Difference between revisions of "Field Management"

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== Read First ==
 
== Read First ==
* include here key points you want to make sure all readers understand
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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 ==
* organize information on the topic into subsections. for each subsection, include a brief description / overview, with links to articles that provide details
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Essential steps for good field management include:
===Subsection 1===
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* Developing clear, detailed [[Survey Protocols]]
===Subsection 2===
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* Creating a [[Data Quality Assurance Plan]]
===Subsection 3===
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* Conducting [[Back Checks]]
 
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* [[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:

Additional Resources

  • list here other articles related to this topic, with a brief description and link