Preface to the Special Issue on Integrating Data from Multiple Sources for Production of Official Statistics.

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Bibliographic Details
Title: Preface to the Special Issue on Integrating Data from Multiple Sources for Production of Official Statistics.
Authors: Fosen, Johan, Holmberg, Anders, Jansson, Ingegerd, Krapavickaitė, Danutė, de Waal, Ton
Source: Journal of Official Statistics (JOS); Jun2025, Vol. 41 Issue 2, p539-546, 8p
Subject Terms: DATA integration, STATISTICAL sampling, STATISTICAL methods in information science, MEASUREMENT errors, SELECTION bias (Statistics), BIG data, METADATA
Abstract: The article focuses on the integration of multiple data sources for the production of official statistics, highlighting the growing interest and challenges associated with using non-probability data alongside traditional probability sampling methods. It discusses the advantages of combining various data sources, such as administrative records and smart data, to enhance the timeliness and detail of statistics while addressing issues like selection bias and measurement error. The special issue presents various methodological contributions aimed at improving data integration processes and ensuring the quality of official statistics, emphasizing the need for innovative solutions in the face of evolving data landscapes. [Extracted from the article]
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Database: Complementary Index
Description
Abstract:The article focuses on the integration of multiple data sources for the production of official statistics, highlighting the growing interest and challenges associated with using non-probability data alongside traditional probability sampling methods. It discusses the advantages of combining various data sources, such as administrative records and smart data, to enhance the timeliness and detail of statistics while addressing issues like selection bias and measurement error. The special issue presents various methodological contributions aimed at improving data integration processes and ensuring the quality of official statistics, emphasizing the need for innovative solutions in the face of evolving data landscapes. [Extracted from the article]
ISSN:0282423X
DOI:10.1177/0282423X251332063