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Methodological Artifacts in Measures of Political Efficacy and Trust: A Multiple Correspondence Analysis

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  • Blasius, Jörg
  • Thiessen, Victor

Abstract

Many authors report a positive relationship of education and political interest with political efficacy and trust, but it is well known that both of the former are associated with response styles, such as a tendency to “strongly agree.” Since they are related to both a substantive concept (political efficacy and trust), and to methodological effects (agreement bias and a tendency to give non-substantive responses) it is important to assess whether the substantive relationship is due to methodological artifacts. Applying multiple correspondence analysis to the 1984 Canadian National Election Study, we will discuss a method which allows to test a set of items for measurement effects such as ordinality and response sets. In the given example, ordinality of the political efficacy and trust items could be confirmed only for politically interested respondents. For respondents with low political interest, there is clear evidence of a response set resulting in a tendency to “strongly agree” regardless of the direction of the items. Taken together, these findings call into question the substantive relationships reported in the literature.

Suggested Citation

  • Blasius, Jörg & Thiessen, Victor, 2001. "Methodological Artifacts in Measures of Political Efficacy and Trust: A Multiple Correspondence Analysis," Political Analysis, Cambridge University Press, vol. 9(1), pages 1-20, January.
    • Handle: RePEc:cup:polals:v:9:y:2001:i:01:p:1-20_00
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    Cited by:

    1. David Bholat & Stephen Hans & Pedro Santos & Cheryl Schonhardt-Bailey, 2015. "Text mining for central banks," Handbooks, Centre for Central Banking Studies, Bank of England, number 33, April.
    2. Dmitriy Poznyak & Bart Meuleman & Koen Abts & George Bishop, 2014. "Trust in American Government: Longitudinal Measurement Equivalence in the ANES, 1964–2008," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 118(2), pages 741-758, September.
    3. Jörg Blasius & John Gower, 2005. "Multivariate Prediction with Nonlinear Principal Components Analysis: Application," Quality & Quantity: International Journal of Methodology, Springer, vol. 39(4), pages 373-390, August.

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