A scaling approach to record linkage.


Goldstein, H; Harron, K; Cortina-Borja, M; (2017) A scaling approach to record linkage. Statistics in medicine. ISSN 0277-6715 DOI: 10.1002/sim.7287

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Abstract

With increasing availability of large datasets derived from administrative and other sources, there is an increasing demand for the successful linking of these to provide rich sources of data for further analysis. Variation in the quality of identifiers used to carry out linkage means that existing approaches are often based upon 'probabilistic' models, which are based on a number of assumptions, and can make heavy computational demands. In this paper, we suggest a new approach to classifying record pairs in linkage, based upon weights (scores) derived using a scaling algorithm. The proposed method does not rely on training data, is computationally fast, requires only moderate amounts of storage and has intuitive appeal. Copyright © 2017 John Wiley & Sons, Ltd.

Item Type: Article
Faculty and Department: Faculty of Public Health and Policy > Dept of Health Services Research and Policy
Research Centre: Centre for Statistical Methodology
PubMed ID: 28303597
Web of Science ID: 404067000003
URI: http://researchonline.lshtm.ac.uk/id/eprint/3649247

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