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ERIC Number: EJ798020
Record Type: Journal
Publication Date: 2008
Pages: 17
Abstractor: As Provided
Reference Count: 18
ISBN: N/A
ISSN: ISSN-0146-6216
Modified Likelihood-Based Item Fit Statistics for the Generalized Graded Unfolding Model
Roberts, James S.
Applied Psychological Measurement, v32 n5 p407-423 2008
Orlando and Thissen (2000) developed an item fit statistic for binary item response theory (IRT) models known as S-X[superscript 2]. This article generalizes their statistic to polytomous unfolding models. Four alternative formulations of S-X[superscript 2] are developed for the generalized graded unfolding model (GGUM). The GGUM is a unidimensional IRT model for unfolding polytomous responses. It yields single-peaked, non-monotonic item characteristic curves that predict a higher item score to the extent that an individual is located close to an item on the underlying latent continuum. A simulation was performed to examine the characteristics of these new item fit indices under the GGUM, as well as a traditional likelihood ratio x[superscript 2] test (G[superscript 2]). All variants of S-X[superscript 2] exhibited reasonable Type I error rates, but that for G[superscript 2] was more erratic. The new indices exhibited variable power to detect misfit. Two new item fit tests are recommended for use based on simulation results. (Contains 1 figure and 4 tables.)
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: Researchers
Language: English
Sponsor: N/A
Authoring Institution: N/A