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In this research, time series models using multiple data series (SUTSE models) are developed and tested. These models have a number of applications, including as part of a toolkit for identifying and measuring the impacts of statistical process change. Impacts can be assessed via intervention analysis, taking advantage of the cross-correlations and leading properties between the target survey variable and the related series.
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