Difference between revisions of "Field Management"
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== Read First == | == Read First == | ||
Careful management of field staff, contractors, and survey firms is essential to completing data collection on time, on budget, without missing observations, and at high quality. Without direct (and usually intensive) oversight of this critical process, unknown errors can enter the dataset. If these errors are made systematically by the data collection team, they can induce biases of unknown size and direction into the estimates of program effects for even the best-executed intervention. | |||
== Guidelines == | == Guidelines == | ||
Essential steps for good field management include: | |||
* Developing clear, detailed [[Survey Protocols]] | |||
* Creating a [[Data Quality Assurance Plan]] | |||
* Conducting [[Back Checks]] | |||
* [[Monitoring Data Quality]] while data collection is ongoing | |||
== Additional Resources == | == Additional Resources == | ||
Revision as of 15:54, 9 February 2018
Read First
Careful management of field staff, contractors, and survey firms is essential to completing data collection on time, on budget, without missing observations, and at high quality. Without direct (and usually intensive) oversight of this critical process, unknown errors can enter the dataset. If these errors are made systematically by the data collection team, they can induce biases of unknown size and direction into the estimates of program effects for even the best-executed intervention.
Guidelines
Essential steps for good field management include:
- Developing clear, detailed Survey Protocols
- Creating a Data Quality Assurance Plan
- Conducting Back Checks
- Monitoring Data Quality while data collection is ongoing
Additional Resources
- list here other articles related to this topic, with a brief description and link