The Generalized Graded Unfolding Model: A General Parametric Item Response Model for Unfolding Graded Responses IRT GGUM
- Author(s):
- Roberts, James S.; Donoghue, John R.; Laughlin, James E
- Publication Year:
- 1998
- Report Number:
- RR-98-32
- Source:
- ETS Research Report
- Document Type:
- Report
- Page Count:
- 63
- 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
Abstract
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.
Read More
- Request Copy (specify title and report number, if any)
- http://dx.doi.org/10.1002/j.2333-8504.1998.tb01781.x