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426 – Data Quality

Improving Editing Efficiency: How a Comprehensive Program Interface Reduces the Time Cost of the Comment Review Process

at Federal Reserve Board

For complex surveys, one of the most effective tools for reducing nonsampling survey error is interviewer comments. In the Survey of Consumer Finances (SCF), these comments have been particularly useful in explaining unusual respondent situations, allowing editors to alter case data after the interview has been completed in order to restore the data to the state they should have been in had they been correctly gathered originally. However, this method of error reduction is also extraordinarily time consuming, requiring months of careful analysis by multiple editors. Furthermore, in order to even become a qualified editor, extensive training is required, necessitating even more time. Given these twin issues, any method for speeding up the training and editing processes while still maintaining the data quality improvements they generate is worth exploring. With this goal in mind, a system was designed to incorporate survey data, interviewer comments, and a series of data checks into a single, easy-to-use program interface. Perhaps most helpfully, the program also generates financial summary sheets-such as a household balance sheet and an income statement-for the quick identification of anomalies. Using this system, data editors can, at a glance, understand the basic fundamentals of a case, identify potential problems, make corrections, and then check to see that these corrections did not create further issues. The program also serves to encapsulate knowledge about the survey that previously had to be memorized during the training process. This program, named the Editor Assistant (EA), was fully employed for the 2013 SCF and was used to swiftly train three new editors and speed up the editing process. The four- to five-month reduction in required editing time-compared with previous years-has been credited in large part to the EA.