<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Data integration is now common practice in official statistics and involves an increasing number of sources. When using multiple sources, an objective is to assess the unknown size of the population. To this aim, capture-recapture methods are applied. Standard capture-recapture methods are based on a number of strong assumptions, including the absence of errors in the integration procedures. However, in particular when the integrated sources were not originally collected for statistical purposes, this assumption is unlikely and linkage errors (false links and missing links) may occur. In this article, the problem of adjusting population estimates in the presence of linkage errors in multiple lists is tackled; under homogeneous linkage error probabilities assumption, a solution is proposed in a realistic and practical scenario of multiple lists linkage procedure.</p></abstract>

Data integration is now common practice in official statistics and involves an increasing number of sources. When using multiple sources, an objective is to assess the unknown size of the population. To this aim, capture-recapture methods are applied. Standard capture-recapture methods are based on a number of strong assumptions, including the absence of errors in the integration procedures. However, in particular when the integrated sources were not originally collected for statistical purposes, this assumption is unlikely and linkage errors (false links and missing links) may occur. In this article, the problem of adjusting population estimates in the presence of linkage errors in multiple lists is tackled; under homogeneous linkage error probabilities assumption, a solution is proposed in a realistic and practical scenario of multiple lists linkage procedure.

Population Size Estimation and Linkage Errors: the Multiple Lists Case

Italian National Institute of Statistics (Istat)

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Population Size Estimation and Linkage Errors: the Multiple Lists Case"}

Data integration is now common practice in official statistics and involves an increasing number of sources. When using multiple sources, an objective is to...

Population Size Estimation and Linkage Errors: the Multiple Lists Case

Online veröffentlicht: 14. Dez. 2018

Seitenbereich: 889 - 908

Eingereicht: 01. Juni 2017

Akzeptiert: 01. Aug. 2018

DOI: https://doi.org/10.2478/jos-2018-0044

Schlüsselwörter
Probabilistically linked data, capture-recapture model, multiple system estimation, log-linear model

© 2018 Loredana Di Consiglio et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Population Size Estimation and Linkage Errors: the Multiple Lists Case

Online veröffentlicht: 14. Dez. 2018

Seitenbereich: 889 - 908

Eingereicht: 01. Juni 2017

Akzeptiert: 01. Aug. 2018

DOI: https://doi.org/10.2478/jos-2018-0044

SchlüsselwörterProbabilistically linked data, capture-recapture model, multiple system estimation, log-linear model

© 2018 Loredana Di Consiglio et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Probabilistically linked data, capture-recapture model, multiple system estimation, log-linear model