NotesFAQContact Us
Collection
Advanced
Search Tips
ERIC Number: ED264268
Record Type: Non-Journal
Publication Date: 1982-Jul
Pages: 16
Abstractor: N/A
Reference Count: N/A
ISBN: N/A
ISSN: N/A
Application of Unidimensional Item Response Theory Models to Multidimensional Data.
Drasgow, Fritz; Parsons, Charles K.
The effects of a multidimensional latent trait space on estimation of item and person parameters by the computer program LOGIST are examined. Several item pools were simulated that ranged from truly unidimensional to an inconsequential general latent trait. Item pools with intermediate levels of prepotency of the general latent trait were also constructed. These item pools were used to determine the degree of prepotency that is required by LOGIST in order to recover the general latent trait and not be drawn to a latent trait underlying a cluster of items. The types of multidimensionality studied have several effects on the estimation techniques programmed in LOGIST. Perhaps most important is that as the prepotency of the general factor decreases, LOGIST is gradually drawn to the strongest group factor. Estimates of item difficulty occasionally become excessively large in magnitude when actual data sets are analyzed by LOGIST, although the most recent version has options that may reduce this problem. The results obtained here indicate that this phenomenon may partially be due to multidimensional item pools. However, unidimensional models do provide a good description of multidimensional data sets when the dominant latent trait is sufficiently prepotent. (PN)
Publication Type: Reports - Research; Speeches/Meeting Papers
Education Level: N/A
Audience: Researchers
Language: English
Sponsor: N/A
Authoring Institution: N/A