Why is data quality assessment needed in NIPN?

NIPN is using existing data. These existing data probably already have 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 are fit-for-purpose for the intended analysis:

  • What was the study design?
  • How were the data collected?
  • What data quality process has been effectively followed?
  • What are the conclusions of the data quality report attached to the dataset?

2) Second, the data probably were collected for a specific data analysis objective that may be different from the NIPN data analysis objective. Therefore, to achieve the NIPN objective, a different data quality level may be needed.

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

*****
Examples