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Nothing but the truth? Effects of faking on the validity of the crosswise model

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  • Adrian Hoffmann
  • Julia Meisters
  • Jochen Musch

Abstract

In self-reports, socially desirable responding threatens the validity of prevalence estimates for sensitive personal attitudes and behaviors. Indirect questioning techniques such as the crosswise model attempt to control for the influence of social desirability bias. The crosswise model has repeatedly been found to provide more valid prevalence estimates than direct questions. We investigated whether crosswise model estimates are also less susceptible to deliberate faking than direct questions. To this end, we investigated the effect of “fake good” instructions on responses to direct and crosswise model questions. In a sample of 1,946 university students, 12-month prevalence estimates for a sensitive road traffic behavior were higher and thus presumably more valid in the crosswise model than in a direct question. Moreover, “fake good” instructions severely impaired the validity of the direct questioning estimates, whereas the crosswise model estimates were unaffected by deliberate faking. Participants also reported higher levels of perceived confidentiality and a lower perceived ease of faking in the crosswise model compared to direct questions. Our results corroborate previous studies finding the crosswise model to be an effective tool for counteracting the detrimental effects of positive self-presentation in surveys on sensitive issues.

Suggested Citation

  • Adrian Hoffmann & Julia Meisters & Jochen Musch, 2021. "Nothing but the truth? Effects of faking on the validity of the crosswise model," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-20, October.
    • Handle: RePEc:plo:pone00:0258603
    DOI: 10.1371/journal.pone.0258603
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    1. repec:cup:judgdm:v:11:y:2016:i:5:p:527-536 is not listed on IDEAS
    2. Ivar Krumpal, 2013. "Determinants of social desirability bias in sensitive surveys: a literature review," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2025-2047, June.
    3. Thorben C. Kundt & Florian Misch & Birger Nerré, 2017. "Re-assessing the merits of measuring tax evasion through business surveys: an application of the crosswise model," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 24(1), pages 112-133, February.
    4. Elisabeth Coutts & Ben Jann, 2011. "Sensitive Questions in Online Surveys: Experimental Results for the Randomized Response Technique (RRT) and the Unmatched Count Technique (UCT)," Sociological Methods & Research, , vol. 40(1), pages 169-193, February.
    5. Xiangen Hu & William Batchelder, 1994. "The statistical analysis of general processing tree models with the EM algorithm," Psychometrika, Springer;The Psychometric Society, vol. 59(1), pages 21-47, March.
    6. Marc Höglinger & Ben Jann, 2018. "More is not always better: An experimental individual-level validation of the randomized response technique and the crosswise model," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-22, August.
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