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Abstract
Official statistics on living conditions and access to goods are crucial in monitoring inequality based on racial and ethnic origin and population decline as a critical contemporary demography challenge. However, data collection for minorities and sensitive information can be restricted. In this study, an independent sampling survey was designed, and machine learning algorithms were used to overcome these issues. We used clustering methods and Census 2021 data to identify essential variables and homogeneous freguesias to distribute the sample size. In addition, dwellings were segmented, and the clusters were analyzed and discussed to minimize the non-response and coverage errors. The proposed methodology provides a comprehensive final survey with proper target population overage.
Original language | English |
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Pages | 211 |
Number of pages | 1 |
Publication status | Published - 4 Jun 2024 |
Event | European Conference on Quality in Official Statistics - Estoril Congress Center, Lisboa, Portugal Duration: 4 Jun 2024 → 7 Jun 2024 Conference number: 11 https://www.q2024.pt/ |
Conference
Conference | European Conference on Quality in Official Statistics |
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Abbreviated title | Q2024 |
Country/Territory | Portugal |
City | Lisboa |
Period | 4/06/24 → 7/06/24 |
Internet address |
Keywords
- Machine Learning
- Clustering
- Official statistics
- Census
- Measurement Error
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Dive into the research topics of 'Population Trajectories Survey Methodology: Improving Coverage Error by Clustering of Freguesias and Dwelling Segmentation using Census Data in Portugal'. Together they form a unique fingerprint.Activities
- 1 Oral presentation
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Population Trajectories Survey Methodology: Improving Coverage Error by Clustering of Freguesias and Dwelling Segmentation using Census Data in Portugal
Afshin Ashofteh (Speaker), João Lopes (Speaker) & Pedro Campos (Speaker)
4 Jun 2024 → 7 Jun 2024Activity: Talk or presentation › Oral presentation
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