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ERIC Number: EJ792208
Record Type: Journal
Publication Date: 2008-Jan
Pages: 24
Abstractor: Author
Reference Count: 29
ISSN: ISSN-0895-7347
Estimating Non-Normal Latent Trait Distributions within Item Response Theory Using True and Estimated Item Parameters
Sass, D. A.; Schmitt, T. A.; Walker, C. M.
Applied Measurement in Education, v21 n1 p65-88 Jan 2008
Item response theory (IRT) procedures have been used extensively to study normal latent trait distributions and have been shown to perform well; however, less is known concerning the performance of IRT with non-normal latent trait distributions. This study investigated the degree of latent trait estimation error under normal and non-normal conditions using four latent trait estimation procedures and also evaluated whether the test composition, in terms of item difficulty level, reduces estimation error. Most importantly, both true and estimated item parameters were examined to disentangle the effects of latent trait estimation error from item parameter estimation error. Results revealed that non-normal latent trait distributions produced a considerably larger degree of latent trait estimation error than normal data. Estimated item parameters tended to have comparable precision to true item parameters, thus suggesting that increased latent trait estimation error results from latent trait estimation rather than item parameter estimation. (Contains 6 tables, 3 figures, and 1 footnote.)
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