Uncertainty in Latent Trait Models. Issue 6 (September 2020)

• Record Type: Journal Article
• Authors: Tutz, Gerhard; Schauberger, Gunther
• Is Part Of: Applied psychological measurement. Volume 44:Issue 6(2020)
• Page Start: 447
• Page End: 464
• Publication Date: 2020-09
• Subjects: Rasch model -- partial credit model -- rating scales -- response styles -- ordinal data -- heterogeneity -- dispersion; Psychometrics -- Periodicals; Psychological tests -- Periodicals; Psychology, Applied -- Periodicals; 150.1519505
• DOI: 10.1177/0146621620920932
• Languages: English
• ISSNs: 0146-6216

Abstract

A model that extends the Rasch model and the Partial Credit Model to account for subject-specific uncertainty when responding to items is proposed. It is demonstrated that ignoring the subject-specific uncertainty may yield biased estimates of model parameters. In the extended version of the model, uncertainty and the underlying trait are linked to explanatory variables. The parameterization allows to identify subgroups that differ in uncertainty and the underlying trait. The modeling approach is illustrated using data on the confidence of citizens in public institutions.