Performance and robustness of single-source capture-recapture population size estimators with covariate information and potential one-inflation
Performance and robustness of single-source capture-recapture population size estimators with covariate information and potential one-inflation
Capture-recapture methods for estimating the total size of elusive populations are widely-used, however, due to the choice of estimator impacting upon the results and conclusions made, the question of performance of each estimator is raised. Motivated by an application of the estimators which allow covariate information to meta-analytic data focused on the prevalence rate of completed suicide after bariatric surgery, where studies with no completed suicides did not occur, this paper explores the performance of the estimators through use of a simulation study. The simulation study addresses the performance of the Horvitz–Thompson, generalised Chao and generalised Zelterman estimators, and develops a novel, generalised, form of the modified Chao estimator to account for both covariate information and one-inflation. In addition, the performance of the analytical approach to variance computation is addressed. Given that the estimators vary in their dependence on distributional assumptions, additional simulations are utilised to address the question of the impact outliers have on performance and inference.
Generalised Chao, Generalised Zelterman, Generalised modified Chao, Horvitz–Thompson, One-inflation, Outliers, Performance, Simulation study
Dennett, Layna
7575487f-392e-4d2c-9c5a-6865fe145ab6
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
18 December 2025
Dennett, Layna
7575487f-392e-4d2c-9c5a-6865fe145ab6
Böhning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Dennett, Layna and Böhning, Dankmar
(2025)
Performance and robustness of single-source capture-recapture population size estimators with covariate information and potential one-inflation.
Metron.
(doi:10.1007/s40300-025-00300-2).
Abstract
Capture-recapture methods for estimating the total size of elusive populations are widely-used, however, due to the choice of estimator impacting upon the results and conclusions made, the question of performance of each estimator is raised. Motivated by an application of the estimators which allow covariate information to meta-analytic data focused on the prevalence rate of completed suicide after bariatric surgery, where studies with no completed suicides did not occur, this paper explores the performance of the estimators through use of a simulation study. The simulation study addresses the performance of the Horvitz–Thompson, generalised Chao and generalised Zelterman estimators, and develops a novel, generalised, form of the modified Chao estimator to account for both covariate information and one-inflation. In addition, the performance of the analytical approach to variance computation is addressed. Given that the estimators vary in their dependence on distributional assumptions, additional simulations are utilised to address the question of the impact outliers have on performance and inference.
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s40300-025-00300-2
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Accepted/In Press date: 29 November 2025
Published date: 18 December 2025
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Publisher Copyright:
© The Author(s) 2025.
Keywords:
Generalised Chao, Generalised Zelterman, Generalised modified Chao, Horvitz–Thompson, One-inflation, Outliers, Performance, Simulation study
Identifiers
Local EPrints ID: 508412
URI: http://eprints.soton.ac.uk/id/eprint/508412
ISSN: 0026-1424
PURE UUID: a47ee1ab-a3f2-42ce-b2af-3e24bc813179
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Date deposited: 20 Jan 2026 18:02
Last modified: 21 Jan 2026 02:43
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Author:
Layna Dennett
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