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Primary data collection and cleaning involve highly repetitive but extremely important processes that contribute to high quality reproducible research. DIME Analytics has developed iefieldkit as a package in Stata to standardize and simplify best practices involved in primary data collection. Iefieldkit consists of commands that automate: error-checking for electronic Open Data Kit (ODK)-based survey modules; duplicate checking and resolution; data cleaning and survey harmonization; and codebook creation.

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One of the most important developments in economics research over the past two decades has been the rise of empirical data collection - both primary and secondary. \citep{angrist2017economic}. The authors have developed iefieldkit to support the implementation of primary data collection in a wide rage of fields like agriculture, health, energy and environment, transport, financial and private sector development, gender, governance, and fragility, conflict and violence (FCV). iefieldkit supports general best practices for data collection.

Each command in this package - All commands utilize spreadsheet-based workflows so that their inputs and outputs are significantly more human-readable than Stata do files completing the same tasks would be. These tasks can be supported and reviewed by personnel who specialize in field work rather than code tools. The increasing diversity and specialization of research teams has made accessibility to non-Stata-proficient personnel an essential component of data management workflows, and this package takes this development seriously.


Before Data Collection

Before data collection occurs, ietestform allows for rapid error-checking of ODK-based electronic surveys, including best practices for SurveyCTO-styled forms. This ensures that data, once collected, will import in Stata-friendly formats -- such as avoiding name conflicts and ensuring compliant variable naming and labelling.

complements the ODK syntax test on SurveyCTO server. It runs tests to inform researchers how to use ODK programming language features to ensure high data quality. This command is especially useful if the data that will be imported to Stata has other restrictions in addition to ODK syntax.

During Data Collection

During data collection, ieduplicates and iecompdup (both previously released as a part of the package ietoolkit but now moved to this package) provide a workflow for detecting and resolving duplicate entries in the dataset, ensuring that the final survey dataset will be a correct record of the survey sample to merge onto the master sampling database.

After Data Collection

After data collection, the iecodebook commands provide a workflow for rapidly cleaning, harmonizing, and documenting datasets. iecodebook uses input specified in an Excel sheet, which provides a much more well-structured and easy to follow overview – especially for non-technical users – than the same operations written directly to a dofile.

Additional Resources

  • Visit the iefieldkit GitHub page here