Goldstein, H;
Harron, K;
Cortina-Borja, M;
(2017)
A scaling approach to record linkage.
Statistics in Medicine
, 36
(16)
pp. 2514-2521.
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.
| Type: | Article |
|---|---|
| Title: | A scaling approach to record linkage |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1002/sim.7287 |
| Publisher version: | https://doi.org/10.1002/sim.7287 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | scaling; record linkage; data linkage; correspondence analysis |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10064550 |
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