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Correcting for Acquiescent Response Bias in the Absence of a Balanced Scale



    (Indiana University, Bloomington)


This article describes a method for purging data of the effects of acquiescent response bias—a tendency to respond in the affirmative to survey items irrespective of substantive content—in the absence of a balanced scale (a scale with an equal number of positively worded and negatively worded items). The method is relevant in situations where the scale of interest is not balanced but where items similar in form from another content area are available to help identify acquiescence; it is illustrated here using data on class consciousness. Structural equation modeling techniques are used to extract a factor that captures the covariation among the items that is due to acquiescence. A series of models is presented illustrating the procedure on data from the Comparative Project on Class Structure and Class Consciousness for the United States. The model is then cross-validated on samples from Canada, Norway, and Sweden.

Suggested Citation

  • Dorothy Watson, 1992. "Correcting for Acquiescent Response Bias in the Absence of a Balanced Scale," Sociological Methods & Research, , vol. 21(1), pages 52-88, August.
  • Handle: RePEc:sae:somere:v:21:y:1992:i:1:p:52-88

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    Cited by:

    1. Stephen Fox, 2018. "Irresponsible Research and Innovation? Applying Findings from Neuroscience to Analysis of Unsustainable Hype Cycles," Sustainability, MDPI, Open Access Journal, vol. 10(10), pages 1-16, September.
    2. Watson, Dorothy, 2011. "Quality of Public Services: Irish Public Perceptions and Implications for Renewal," Papers EC6, Economic and Social Research Institute (ESRI).
    3. Chau-kiu Cheung & Raymond Chan, 2010. "Social Capital as Exchange: Its Contribution to Morale," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 96(2), pages 205-227, April.
    4. Maike Schulz, 2012. "Messartefakte bei der Erfassung der Gesundheit von Migranten in Deutschland: zur interkulturellen Äquivalenz des SF-12-Fragebogen im Sozio-oekonomischen Panel (SOEP)," SOEPpapers on Multidisciplinary Panel Data Research 447, DIW Berlin, The German Socio-Economic Panel (SOEP).
    5. Jean-Charles Pillet & Claudio Vitari & Federico Pigni & Kevin Carillo, 2018. "Detecting Biased Items When Developing a Scale: A Quantitative Method," Grenoble Ecole de Management (Post-Print) halshs-01923612, HAL.
    6. Kristiina Janhunen, 2012. "A comparison of Likert-type rating and visually-aided rating in a simple moral judgment experiment," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(5), pages 1471-1477, August.
    7. Alain De Beuckelaer & Bert Weijters & Anouk Rutten, 2010. "Using ad hoc measures for response styles: a cautionary note," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(4), pages 761-775, June.
    8. van Rosmalen, J.M. & van Herk, H. & Groenen, P.J.F., 2007. "Identifying Unknown Response Styles: A Latent-Class Bilinear Multinomial Logit Model," ERIM Report Series Research in Management ERS-2007-045-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

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