#3209. Investigating the Normativity of Trait Estimates from Multidimensional Forced-Choice Data

October 2026publication date
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Journal’s subject area:
Statistics and Probability;
Arts and Humanities (miscellaneous);
Experimental and Cognitive Psychology;
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Abstract:
The Thurstonian item response model (Thurstonian IRT model) allows deriving normative trait estimates from multidimensional forced-choice (MFC) data. In the MFC format, persons must rank-order items that measure different attributes according to how well the items describe them. This study evaluated the normativity of Thurstonian IRT trait estimates both in a simulation and empirically. The results showed that, with blocks of opposite keyed items, Thurstonian IRT trait estimates were normative in contrast to classical partially ipsative estimates. Measurement precision was lower than that of rating scale data. Criterion validity was equal and construct validity lower in MFC. Thurstonian IRT modeling of MFC data overcomes the drawbacks of classical scoring, but gains in validity may depend on eliminating common method biases from the comparison.
Keywords:
Forced-choice format; ipsative data; rating scale; Thurstonian IRT model; true-false

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