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A General Framework for Multiple-Recapture Estimation that Incorporates Linkage Error Correction

Author

Listed:
  • Zult Daan

    (Statistics Netherlands – Methodology, P.O. Box 24500, 2490 HA The Hague, the Netherlands.)

  • de Wolf Peter-Paul

    (Statistics Netherlands – Methodology, P.O. Box 24500, 2490 HA The Hague, the Netherlands.)

  • Bakker Bart F. M.

    (Statistics Netherlands – Methodology, P.O. Box 24500, 2490 HA The Hague, the Netherlands.)

  • van der Heijden Peter

    (Utrecht University – Methodology and Statistics, Padualaan 14, Utrecht 3508 TC, the Netherlands.)

Abstract

The size of a partly observed population is often estimated with the capture-recapture model. An important assumption of this chat model is that sources can be perfectly linked. This assumption is of relevance if the identification of records is not obtained by some perfect identifier (such as an id code) but by indirect identifiers (such as name and address). In that case, the perfect linkage assumption is often violated, which in general leads to biased population size estimates. Initial suggestions to solve this use record linkage probabilities to correct the capture-recapture model. In this article we provide a general framework, based on the standard log-linear modelling approach, that generalises this work towards the inclusion of additional sources and covariates. We show that the method performs well in a simulation study.

Suggested Citation

  • Zult Daan & de Wolf Peter-Paul & Bakker Bart F. M. & van der Heijden Peter, 2021. "A General Framework for Multiple-Recapture Estimation that Incorporates Linkage Error Correction," Journal of Official Statistics, Sciendo, vol. 37(3), pages 699-718, September.
    • Handle: RePEc:vrs:offsta:v:37:y:2021:i:3:p:699-718:n:10
    DOI: 10.2478/jos-2021-0031
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