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  • Articles and reports: 11-522-X201700014715
    Description:

    In preparation for 2021 UK Census the ONS has committed to an extensive research programme exploring how linked administrative data can be used to support conventional statistical processes. Item-level edit and imputation (E&I) will play an important role in adjusting the 2021 Census database. However, uncertainty associated with the accuracy and quality of available administrative data renders the efficacy of an integrated census-administrative data approach to E&I unclear. Current constraints that dictate an anonymised ‘hash-key’ approach to record linkage to ensure confidentiality add to that uncertainty. Here, we provide preliminary results from a simulation study comparing the predictive and distributional accuracy of the conventional E&I strategy implemented in CANCEIS for the 2011 UK Census to that of an integrated approach using synthetic administrative data with systematically increasing error as auxiliary information. In this initial phase of research we focus on imputing single year of age. The aim of the study is to gain insight into whether auxiliary information from admin data can improve imputation estimates and where the different strategies fall on a continuum of accuracy.

    Release date: 2016-03-24
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  • Articles and reports: 11-522-X201700014715
    Description:

    In preparation for 2021 UK Census the ONS has committed to an extensive research programme exploring how linked administrative data can be used to support conventional statistical processes. Item-level edit and imputation (E&I) will play an important role in adjusting the 2021 Census database. However, uncertainty associated with the accuracy and quality of available administrative data renders the efficacy of an integrated census-administrative data approach to E&I unclear. Current constraints that dictate an anonymised ‘hash-key’ approach to record linkage to ensure confidentiality add to that uncertainty. Here, we provide preliminary results from a simulation study comparing the predictive and distributional accuracy of the conventional E&I strategy implemented in CANCEIS for the 2011 UK Census to that of an integrated approach using synthetic administrative data with systematically increasing error as auxiliary information. In this initial phase of research we focus on imputing single year of age. The aim of the study is to gain insight into whether auxiliary information from admin data can improve imputation estimates and where the different strategies fall on a continuum of accuracy.

    Release date: 2016-03-24
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