Difference between revisions of "Data Quality Assurance Plan"
| Line 16: | Line 16: | ||
== Additional Resources == | == Additional Resources == | ||
* Guidance on survey quality assurance from the [https://unstats.un.org/unsd/hhsurveys/pdf/Chapter_10.pdf UN World Health Surveys] | * Guidance on survey quality assurance from the [https://unstats.un.org/unsd/hhsurveys/pdf/Chapter_10.pdf UN World Health Surveys] | ||
*DIME's [http://web.worldbank.org/archive/website01542/WEB/IMAGES/SURVEY.PDF Planning for, Preparing & Monitoring Household Surveys] | |||
*DIME Analytics’ [https://github.com/worldbank/DIME-Resources/blob/master/stata1-4-quality.pdf Real Time Data Quality Checks] | |||
[[Category: Field Management ]] | [[Category: Field Management ]] | ||
Revision as of 19:21, 14 May 2019
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
- DIME's Planning for, Preparing & Monitoring Household Surveys
- DIME Analytics’ Real Time Data Quality Checks