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The Generalized Graded Unfolding Model: A General Parametric Item Response Model for Unfolding Graded Responses IRT GGUM

Roberts, James S.; Donoghue, John R.; Laughlin, James E
Publication Year:
Report Number:
ETS Research Report
Document Type:
Page Count:
Subject/Key Words:
Attitude Measures, Item Response Models, Thurstone Scales, Likert Scales, Item Response Theory (IRT), Unfolding Technique, Generalized Graded Unfolding Model (GGUM), Student Attitudes


Second, the GGUM allows for a distinctively different use of response categories across items. It does this by implementing response category threshold parameters that vary across items. A marginal maximum likelihood algorithm is implemented to estimate GGUM item parameters, whereas person parameters are derived from an expected a posteriori technique. Recovery simulations suggest that accurate item parameter estimates can be obtained with approximately 750 subjects. Additionally, accurate person estimates are derived with approximately 20 6-category items. The applicability of the GGUM to common attitude testing situations is illustrated with real data on student attitudes toward abortion.

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