Difference between revisions of "Iefieldkit"
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<code>iefieldkit</code> is a package of Stata commands that standardizes and simplifies best practices for high-quality, [[Reproducible Research | reproducible]], [[Primary Data Collection | primary data collection]]. This package | <code>iefieldkit</code> is a package of Stata commands that standardizes and simplifies best practices for high-quality, [[Reproducible Research | reproducible]], [[Primary Data Collection | primary data collection]]. This package contains commands that support three major components of data workflow: survey design; survey completion; and data cleaning and survey harmonization. This page will explain the package's commands and what they do. | ||
==Read First== | ==Read First== | ||
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*All commands in the package can be used independently, and are developed for use in a wide range contexts. | *All commands in the package can be used independently, and are developed for use in a wide range contexts. | ||
*See the open-source code on GitHub [https://github.com/worldbank/iefieldkit here] for public contribution and comment. | *See the open-source code on GitHub [https://github.com/worldbank/iefieldkit here] for public contribution and comment. | ||
*To install the package, type <code>ssc install iefieldkit</code> in the Stata command box. | |||
==Overview== | ==Overview== |
Revision as of 21:06, 10 May 2019
iefieldkit
is a package of Stata commands that standardizes and simplifies best practices for high-quality, reproducible, primary data collection. This package contains commands that support three major components of data workflow: survey design; survey completion; and data cleaning and survey harmonization. This page will explain the package's commands and what they do.
Read First
iefieldkit
aims to provide Stata-based tools for managing the primary data collection process from start to finish.iefieldkit
currently consists of four commands:ietestform
,ieduplicates
,iecompdup
, andiecodebook
.- All commands in the package can be used independently, and are developed for use in a wide range contexts.
- See the open-source code on GitHub here for public contribution and comment.
- To install the package, type
ssc install iefieldkit
in the Stata command box.
Overview
One of the most important developments in economics research over the past two decades has been the rise of empirical data collection, especially with unique primary datasets collected by the researchers themselves. The authors of iefieldkit
have supported the implementation of a wide range of primary data collection in fields including agriculture, health, energy and environment, edutainment, financial and private sector development, fragility, conflict, violence, gender, governance, and transport. They have developed workflows to support general best practices for data collection. As a rule, they develop new packages only in order to fill an essential gap in Stata functionality. iefieldkit
aims to provide Stata-based tools for managing the primary data collection process from start to finish.
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.
Commands
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.
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