 07 Mar 2016 09:20
Last Modified: 18 Dec 2019 15:38


Author: Kenneth McGarry ORCID iD
Author: Norman Solomon
Author: Giles Oatley

University Divisions

Faculty of Technology
Faculty of Technology > School of Computer Science


Computing > Artificial Intelligence
Computing > Information Systems

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