Fitting a Mixture Item Response Theory Model to Personality Questionnaire Data: Characterizing Latent Classes and Investigating Possibilities for Improving Prediction

Mixture item response theory (IRT) models aid the interpretation of response behavior on personality tests and may provide possibilities for improving prediction. Heterogeneity in the population is modeled by identifying homogeneous subgroups that conform to different measurement models. In this study, mixture IRT models were applied to the Extroversion and Neuroticism scales of the Amsterdam Biographical Questionnaire, and a three-class mixture version of the nominal response model was identified as the best fitting model. The latent classes differed with respect to social desirability and ethnic background. Within latent classes, response tendencies demonstrated a differential use of the "?" category. An important issue is whether applying mixture IRT models results in a better prediction of relevant external criteria compared to a one-class model. For the Neuroticism scale the prediction improved, but not for the Extraversion scale. The results demonstrate the possible advantage of applying mixture IRT models to personality questionnaires.