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This paper covers methods of creating a set of edits for a set of data. The edits are logical constraints designed to detect errors on the data such as five-year-old children being married or the wages of a particular employee being five times as high as the wages of an employee in a similar position. Edits are intended to improve the quality of data. If data is edited and erroneous fields are identified and imputed, then they can be used for statistical analyses or business purposes. If errors remain in the data, then it is possible that analysts and policy makers who use the data will make inappropriate decisions.
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