A Comparison of Ideal-Point and Dominance Response Processes with a Trust in Science Thurstone Scale

  • Samuel WilgusEmail author
  • Justin Travis
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 265)


The purpose of this study is to compare the dominance and ideal-point response process models for a trust in science measure developed from Thurstone’s (Am J Sociol 33(4):529–554, 1928; Psychol Rev 36(3):222–241, 1929) scaling procedures. The trust in science scale was scored in four different ways: (1) a dominance response approach using observed scores, (2) a dominance response approach using model-based trait estimates, (3) an ideal-point response observed score approach using Thurstone scoring, and (4) an ideal-point response approach using model-based trait estimates. Comparisons were made between the four approaches in terms of psychometric properties and correlations with political beliefs, education level, and beliefs about scientific consensus in a convenience sample of 401 adults. Results suggest that both the ideal-point and two-parameter IRT models fit equally well in terms of overall model fit. However, two items demonstrated poor item fit in the two-parameter model. Correlations with political beliefs, education level, and science-related items revealed very little differences in magnitude across the four scoring procedures. This study shows support for the flexibility of the ideal-point IRT model for capturing non-ideal-point response patterns. The study also demonstrates the use of using IRT to examine item parameters and item fit.


Dominance response process Ideal-point response process Thurstone scaling 


  1. Borman, W. C., Penner, L. A., Allen, T. D., & Motowidlo, S. J. (2001). Personality predictors of citizenship performance. International Journal of Selection and Assessment, 9(1–2), 52–69.Google Scholar
  2. Chernyshenko, O. S., Stark, S., Drasgow, F., & Roberts, B. W. (2007). Constructing personality scales under the assumptions of an ideal point response process: Toward increasing the flexibility of personality measures. Psychological Assessment, 19(1), 88–106.CrossRefGoogle Scholar
  3. Chernyshenko, O. S., Stark, S., Prewett, M. S., Gray, A. A., Stilson, F. R., & Tuttle, M. D. (2009). Normative scoring of multidimensional pairwise preference personality scales using IRT: Empirical comparisons with other formats. Human Performance, 22(2), 105–127.CrossRefGoogle Scholar
  4. Coombs, C. H. (1964). A theory of data. New York: Wiley.Google Scholar
  5. Drasgow, F., Chernyshenko, O. S., & Stark, S. (2009). Test theory and personality measurement. Oxford Handbook of Personality Assessment, 59–80.Google Scholar
  6. Drasgow, F., Chernyshenko, O. S., & Stark, S. (2010). 75 years after Likert: Thurstone was right! Industrial and Organizational Psychology, 3(4), 465–476.CrossRefGoogle Scholar
  7. Funk, C., & Rainie, L. (2015). Americans, politics, and science issues. Retrieved from:
  8. Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 140, 5–53.Google Scholar
  9. Maydeu-Olivares, A., Hernández, A., & McDonald, R. P. (2006). A multidimensional ideal point item response theory model for binary data. Multivariate Behavioral Research, 41(4), 445–472.CrossRefGoogle Scholar
  10. McCright, A. M. (2010). The effects of gender on climate change knowledge and concern in the american public. Population and Environment, 32(1), 66–87. Scholar
  11. Meade, A. W. (2004). Psychometric problems and issues involved with creating and using ipsative measures for selection. Journal of Occupational and Organizational Psychology, 77(4), 531–551.MathSciNetCrossRefGoogle Scholar
  12. Orlando, M., & Thissen, D. (2003). Further investigation of the performance of S-X2: An item fit index for use with dichotomous item response theory models. Applied Psychological Measurement, 27(4), 289–298.MathSciNetCrossRefGoogle Scholar
  13. Roberts, J. S., Donoghue, J. R., & Laughlin, J. E. (2000). A general item response theory model for unfolding unidimensional polytomous responses. Applied Psychological Measurement, 24(1), 3–32.CrossRefGoogle Scholar
  14. Roberts, J. S., & Laughlin, J. E. (1996). A unidimensional item response model for unfolding responses from a graded disagree-agree response scale. Applied Psychological Measurement, 20(3), 231–255.CrossRefGoogle Scholar
  15. Stark, S., Chernyshenko, O. S., Drasgow, F., & Williams, B. A. (2006). Examining assumptions about item responding in personality assessment: Should ideal point methods be considered for scale development and scoring? Journal of Applied Psychology, 91(1), 25–39.CrossRefGoogle Scholar
  16. Thurstone, L. L. (1928). Attitudes can be measured. American Journal of Sociology, 33(4), 529–554.CrossRefGoogle Scholar
  17. Thurstone, L. L. (1929). Theory of attitude measurement. Psychological Review, 36(3), 222–241.CrossRefGoogle Scholar
  18. Thurstone, T. G. (1932). The difficulty of a test and its diagnostic value. Journal of Educational Psychology, 23(5), 335.CrossRefGoogle Scholar
  19. Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The Psychology of Survey Response. Cambridge: Cambridge University Press.Google Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.North Carolina State UniversityRaleighUSA
  2. 2.University of South Carolina UpstateSpartanburgUSA

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