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Record linkage: statistical models for matching computer records.

J B Copas, F J Hilton

    Journal of the Royal Statistical Society. Series A, (Statistics in Society)
    |January 1, 1990
    PubMed
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    This study introduces statistical models to assess if record pairs belong to the same individual, crucial for accurate data linkage and record matching. The models estimate likelihood ratios using U.K. immigration data.

    Area of Science:

    • Statistics
    • Data Science
    • Computational Statistics

    Background:

    • Accurate record linkage is essential for managing large datasets.
    • Distinguishing between records of the same and different individuals presents a significant challenge.
    • Existing methods may not adequately quantify the evidence for matching.

    Purpose of the Study:

    • To develop and evaluate statistical models for measuring evidence in record linkage.
    • To estimate likelihood ratios for record pairs using known matches.
    • To apply these models to real-world data, specifically U.K. immigration statistics.

    Main Methods:

    • Fitting statistical models to a file of correctly matched record pairs.
    • Estimating likelihood ratios as a measure of evidence for matching.
    Keywords:
    Data CollectionData LinkageDemographic FactorsDeveloped CountriesEuropeInternational MigrationMathematical ModelMigrationModels, TheoreticalNorthern EuropePopulationPopulation DynamicsResearch MethodologyUnited Kingdom

    Related Experiment Videos

  • Developing methods for combining likelihood ratios, considering correlated record fields.
  • Application to U.K. immigration record data.

    • Main Results:

    • Demonstrated the utility of statistical models in quantifying record linkage evidence.
    • Successfully applied likelihood ratio estimation to U.K. immigration statistics.
    • Presented approaches for handling correlated fields in likelihood ratio combination.

    Conclusions:

    • Statistical models provide a robust framework for evidence measurement in record linkage.
    • Likelihood ratio estimation is a powerful tool for assessing the probability of a match.
    • The methods are applicable to complex datasets and can be extended to correlated data fields.