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.
- Stata coding practices.
- DIME Analytics Bootcamp on Reproducible Research.
iefieldkitaims to provide Stata-based tools for managing the primary data collection process from start to finish.
iefieldkitcurrently consists of four commands:
- Each of these commands can be used independently in a wide range contexts.
- The open-source code for
iefieldkitis available on GitHub for public contribution and comment.
- To install the package, type
ssc install iefieldkitin the Stata command box.
One of the most important developments in economics over the past two decades has been the rise of empirical research, through primary as well as secondary data collection. The authors of
iefieldkit have developed the package to support data collection by researchers directly in a wide range of fields like agriculture, health, energy and environment, transport, financial and private sector development, gender, governance, and fragility, conflict and violence (FCV).
iefieldkit therefore supports general best practices in primary data collection from start to finish:
- Before data collection.
- During data collection.
- After data collection.
These four commands in this package make sure that inputs and outputs are significantly more human-readable by working with spreadsheets instead of Stata do-files. In doing so, they allow field personnel who do not specialize in code tools to understand and review the tasks involved in primary data collection.
iefieldkit thus recognizes the vital role played by field personnel in supporting data management and data cleaning even if they are not proficient in Stata.
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,
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.
- Visit the
iefieldkitGitHub page here