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. Researchers can personally direct primary data collection to ensure that 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 [[Software Tools |survey tools]], | '''Primary data collection''' is the process of gathering data through surveys, interviews or experiments. A typical example of primary data is household surveys. Researchers can personally direct primary data collection to ensure that 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 == | ||
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*[https://github.com/worldbank/dime-standards/blob/master/dime-research-standards/README.md DIME's Research Standards] provide a comprehensive checklist to ensure that collection and handling of research data are in line with global best-practices. | *[https://github.com/worldbank/dime-standards/blob/master/dime-research-standards/README.md DIME's Research Standards] provide a comprehensive checklist to ensure that collection and handling of research data are in line with global best-practices. | ||
*The large majority of primary data comes from personal interviews. Depending on the research, these may take the form of household surveys, business (firm) surveys, or agricultural (farm) surveys. | *The large majority of primary data comes from personal interviews. Depending on the research, these may take the form of household surveys, business (firm) surveys, or agricultural (farm) surveys. | ||
*<code>iefieldkit</code> is a Stata package | *<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 == | ||
The following are critical steps in [[Preparing for Field Data Collection | preparing for]] and conducting primary data collection: | The following are critical steps in [[Preparing for Field Data Collection | preparing for]] and conducting primary data collection: | ||
=== Pre-register research === | |||
[[Pre-Registration | Pre-register]] and consider producing a [[Pre-Analysis Plan | pre-analysis plan]]. | |||
=== Acquire approval from human subjects === | |||
Acquire [[Human Subjects Approval | human subjects approval]] and get set up with the proper tools for [[Encryption | encryption]] and [[De-identification | de-identification]]. | |||
=== Compile the survey budget === | |||
Compile the [[Survey Budget | survey budget]] | |||
=== Determine and set the relevant sampling parameters. === | |||
Determine the sampling frame, calculate [[Sample Size | sample size]], conduct [[Sampling & Power Calculations | sampling and power calculations]], and [[Randomization in Stata|randomize]] treatment. | |||
=== Desing and translate the survey instrument === | |||
[[Questionnaire Design | Design]] and [[Questionnaire Translation | translate]] the survey instrument | |||
=== Program the instrument === | |||
[[Questionnaire Programming|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 | survey protocols]]. | |||
=== Pilot the survey instrument === | |||
[[Survey Pilot|Pilot]] the survey instrument–both the [[Piloting Survey Content | content]] and [[Piloting Survey Protocols | protocols]]. | |||
=== Procure a survey firm === | |||
[[Procuring a Survey Firm|Procure]] a [[Survey Firm |survey firm]], taking care to prepare detailed [[Survey Firm TOR|Terms of Reference]]. | |||
=== Train enumerators === | |||
[[Enumerator Training | Train enumerators]] | |||
=== Monitor data quality === | |||
[[Monitoring Data Quality | Monitor data quality]] can be done through back-checks, high frequency checks, and other methods. | |||
=== Maintain an organized data folder === | |||
via <code>[[iefolder]]</code>. | |||
== Back to Parent == | == Back to Parent == | ||
This article is part of the topic [[Primary Data Collection]] | This article is part of the topic [[Primary Data Collection|primary data collection]] | ||
== Additional Resources == | == Additional Resources == | ||
* Brief from Oxfam: [http://policy-practice.oxfam.org.uk/publications/planning-survey-research-578973 Planning Survey Research] | * Brief from Oxfam: [http://policy-practice.oxfam.org.uk/publications/planning-survey-research-578973 Planning Survey Research] | ||
* | *[http://web.worldbank.org/archive/website01542/WEB/IMAGES/SURVEY.PDF DIME Guide on Planning, Preparing & Monitoring Household Surveys] | ||
* | *[https://github.com/worldbank/DIME-Resources/blob/master/survey-preparing.pdf DIME Analytics Guidelines on Preparing for Data Collection] | ||
* Guidelines and tools for [http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTHEALTHNUTRITIONANDPOPULATION/EXTHSD/EXTIMPEVALTK/0,,contentMDK:23262154~pagePK:64168427~piPK:64168435~theSitePK:8811876,00.html Preparing for Data Collection] from the World Bank's Results Based Financing Impact Evaluation Toolkit | * Guidelines and tools for [http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTHEALTHNUTRITIONANDPOPULATION/EXTHSD/EXTIMPEVALTK/0,,contentMDK:23262154~pagePK:64168427~piPK:64168435~theSitePK:8811876,00.html Preparing for Data Collection] from the World Bank's Results Based Financing Impact Evaluation Toolkit | ||
Oxfam provides [https://oxfamilibrary.openrepository.com/bitstream/handle/10546/620522/cs-going-digital-data-quality-data-collection-240718-en.pdf?sequence=1&isAllowed=y a detailed case study] of how to use electronic data collection (SurveyCTO) combined with Stata code to improve data quality in the field. | *Oxfam provides [https://oxfamilibrary.openrepository.com/bitstream/handle/10546/620522/cs-going-digital-data-quality-data-collection-240718-en.pdf?sequence=1&isAllowed=y a detailed case study] of how to use electronic data collection (SurveyCTO) combined with Stata code to improve data quality in the field. | ||
[[Category: Primary Data Collection ]] | [[Category: Primary Data Collection ]] | ||
Revision as of 19:46, 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. Researchers can personally direct primary data collection to ensure that 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
- Primary data collection typically requires a great deal of foresight, planning and coordination.
- DIME's Research Standards provide a comprehensive checklist to ensure that collection and handling of research data are in line with global best-practices.
- The large majority of primary data comes from personal interviews. Depending on the research, these 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
The following are critical steps in preparing for and conducting primary data collection:
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.