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Coverage Evaluation on Probabilistically Linked Data

Author

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  • Di Consiglio Loredana

    (Italian National Statistical Institute - Istat, Via Cesare Balbo, 16 00184 Rome, Italy)

  • Tuoto Tiziana

    (Italian National Statistical Institute - Istat, Via Cesare Balbo, 16 00184 Rome, Italy)

Abstract

The Capture-recapture method is a well-known solution for evaluating the unknown size of a population. Administrative data represent sources of independent counts of a population and can be jointly exploited for applying the capture-recapture method. Of course, administrative sources are affected by over- or undercoverage when considered separately. The standard Petersen approach is based on strong assumptions, including perfect record linkage between lists. In reality, record linkage results can be affected by errors. A simple method for achieving linkage error-unbiased population total estimates is proposed in Ding and Fienberg (1994). In this article, an extension of the Ding and Fienberg model by relaxing their conditions is proposed. The procedures are illustrated for estimating the total number of road casualties, on the basis of a probabilistic record linkage between two administrative data sources. Moreover, a simulation study is developed, providing evidence that the adjusted estimator always performs better than the Petersen estimator.

Suggested Citation

  • Di Consiglio Loredana & Tuoto Tiziana, 2015. "Coverage Evaluation on Probabilistically Linked Data," Journal of Official Statistics, Sciendo, vol. 31(3), pages 415-429, September.
    • Handle: RePEc:vrs:offsta:v:31:y:2015:i:3:p:415-429:n:5
    DOI: 10.1515/jos-2015-0025
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    References listed on IDEAS

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    1. Bartolucci, Francesco & Forcina, Antonio, 2006. "A Class of Latent Marginal Models for CaptureRecapture Data With Continuous Covariates," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 786-794, June.
    2. Chen Z. & Kuo L., 2001. "A Note on the Estimation of the Multinomial Logit Model With Random Effects," The American Statistician, American Statistical Association, vol. 55, pages 89-95, May.
    3. Brent A. Coull & Alan Agresti, 1999. "The Use of Mixed Logit Models to Reflect Heterogeneity in Capture-Recapture Studies," Biometrics, The International Biometric Society, vol. 55(1), pages 294-301, March.
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    1. Di Consiglio Loredana & Tuoto Tiziana, 2018. "Population Size Estimation and Linkage Errors: the Multiple Lists Case," Journal of Official Statistics, Sciendo, vol. 34(4), pages 889-908, December.
    2. Zhang Li-Chun, 2019. "A Note on Dual System Population Size Estimator," Journal of Official Statistics, Sciendo, vol. 35(1), pages 279-283, March.
    3. Bijak Jakub & Bryant Johan & Gołata Elżbieta & Smallwood Steve, 2021. "Preface," Journal of Official Statistics, Sciendo, vol. 37(3), pages 533-541, September.
    4. de Wolf Peter-Paul & van der Laan Jan & Zult Daan, 2019. "Connecting Correction Methods for Linkage Error in Capture-Recapture," Journal of Official Statistics, Sciendo, vol. 35(3), pages 577-597, September.
    5. Ton de Waal & Arnout van Delden & Sander Scholtus, 2020. "Multi‐source Statistics: Basic Situations and Methods," International Statistical Review, International Statistical Institute, vol. 88(1), pages 203-228, April.

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