Coverage Evaluation on Probabilistically Linked Data
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...
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doaj-503eaecfe2b0426b8fb5f0a2035c27672021-09-06T19:40:51ZengSciendoJournal of Official Statistics2001-73672015-09-0131341542910.1515/jos-2015-0025jos-2015-0025Coverage Evaluation on Probabilistically Linked DataDi Consiglio Loredana0Tuoto Tiziana1Italian National Statistical Institute - Istat, Via Cesare Balbo, 16 00184 Rome, ItalyItalian National Statistical Institute - Istat, Via Cesare Balbo, 16 00184 Rome, ItalyThe 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.https://doi.org/10.1515/jos-2015-0025linkage errorscapture-recapture methodpetersen estimatoradministrative data |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Di Consiglio Loredana Tuoto Tiziana |
spellingShingle |
Di Consiglio Loredana Tuoto Tiziana Coverage Evaluation on Probabilistically Linked Data Journal of Official Statistics linkage errors capture-recapture method petersen estimator administrative data |
author_facet |
Di Consiglio Loredana Tuoto Tiziana |
author_sort |
Di Consiglio Loredana |
title |
Coverage Evaluation on Probabilistically Linked Data |
title_short |
Coverage Evaluation on Probabilistically Linked Data |
title_full |
Coverage Evaluation on Probabilistically Linked Data |
title_fullStr |
Coverage Evaluation on Probabilistically Linked Data |
title_full_unstemmed |
Coverage Evaluation on Probabilistically Linked Data |
title_sort |
coverage evaluation on probabilistically linked data |
publisher |
Sciendo |
series |
Journal of Official Statistics |
issn |
2001-7367 |
publishDate |
2015-09-01 |
description |
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. |
topic |
linkage errors capture-recapture method petersen estimator administrative data |
url |
https://doi.org/10.1515/jos-2015-0025 |
work_keys_str_mv |
AT diconsiglioloredana coverageevaluationonprobabilisticallylinkeddata AT tuototiziana coverageevaluationonprobabilisticallylinkeddata |
_version_ |
1717767655359774720 |