Kristoffer Bjärkefur, Luíza Cardoso de Andrade, Benjamin Daniels
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引用次数: 0
Abstract
Data collection and cleaning workflows implement highly repetitive but extremely important processes. In this article, we describe an update to iefieldkit, a package developed to standardize and simplify best practices for high-quality primary data collection across the World Bank’s Development Impact Evaluation department. The first release of iefieldkit provided workflows to automate error checking for Open Data Kit-based survey modules, duplicate management, data cleaning, and codebook creation. This update to the package includes improved commands to document and implement data point corrections, verify the structure or contents of data using codebooks, and create replicationready data through automated variable subsetting.
数据收集和清理工作流程实现了高度重复但极其重要的过程。在本文中,我们介绍了iefieldkit的更新,该工具包是为规范和简化世界银行发展影响评估部门高质量原始数据收集的最佳实践而开发的。iefieldkit的第一个版本提供了工作流来自动检查基于Open Data kit的调查模块、副本管理、数据清理和代码本创建的错误。该包的更新包括改进的命令,用于记录和实现数据点更正,使用代码本验证数据的结构或内容,以及通过自动变量子集创建可复制数据。
期刊介绍:
The Stata Journal is a quarterly publication containing articles about statistics, data analysis, teaching methods, and effective use of Stata''s language. The Stata Journal publishes reviewed papers together with shorter notes and comments, regular columns, book reviews, and other material of interest to researchers applying statistics in a variety of disciplines.