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An uninterrupted time series of population parameters is one of the key outputs of the repeated surveys carried out by national statistical organisations. However, some changes in survey processes are inevitable, and such changes can have an impact on the comparability of survey results over time. Therefore, to efficiently manage such risks during the transition to a new statistical process, it may be necessary to quantify the impact of a change on the outputs of a repeated survey.
This research paper describes a framework of statistical methods that can be applied to quantify the statistical impact due to a survey transition, and discusses the advantages and disadvantages of the available methods in the context of impact measurement requirements and constraints.
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