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ERIC Number: ED430001
Record Type: Non-Journal
Publication Date: 1999-Apr
Pages: 15
Abstractor: N/A
Reference Count: N/A
ISBN: N/A
ISSN: N/A
Estimability of Parameters in the Generalized Graded Unfolding Model.
Roberts, James S.; Donoghue, John R.; Laughlin, James E.
The generalized graded unfolding model (GGUM) (J. Roberts, J. Donoghue, and J. Laughlin, 1998) is an item response theory model designed to analyze binary or graded responses that are based on a proximity relation. The purpose of this study was to assess conditions under which item parameter estimation accuracy increases or decreases, with special attention paid to the influence that a given item parameter value has on the estimation of another item parameter. This assessment was based on a recovery simulation in which the effects of sample size, item location, degree of item discrimination, and extremity of subjective category thresholds were varied. Results indicate that with 750 or more respondents, sample size has negligible effect on all but the estimation of subjective response category thresholds. The true extremity of both item location and item discrimination did affect the estimation of these parameters themselves, and also affected the estimation of other item parameters in the model. However, these effects were modest and had little impact on the estimation of the corresponding item response functions. These results suggest that marginal maximum likelihood estimates of item parameters will provide accurate results across a variety of item parameter configurations when the sample size is at or above the recommended levels. (Contains 1 table, 3 figures, and 14 references.) (Author/SLD)
Publication Type: Reports - Evaluative; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A