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Quality control is highly dependent on the data collection methodology, but there are some general practices that can be applied

Missing values in a data set should be standardized for identification by the consistent use of well-defined missing value codes in data tables

Problematic data should be flagged to indicate known issues so potential users are aware the limitations of the data.

Use consistent coding schemes.

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