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Identifying Data Quality Challenges in Online Opt-In Panels Using Cognitive Interviews in English and Spanish

Author

Listed:
  • Trejo Yazmín García
  • Meyers Mikelyn
  • Martinez Mandi
  • O’Brien Angela
  • Goerman Patricia
  • Class Betsarí Otero

    (U.S. Census Bureau, 4600 Silver Hill Road, Suitland-Silver Hill, MD 20746, U.S.A.)

Abstract

In this article, we evaluate how the analysis of open-ended probes in an online cognitive interview can serve as a metric to identify cases that should be excluded due to disingenuous responses by ineligible respondents. We analyze data collected in 2019 via an online opt-in panel in English and Spanish to pretest a public opinion questionnaire (n = 265 in English and 199 in Spanish). We find that analyzing open-ended probes allowed us to flag cases completed by respondents who demonstrated problematic behaviors (e.g., answering many probes with repetitive textual patterns, by typing random characters, etc.), as well as to identify cases completed by ineligible respondents posing as eligible respondents (i.e., non-Spanish-speakers posing as Spanish-speakers). These findings indicate that data collected for multilingual pretesting research using online opt-in panels likely require additional evaluations of data quality. We find that open-ended probes can help determine which cases should be replaced when conducting pretesting using opt-in panels. We argue that open-ended probes in online cognitive interviews, while more time consuming and expensive to analyze than close-ended questions, serve as a valuable method of verifying response quality and respondent eligibility, particularly for researchers conducting multilingual surveys with online opt-in panels.

Suggested Citation

  • Trejo Yazmín García & Meyers Mikelyn & Martinez Mandi & O’Brien Angela & Goerman Patricia & Class Betsarí Otero, 2022. "Identifying Data Quality Challenges in Online Opt-In Panels Using Cognitive Interviews in English and Spanish," Journal of Official Statistics, Sciendo, vol. 38(3), pages 793-822, September.
    • Handle: RePEc:vrs:offsta:v:38:y:2022:i:3:p:793-822:n:6
    DOI: 10.2478/jos-2022-0035
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    References listed on IDEAS

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    1. Jennifer Edgar & Joe Murphy & Michael Keating, 2016. "Comparing Traditional and Crowdsourcing Methods for Pretesting Survey Questions," SAGE Open, , vol. 6(4), pages 21582440166, October.
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