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Modeling Motivated Misreports to Sensitive Survey Questions

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  • Ulf Böckenholt

Abstract

Asking sensitive or personal questions in surveys or experimental studies can both lower response rates and increase item non-response and misreports. Although non-response is easily diagnosed, misreports are not. However, misreports cannot be ignored because they give rise to systematic bias. The purpose of this paper is to present a modeling approach that identifies misreports and corrects for them. Misreports are conceptualized as a motivated process under which respondents edit their answers before they report them. For example, systematic bias introduced by overreports of socially desirable behaviors or underreports of less socially desirable ones can be modeled, leading to more-valid inferences. The proposed approach is applied to a large-scale experimental study and shows that respondents who feel powerful tend to overclaim their knowledge. Copyright The Psychometric Society 2014

Suggested Citation

  • Ulf Böckenholt, 2014. "Modeling Motivated Misreports to Sensitive Survey Questions," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 515-537, July.
    • Handle: RePEc:spr:psycho:v:79:y:2014:i:3:p:515-537
    DOI: 10.1007/s11336-013-9390-9
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    1. van Soest, Arthur & Hurd, Michael, 2008. "A Test for Anchoring and Yea-Saying in Experimental Consumption Data," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 126-136, March.
    2. Timothy R. Johnson & Daniel M. Bolt, 2010. "On the Use of Factor-Analytic Multinomial Logit Item Response Models to Account for Individual Differences in Response Style," Journal of Educational and Behavioral Statistics, , vol. 35(1), pages 92-114, February.
    3. Dan Ariely & Nina Mazar, 2006. "Dishonesty in everyday life and its policy implications," Working Papers 06-3, Federal Reserve Bank of Boston.
    4. Leslie K. John & Alessandro Acquisti & George Loewenstein, 2011. "Strangers on a Plane: Context-Dependent Willingness to Divulge Sensitive Information," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 37(5), pages 858-873.
    5. Hugo Benítez-Silva & Moshe Buchinsky & Hiu Man Chan & Sofia Cheidvasser & John Rust, 2004. "How large is the bias in self-reported disability?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(6), pages 649-670.
    6. Ulf Böckenholt & Peter van der Heijden, 2007. "Item Randomized-Response Models for Measuring Noncompliance: Risk-Return Perceptions, Social Influences, and Self-Protective Responses," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 245-262, June.
    7. Harvey, James W. & McCrohan, Kevin F., 1988. "Voluntary compliance and the effectiveness of public and non-profit institutions: American philanthropy and taxation," Journal of Economic Psychology, Elsevier, vol. 9(3), pages 369-386, September.
    8. Tellis, Gerard J. & Chandrasekaran, Deepa, 2010. "Extent and impact of response biases in cross-national survey research," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 329-341.
    9. Sha Yang & Yi Zhao & Ravi Dhar, 2010. "Modeling the Underreporting Bias in Panel Survey Data," Marketing Science, INFORMS, vol. 29(3), pages 525-539, 05-06.
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