Influencing factors of Thurstonian IRT model in faking-resisting forced-choice questionnaire

A Monte Carlo simulation was used here to compare performance of Thurstonian IRT model across a variety of faking-resisting forced-choice designs.Intotal,24 conditions were examined by crossing the following factors: 1) number of trait (2or5); 2) items per trait(10or20); 3) percentage of pairs composed of items on the same dimension (0or20%); 4) percentage of pairs composed of items keyed in opposite directions(0,20% or40%). Larger number of traits was found to lead to more accurate estimation of model parameters,and more precise recovery of trait score. Items per trait had apositive impact on application of Thurstonian model, with a larger amount indicating more precise parametere stimation and better true trait score recovery.It had greater influence when there were not enough traits. The percentage of item pairs composed of items on the same dimensions had no significant influence on model estimates. Including a percentage of pairs with items keyed in opposite direction(20%) could greatly improve accuracy of parameter and trait score estimation. The factor impact was greater when the number of traits measured in the questionnaire was small. These results have important implications for how faking-resisting forced-choice questionnaires should be designed in the future.