Audit sampling as a quality standard for multisource official statistics
Audit sampling as a quality standard for multisource official statistics
Designed surveys through sampling or census are the standard approach to official statistics, where the targets are descriptive summaries of a given population. Official statistics are also commonly produced by combining relevant administrative registers, such as in the Nordic countries since the 1960s. The scope of non-survey data sources are being extended to include various so-called big-data sources, although so far relatively few multisource statistics of this kind have been credited as official statistics. Trustworthy evaluation of multisource official statistics is a fundamental issue for creating a new quality assurance standard. In this paper, audit sampling inference will be explained, illustrated and promoted to this end.
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
Zhang, Li-Chun
a5d48518-7f71-4ed9-bdcb-6585c2da3649
Zhang, Li-Chun
(2023)
Audit sampling as a quality standard for multisource official statistics.
Spanish Journal of Statistics.
(In Press)
Abstract
Designed surveys through sampling or census are the standard approach to official statistics, where the targets are descriptive summaries of a given population. Official statistics are also commonly produced by combining relevant administrative registers, such as in the Nordic countries since the 1960s. The scope of non-survey data sources are being extended to include various so-called big-data sources, although so far relatively few multisource statistics of this kind have been credited as official statistics. Trustworthy evaluation of multisource official statistics is a fundamental issue for creating a new quality assurance standard. In this paper, audit sampling inference will be explained, illustrated and promoted to this end.
Text
qualityMultisourceStat-Zhang
- Accepted Manuscript
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Accepted/In Press date: 25 November 2023
Identifiers
Local EPrints ID: 486585
URI: http://eprints.soton.ac.uk/id/eprint/486585
ISSN: 2695-9070
PURE UUID: cd028806-e361-48aa-9b8a-288f643d715a
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Date deposited: 26 Jan 2024 17:50
Last modified: 18 Mar 2024 03:24
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