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ERIC Number: EJ792215
Record Type: Journal
Publication Date: 2008-Jan
Pages: 19
Abstractor: Author
Reference Count: 19
ISSN: ISSN-0895-7347
Investigation of a Nonparametric Procedure for Assessing Goodness-of-Fit in Item Response Theory
Wells, Craig S.; Bolt, Daniel M.
Applied Measurement in Education, v21 n1 p22-40 Jan 2008
Tests of model misfit are often performed to validate the use of a particular model in item response theory. Douglas and Cohen (2001) introduced a general nonparametric approach for detecting misfit under the two-parameter logistic model. However, the statistical properties of their approach, and empirical comparisons to other methods, have not been examined. In the present study, a Monte Carlo simulation study was used to examine the empirical Type I error rates and power of two nonparametric statistics based on the Douglas and Cohen (2001) approach. The procedures are compared to two commonly used goodness-of-fit statistics, "S-X[superscript 2]" (Orlando & Thissen, 2000) and BILOG's G[superscript 2] (Mislevy & Bock, 1990), across conditions varied by test length, sample size, and the percentage of misfitting items. Overall, the nonparametrically based statistics controlled the Type I error rate and exhibited the most power across all conditions. Due to its close association with a graphical representation of the item response function, it is argued that the Douglas and Cohen (2001) approach may also allow for a more informative inspection of the type of misfit that is present in test items, although at a slightly greater computational cost. (Contains 6 figures and 3 tables.)
Lawrence Erlbaum. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A