A ranking forced choice diagnostic classification model for psychological assessment using forced choice questionnaires

The diagnostic classification model (DCM) has been widely utilized in non-cognitive tests, offering diagnostic information on latent attributes. However, the model's reliance on single-stimulus (SS) items may lead to response biases (e.g., social desirability), jeopardizing the psychometric properties. As an alternative to SS scales, forced choice questionnaires (FCQ) can effectively control response biases. The combination of FCQs and the DCM not only circumvents response bias but also yields fine-grained diagnostic information on latent attributes. To the best of our knowledge, only one study (Huang, Educ. Psychol. Meas., 83, 2022, 146) has explored this topic and developed a DCM for forced choice (FC) items. However, the existing model has limitations in terms of its modelling assumption, the FC format and the number of attributes measured by statement. To address these limitations, this study proposes a ranking FC-DCM that (1) adopts a generalized assumption, (2) covers all FC formats and (3) eases the limitation on the number of attributes measured by each statement. The simulation study demonstrated that the proposed model exhibited satisfactory person and item parameter recovery under all conditions. This study provided an illustrative example by developing an FC version questionnaire to further explore the applications and advantages of the proposed model in real-world settings.