Data collection and cleaning workflows implement highly repetitive but extremely important processes. In this article, we introduce iefieldkit, a package developed to standardize and simplify best practices for high-quality primary data collection across the World Bank’s Development Research Group Impact Evaluations department. iefieldkit automates error-checking for electronic Open Data Kit-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.
Some rights reserved 1 2 3 4 24 23 22 21This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy, completeness, or currency of the data included in this work and does not assume responsibility for any errors, omissions, or discrepancies in the information, or liability with respect to the use of or failure to use the information, methods, processes, or conclusions set forth. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.Nothing herein shall constitute or be construed or considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved.
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