LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Maydeu-Olivares, Alberto; Brown, Anna (2010)
Languages: English
Types: Article
Subjects: HA
The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally presented as scaling models, that is, stimuli-centered models, they can also be used as person-centered models. In this article, we discuss how Thurstone's model for comparative data can be formulated as item response theory models so that respondents' scores on underlying dimensions can be estimated. Item parameters and latent trait scores can be readily estimated using a widely used statistical modeling program. Simulation studies show that item characteristic curves can be accurately estimated with as few as 200 observations and that latent trait scores can be recovered to a high precision. Empirical examples are given to illustrate how the model may be applied in practice and to recommend guidelines for designing ranking and paired comparisons tasks in the future.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • data: Limited vs. full information methods. " $ ( $ , &,, 275 299.
    • Holland, J. L. (1997). ( $ + $ (3rd ed.). Eglewood Cliffs, NJ: Prentice Hall.
    • Yang, M., Inceoglu, I. & Silvester, J. (2010). Exploring ways of measuring Person Job fit to predict engagement. " $ 7" 9 : ) " $ ( , January 13 15, Brighton, UK.
    • Maydeu Olivares, A. (1999). Thurstonian modeling of ranking data via mean and covariance structure analysis. " $ , -,, 325 340.
    • Maydeu Olivares, A. (2001). Limited information estimation and testing of Thurstonian models for paired comparison data under multiple judgment sampling.
    • Maydeu Olivares, A. (2002). Limited information estimation and testing of Thurstonian models for preference data. $ , ,;, 467 483.
    • Maydeu Olivares, A. & Böckenholt, U. (2005). Structural equation modeling of paired comparisons and ranking data. " $ ( $ , &2, 285 304.
    • Maydeu Olivares, A. & Coffman, D. L. (2006). Random intercept item factor analysis.
    • Maydeu Olivares, A. & Hernández, A. (2007). Identification and small sample estimation of Thurstone's unrestricted model for paired comparisons data. ) 7 $ $, ,*, 323 347.
    • McDonald, R.P. (1999). $ ' ) $. Mahwah, NJ: Lawrence Erlbaum.
    • Murphy, K. R., Jako, R. A., & Anhalt, R. L. (1993). Nature and consequences of halo error: A critical analysis. 4 ) " $ ( , 78, 218 225.
    • Muthén, L.K. & Muthén, B. (1998 2007). Mplus 5. Los Angeles, CA: Muthén & Muthén.
    • Muthén, B., du Toit, S.H.C. & Spisic, D. (1997). %) ) ( ($ ) % ( $ . Unpublished manuscript. College of Education, 2 ψ 2 ψ 2 ψ + ψ 0 η
  • No related research data.
  • Discovered through pilot similarity algorithms. Send us your feedback.

Share - Bookmark

Download from

Cite this article