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Record Linkage: Statistical Models for Matching Computer Records

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  • J. B. Copas
  • F. J. Hilton

Abstract

We wish to measure the evidence that a pair of records relates to the same, rather than different, individuals. The paper emphasizes statistical models which can be fitted to a file of record pairs known to be correctly matched, and then used to estimate likelihood ratios. A number of models are developed and applied to UK immigration statistics. The combination of likelihood ratios for possibly correlated record fields is discussed.

Suggested Citation

  • J. B. Copas & F. J. Hilton, 1990. "Record Linkage: Statistical Models for Matching Computer Records," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 153(3), pages 287-312, May.
    • Handle: RePEc:bla:jorssa:v:153:y:1990:i:3:p:287-312
    DOI: 10.2307/2982975
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    Citations

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    Cited by:

    1. C. J. Skinner, 2007. "The probability of identification: applying ideas from forensic statistics to disclosure risk assessment," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(1), pages 195-212, January.
    2. Li‐Chun Zhang & Tiziana Tuoto, 2021. "Linkage‐data linear regression," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(2), pages 522-547, April.
    3. Bruce D. Meyer & Nikolas Mittag, 2019. "Misreporting of Government Transfers: How Important Are Survey Design and Geography?," Southern Economic Journal, John Wiley & Sons, vol. 86(1), pages 230-253, July.
    4. Francesco D. d’Ovidio & Paola Perchinunno & Laura Antonucci, 2021. "Data Integration Techniques for the Identification of Poverty Profiles," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 515-531, August.
    5. Oleg Seleznjev & Bernhard Thalheim, 2010. "Random Databases with Approximate Record Matching," Methodology and Computing in Applied Probability, Springer, vol. 12(1), pages 63-89, March.
    6. Vo, Thanh Huan & Chauvet, Guillaume & Happe, André & Oger, Emmanuel & Paquelet, Stéphane & Garès, Valérie, 2023. "Extending the Fellegi-Sunter record linkage model for mixed-type data with application to the French national health data system," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
    7. Xinyi Lu & Mevin B. Hooten & Andee Kaplan & Jamie N. Womble & Michael R. Bower, 2022. "Improving Wildlife Population Inference Using Aerial Imagery and Entity Resolution," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 364-381, June.
    8. Meyer, Bruce D. & Mittag, Nikolas, 2018. "Misreporting of Government Transfers: How Important Are Survey Design and Geography?," IZA Discussion Papers 12038, Institute of Labor Economics (IZA).
    9. Debabrata Dey & Sumit Sarkar & Prabuddha De, 1998. "A Probabilistic Decision Model for Entity Matching in Heterogeneous Databases," Management Science, INFORMS, vol. 44(10), pages 1379-1395, October.
    10. Debabrata Dey, 2003. "Record Matching in Data Warehouses: A Decision Model for Data Consolidation," Operations Research, INFORMS, vol. 51(2), pages 240-254, April.
    11. Bartolini, Fabio & Brunori, Gianluca & Coli, Alessandra & Landi, Chiara & Pacini, Barbara, 2015. "Assessing the Causal Effect of Decoupled Payments on farm labour in Tuscany Using Propensity Score Methods," 2015 Conference, August 9-14, 2015, Milan, Italy 211200, International Association of Agricultural Economists.
    12. Jixian Wang & Peter Donnan, 2002. "Adjusting for missing record linkage in outcome studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(6), pages 873-884.
    13. Lee, Gyumin & Lee, Sungjun & Lee, Changyong, 2023. "Inventor–licensee matchmaking for university technology licensing: A fastText approach," Technovation, Elsevier, vol. 125(C).
    14. Skinner, Chris J., 2007. "The probability of identification: applying ideas from forensic statistics to disclosure risk assessment," LSE Research Online Documents on Economics 39105, London School of Economics and Political Science, LSE Library.
    15. Perchinunno, Paola & Mongelli, Lucia & d’Ovidio, Francesco D., 2020. "Statistical matching techniques in order to plan interventions on socioeconomic weakness: An Italian case," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).

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