The dominant trait profile method evaluates traits through binary scores, suggesting improved accuracy in scoring multidimensional forced-choice questionnaires.
Proposed is a new method of scoring multidimensional forced-choice (MFC) questionnaires referred to as the dominant trait profile (DTP) method. The DTP method identifies a dominant response vector (DRV) for each trait-a vector of binary scores for preferences in item pairs within MFC blocks from the perspective of a respondent for whom the trait under consideration dominates over the other traits being measured. The respondents' observed response vectors are matched to the DRV for each trait to produce (1/0) matching scores that are then analyzed via latent trait modeling, with scaling options (a) bounded D-scale (from 0 to 1), or (b) item response theory logit scale. The DTP method allows for the comparison of individuals on a trait of interest, as well as their standing in relation to a dominant trait "standard" (criterion). The study results indicate that DTP-based trait estimates are highly correlated with those produced by the popular Thurstonian item response theory model and the Zinnes and Griggs pairwise preference item response theory model, while avoiding the complexity of their designs and some computations issues.
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Dimiter M. Dimitrov (2025) studied this question.
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