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Total Process Error: An Approach for Assessing and Monitoring the Quality of Multisource Processes

Author

Listed:
  • Rocci Fabiana
  • Varriale Roberta
  • Luzi Orietta

    (Istat, Via Cesare Balbo 16, 00184 Roma, Italy .)

Abstract

Most National Statistical Institutes are progressively moving from traditional production models to new strategies based on the combined use of different sources of information, which can be both primary and secondary. In this article, we propose a framework for assessing the quality of multisource processes, such as statistical registers.

Suggested Citation

  • Rocci Fabiana & Varriale Roberta & Luzi Orietta, 2022. "Total Process Error: An Approach for Assessing and Monitoring the Quality of Multisource Processes," Journal of Official Statistics, Sciendo, vol. 38(2), pages 533-556, June.
    • Handle: RePEc:vrs:offsta:v:38:y:2022:i:2:p:533-556:n:12
    DOI: 10.2478/jos-2022-0025
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    References listed on IDEAS

    as
    1. Marco Di Zio & Ugo Guarnera & Roberta Varriale, 2016. "Estimation of the main variables of the economic account of small and medium enterprises based on administrative sources," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 18(1), pages 71-81.
    2. Ton de Waal & Arnout van Delden & Sander Scholtus, 2020. "Multi‐source Statistics: Basic Situations and Methods," International Statistical Review, International Statistical Institute, vol. 88(1), pages 203-228, April.
    Full references (including those not matched with items on IDEAS)

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