Authors’ response to comments on “Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith”

Articles and reports: 12-001-X202400100009

Description: Our comments respond to discussion from Sen, Brick, and Elliott. We weigh the potential upside and downside of Sen’s suggestion of using machine learning to identify bogus respondents through interactions and improbable combinations of variables. We join Brick in reflecting on bogus respondents’ impact on the state of commercial nonprobability surveys. Finally, we consider Elliott’s discussion of solutions to the challenge raised in our study.
Issue Number: 2024001
Author(s): Kennedy, Courtney; Mercer, Andrew; Lau, Arnold

Main Product: Survey Methodology

FormatRelease dateMore information
HTMLJune 25, 2024
PDFJune 25, 2024

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