Difference between revisions of "Data Quality Assurance Plan"
Maria jones (talk | contribs) |
Maria jones (talk | contribs) |
||
| Line 11: | Line 11: | ||
== Back to Parent == | == Back to Parent == | ||
This article is part of the topic [[Field Management]] | This article is part of the topic [[Field Management]] | ||
== Additional Resources == | == Additional Resources == | ||
Revision as of 20:02, 12 February 2018
Read First
Many things can go wrong during Primary Data Collection. The purpose of a data quality assurance plan is to think about everything that could go wrong ahead of time, and make a plan to preempt it. The plan should be shared with all impact evaluation stakeholders, including the Impact Evaluation Team and the Survey Firm before data collection starts. It is essential to delineate how data quality will be assessed and what actions will be taken when problems arise.
Guidelines
Your data quality assurance plan should include
- Back Checks
- Monitoring Data Quality
- For follow-up surveys, special consideration should be paid to Tracking and Attrition
Back to Parent
This article is part of the topic Field Management
Additional Resources
- Guidance on survey quality assurance from the UN World Health Surveys