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thurstonianIRT: Thurstonian IRT Models in R

Bürkner, Paul-Christian

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  <dc:creator>Bürkner, Paul-Christian</dc:creator>
  <dc:description>The thurstonianIRT package allows to fit various models from Item Response Theory (IRT) for forced-choice questionnaires, most notably the Thurstonian IRT model originally proposed by Brown and Maydeu-Olivares (2011). IRT in general comes with several advantages over classical test theory, for instance, the ability to model varying item difficulties as well as item factor loadings on the participants’ traits they are supposed to measure. Moreover, if multiple traits are modeled at the same time, their correlation can be incorporated into an IRT model to improve the overall estimation accuracy. The key characteristic of forced-choice questionnaires is that participants cannot endorse all items at the same time and instead have to make a comparative judgment between two or more items. Such a format comes with the hope of providing more valid inference in situation where participants have motivation to not answer honestly (e.g., in personnel selection), but instead respond in a way that appears favorable in the given situation. Whether forced-choice questionnaires and the corresponding IRT models live up to this hope remains a topic of debate (e.g., see Bürkner, Schulte, &amp; Holling, 2019) but it is in any case necessary to provide software for fitting these statistical models both for practical and research purposes.



Brown, A., &amp; Maydeu-Olivares, A. (2011). Item response modeling of forced-choice questionnaires. Educational and Psychological Measurement, 71(3), 460-502.

Bürkner P. C., Schulte N., &amp; Holling H. (2019). On the Statistical and Practical Limitations of Thurstonian IRT Models. Educational and Psychological Measurement.</dc:description>
  <dc:subject>item response theory</dc:subject>
  <dc:subject>forced-choice data</dc:subject>
  <dc:title>thurstonianIRT: Thurstonian IRT Models in R</dc:title>
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