Difference between revisions of "Primary Data Collection"
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'''Primary data collection''' is the process of gathering data through surveys, interviews or experiments. A typical example of primary data is household surveys. | '''Primary data collection''' is the process of gathering data through [[Survey Pilot|surveys]], interviews or experiments. A typical example of primary data is '''household surveys'''. In this form of data collection, researchers can personally ensure that primary data meets the standards of [[Monitoring Data Quality | quality]], availability, [[Power Calculations in Stata | statistical power]] and [[Sampling & Power Calculations | sampling]] required for a particular research question. With globally increasing access to specialized [[Software Tools |survey tools]], [[Survey Firm | survey firms]], and field manuals, primary data has become the dominant source for empirical inquiry in development economics. | ||
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== Read First == | == Read First == | ||
*[https://github.com/worldbank/dime-standards/blob/master/dime-research-standards/README.md The DIME Research Standards] provide a comprehensive checklist to ensure that collection and handling of research data is in line with global best-practices. | |||
*[https://github.com/worldbank/dime-standards/blob/master/dime-research-standards/README.md DIME | *'''Personal interviews''' are the most effective medium for primary data collection. Depending on the research question, these interviews may take the form of household surveys, business (firm) surveys, or agricultural (farm) surveys. | ||
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*<code>[[iefieldkit]]</code> is a Stata package that aids primary data collection. It currently supports three major components of that workflow: [[Questionnaire Design|survey design]]; survey completion; and [[Data Cleaning|data-cleaning]] and survey harmonization. | *<code>[[iefieldkit]]</code> is a Stata package that aids primary data collection. It currently supports three major components of that workflow: [[Questionnaire Design|survey design]]; survey completion; and [[Data Cleaning|data-cleaning]] and survey harmonization. | ||
== Guidelines == | == Guidelines == | ||
While impact evaluations often benefit from [[Secondary Data Sources|secondary sources of data]] like administrative data, census data, or household data, these sources may not always be available. In such cases, researchers need to collect data directly through a series of [[Questionnaire Design|well-designed]] interviews and [[Survey Pilot|surveys]]. The process of collecting primary data requires a great deal of foresight, [[Field Management|planning]] and coordination. | |||
Listed below are the crucial steps involved the in [[Preparing for Field Data Collection | preparation and collection]] of primary data: | |||
=== Pre-register research === | === Pre-register research === | ||
[[Pre-Registration | Pre-register]] and consider producing a [[Pre-Analysis Plan | pre-analysis plan]]. | [[Pre-Registration | Pre-register]] and consider producing a [[Pre-Analysis Plan | pre-analysis plan]]. | ||
Revision as of 20:19, 19 March 2020
Primary data collection is the process of gathering data through surveys, interviews or experiments. A typical example of primary data is household surveys. In this form of data collection, researchers can personally ensure that primary data meets the standards of quality, availability, statistical power and sampling required for a particular research question. With globally increasing access to specialized survey tools, survey firms, and field manuals, primary data has become the dominant source for empirical inquiry in development economics.
Read First
- The DIME Research Standards provide a comprehensive checklist to ensure that collection and handling of research data is in line with global best-practices.
- Personal interviews are the most effective medium for primary data collection. Depending on the research question, these interviews may take the form of household surveys, business (firm) surveys, or agricultural (farm) surveys.
iefieldkitis a Stata package that aids primary data collection. It currently supports three major components of that workflow: survey design; survey completion; and data-cleaning and survey harmonization.
Guidelines
While impact evaluations often benefit from secondary sources of data like administrative data, census data, or household data, these sources may not always be available. In such cases, researchers need to collect data directly through a series of well-designed interviews and surveys. The process of collecting primary data requires a great deal of foresight, planning and coordination. Listed below are the crucial steps involved the in preparation and collection of primary data:
Pre-register research
Pre-register and consider producing a pre-analysis plan.
Acquire approval from human subjects
Acquire human subjects approval and get set up with the proper tools for encryption and de-identification.
Compile the survey budget
Compile the survey budget
Determine and set the relevant sampling parameters.
Determine the sampling frame, calculate sample size, conduct sampling and power calculations, and randomize treatment.
Desing and translate the survey instrument
Design and translate the survey instrument
Program the instrument
Program the instrument f data is being collected electronically via a Computer-Assisted Personal Interviews (CAPI) or Computer-Assisted Field Entry (CAFE) survey.
Establish survey protocols
Establish survey protocols.
Pilot the survey instrument
Pilot the survey instrument–both the content and protocols.
Procure a survey firm
Procure a survey firm, taking care to prepare detailed Terms of Reference.
Train enumerators
Monitor data quality
Monitor data quality can be done through back-checks, high frequency checks, and other methods.
Maintain an organized data folder
via iefolder.
Back to Parent
This article is part of the topic primary data collection
Additional Resources
- Brief from Oxfam: Planning Survey Research
- DIME Guide on Planning, Preparing & Monitoring Household Surveys
- DIME Analytics Guidelines on Preparing for Data Collection
- Guidelines and tools for Preparing for Data Collection from the World Bank's Results Based Financing Impact Evaluation Toolkit
- Oxfam provides a detailed case study of how to use electronic data collection (SurveyCTO) combined with Stata code to improve data quality in the field.