00000cam 2200000zi 4500 9.966464 CaOODSP 20261002085504 m o d f cr cn||||||||| 261002e20250908oncad ob f000 0 eng d CaOODSP eng rda CaOODSP n-cn--- CS11-522/2024-1-11E-PDF Mireuta, Matei, author. Data-driven imputation strategies and their associated quality indicators in economic surveys / by Matei Mireuta, Ahalya Sivathayalan and Stephen Styles. At head of title: Proceedings of Statistics Canada Symposium 2024 : the future of official statistics [Ottawa] : Statistics Canada = Statistique Canada, September 8, 2025. 1 online resource (7 unnumbered pages) : illustrations, graphs. text txt rdacontent computer c rdamedia online resource cr rdacarrier [Statistics Canada international symposium series : proceedings], 1709-8211 Title from cover. Issued also in French under title: Stratégies d'imputation axées sur les données et leurs indicateurs de qualité connexes dans les enquêtes économiques. Includes bibliographical references. "The use of modern "data"-driven imputation methods to treat non-response in the context of surveys processed in the Integrated Business Statistics Program at Statistics Canada have previously been explored. It has been observed that these methods can lead to high quality imputation and further have the potential to result in broad efficiencies when setting up a particular survey's edit and imputation strategy. However, estimation of the associated total variance, more specifically the component due to imputation, remains a challenge. In this article, two methods for estimation of total variance are proposed and preliminary results are shown that gave motivation to pursue further research in this area"--Abstract, page [2]. Statistical matching. Analysis of variance. Economic surveys Canada. Statistics Canada, issuing body. Stratégies d'imputation axées sur les données et leurs indicateurs de qualité connexes dans les enquêtes économiques / (CaOODSP)9.966465 Statistics Canada international symposium series - proceedings, 1709-8211 (CaOODSP)9.505681 PDF 469 KB https://publications.gc.ca/collections/collection_2026/statcan/11-522-x/CS11-522-2024-1-11-eng.pdf 11-522-X