Difference between revisions of "Primary Data Collection"

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== Preparing for primary data collection ==
 
== Preparing for primary data collection ==
 
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The following are critical steps in preparing for primary data collection:
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* Determine sampling frame
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* Conduct sampling, based on [[Sample Size]] calculations, taking care to do so [[Randomization in Stata|reproducibly]]
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* [[Questionnaire Design and Translation|Design and translate the survey instrument]]
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* [[Questionnaire Programming|Program the survey instrument]] if data is being collected electronically
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* [[Procuring a Survey Firm|Procure a Survey Firm]], taking care to prepare detailed [[Survey Firm TOR|Terms of Reference]]
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* [[Preparing for Field Data Collection|Prepare for field work]]
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* Create a [[Data Quality Assurance Plan]]
  
  

Revision as of 15:12, 9 February 2018

Read First

Primary data is directly generated by the researcher. Household surveys are the prototypical example of primary data collection. Unlike Secondary Data Sources, primary data collection can be personally directed by the researcher to ensure it meets the standards of quality, availability, statistical power, and sampling required for a particular research inquiry. With globally increasing access to survey tools such as software, field manuals, and specialized firms, data collected and owned by the researcher has become the dominant method of empirical inquiry in development economics.


Types of primary data

The most common types of primary data are personal interviews. Depending on the research, these may take the form of household surveys, business (firm) surveys, or agricultural (farm) surveys.

Modes of primary data collection

Surveys can be conducted on paper (Pen-and-Paper Personal Interviews (PAPI)) or electronically (Computer-Assisted Personal Interviews (CAPI)), or a combination of the two (Computer-Assisted Field Entry (CAFE)).

Preparing for primary data collection

The following are critical steps in preparing for primary data collection:


Additional Resources