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Multiple systems estimation for modern slavery : robustness of list omission and combination

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Far_2020_CD_Multiplesystems_CC.pdf (874.9Kb)
Date
22/08/2020
Author
Sharifi Far, Serveh
King, Ruth
Bird, Sheila
Overstall, Antony
Worthington, Hannah
Jewell, Nicholas
Keywords
Combining sources
Estimate stability
Generalized linear models
List omission
K Law
Pathology and Forensic Medicine
Law
3rd-DAS
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Abstract
Performing censuses on stigmatized or vulnerable populations is challenging, however, for such populations partial enumeration is often possible using different lists or sources. If the sources overlap then multiple systems estimation (MSE) methods can be applied to obtain an estimate of the total population. These are typically expressed by a log-linear model which permits positive/negative dependencies between lists. This paper considers issues that arise for the application of MSE to modern slavery where there is little to no overlap of individuals across lists. We investigate the robustness of MSE in terms of the importance of each list and the impact of combining lists on the estimation process. We undertake a simulation study and consider real national modern slavery data from the UK and Romania.
Citation
Sharifi Far , S , King , R , Bird , S , Overstall , A , Worthington , H & Jewell , N 2020 , ' Multiple systems estimation for modern slavery : robustness of list omission and combination ' , Crime and Delinquency , vol. OnlineFirst . https://doi.org/10.1177/0011128720951429
Publication
Crime and Delinquency
Status
Peer reviewed
DOI
https://doi.org/10.1177/0011128720951429
ISSN
0011-1287
Type
Journal article
Rights
Copyright © The Author(s) 2020. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/20645

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