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A study on estimating population size of disabled people using capture-recapture method
Journal of the Korean Data & Information Science Society 2022;33:977-90
Published online November 30, 2022;  https://doi.org/10.7465/jkdi.2022.33.6.977
© 2022 Korean Data and Information Science Society.

Ji-Su Gil1 · Seunghwan Park2

12Department of Information Statistics, Kangwon University, South Korea
Correspondence to: 1 Master’s degree, Department of Information Statistics, Kangwon University, Chuncheon-si, Kangwondo 24341, Korea.
2 Assistant professor, Department of Information Statistics, Kangwon University, Chuncheon-si, Kangwon-do 24341, Korea. E-mail: stat.shpark@kangwon.ac.kr
Received August 7, 2022; Revised September 20, 2022; Accepted October 10, 2022.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
The purpose of this study was to investigate the applications of capture-recapture methods to estimate population size with two data sources. We review the weighted sum estimator of the population size and its variance estimation formula. Several estimators of the population size are considered in the context of capture-recapture methods. The proposed method is applied to National Survey on Persons with disabilities in Korea. Real data analysis shows that the proposed estimator using capture-recapture methods has smaller variance than that of the weighted estimator. Result also indicate that the proposed estimator using the calibration weights in survey gives same estimate of population size to the weighted estimator. Moreover the proposed estimator using the calibration weights has smaller mean squared error than the weighted estimator. We propose a novel application of capture-recapture methods to estimate the population size with complex survey data. Variance estimation using Taylor linearization is developed.
Keywords : Capture-recaputre model, complex survey data, estimating population size, variance estimation.