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Joint modeling of the two-alternative multidimensional forced-choice personality measurement and its response time by a Thurstonian D-diffusion item response model.

Kyosuke BunjiKensuke Okada
Published in: Behavior research methods (2020)
The two-alternative multidimensional forced-choice measurement of personality has attracted researchers' attention for its tolerance to response bias. Moreover, the response time can be collected along with the item response when personality measurement is conducted with computers. In view of this situation, the objective of this study is to propose a Thurstonian D-diffusion item response theory (IRT) model, which combines two key existing frameworks: the Thurstonian IRT model for forced-choice measurement and the D-diffusion IRT model for the response time in personality measurement. The proposed model reflects the psychological theories behind the data-generating mechanism of the item response and response time. A simulation study reveals that the proposed model can successfully recover the parameters and factor structure in typical application settings. A real data application reveals that the proposed model estimates similar but still different parameter values compared to the original Thurstonian IRT model, and this difference can be explained by the response time information. In addition, the proposed model successfully reflects the distance-difficulty relationship between the response time and the latent relative respondent position.
Keyphrases
  • machine learning
  • big data
  • electronic health record
  • data analysis