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iefieldkit: Stata commands for primary data collection and cleaning

Author

Listed:
  • Benjamin Daniels

    (World Bank Development Research Group, Impact Evaluations (DIME))

  • Luiza Cardoso de Andrade

    (The World Bank Group)

  • Kristoffer Bjarkefur

    (The World Bank Group)

Abstract

Data collection and cleaning workflows use highly repetitive but extremely important processes. -iefieldkit- was developed to standardize and simplify best practices for high-quality primary data collection across the 100+ members of the World Bank's Development Research Group, Impact Evaluations team (DIME). It automates: error-checking for electronic ODK-based survey modules such as those implemented in SurveyCTO; duplicate checking and resolution; data cleaning including renaming, labeling, recoding, and survey harmonization; and codebook creation. The presentation will outline how the -iefieldkit- package is intended to provide a data collection workflow skeleton for nearly any type of primary data collection, from questionnaire design to data import. One feature of many -iefieldkit- commands is their utilization of spreadsheet-based workflows, which reduce repetitive coding in Stata and document corrections and cleaning in a human-readable format. This enables rapid review of data quality in a standardized process, with the goal of producing maximally clean primary data for the downstream data construction and analysis phases in a transparent and accessible manner. These tools are developed open-source on GitHub and available publicly.

Suggested Citation

  • Benjamin Daniels & Luiza Cardoso de Andrade & Kristoffer Bjarkefur, 2019. "iefieldkit: Stata commands for primary data collection and cleaning," 2019 Stata Conference 11, Stata Users Group.
  • Handle: RePEc:boc:scon19:11
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