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Probabilistic data linking aims to link records that are believed to belong to the same person from two different data sets. Candidate record pairs are given a weight based on the degree of agreement between fields on the two records. Record pairs with a weight above some upper cut-off are declared links while those with a weight below some lower cut-off are declared non-links. However, there are many record pairs that cannot be automatically assigned a status and are designated for clerical review. Clerical review is a time-consuming and resource-intensive stage of the data linking process requiring careful visual inspection and keyboard use. Acceptance sampling is proposed to dramatically reduce the amount of clerical inspection. Sampling is also proposed as a method to provide an accurate and reliable means of assessing and setting the most appropriate clerical review bounds.
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