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Why is data quality assessment needed in NIPN?

NIPN is using existing data. Therefore the data has probably already been validated by a national institution after going through a data quality control process. For example, Demographic and Health Surveys are usually validated by the National Statistic Office and international organisations (https://data.unicef.org/resources/jme)

So, why should NIPN review the data quality of these datasets?

  1. First, when conducting secondary data analysis, it is compulsory to have a critical eye on the quality of the data before using it. It is important to know if the data is suited for the intended analysis:
  • What is the study design?
  • How has the data been collected?
  • What data quality process has been effectively followed?
  • What are the conclusions of the data quality report attached to the dataset?
  1. Second, the data has probably been collected for a specific data analysis objective that may be different from the NIPN data analysis objective. Therefore, to achieve the NIPN objective, you may need a different data quality level.

“Data quality” is neither “good” nor “bad”: it should be “good enough” for the intended analysis

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