Uncertainty in Latent Trait Models

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,...

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Bibliographic Details
Published inApplied psychological measurement Vol. 44; no. 6; pp. 447 - 464
Main Authors Tutz, Gerhard, Schauberger, Gunther
Format Journal Article
LanguageEnglish
Published Los Angeles, CA SAGE Publications 01.09.2020
Subjects
ordinal data
partial credit model
rating scales
response styles
Rasch model
dispersion
heterogeneity
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Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0146-6216
1552-3497
1552-3497
DOI:10.1177/0146621620920932