Application of unidimensional item response theory models to mutidimensional data

Loading...
Thumbnail Image

View/Download File

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Application of unidimensional item response theory models to mutidimensional data

Published Date

1983

Publisher

Type

Article

Abstract

A simulation model was developed for generating item responses from a multidimensional latent trait space The model permits the prepotency of a general latent trait underlying responses to all simulated items to be varied systematically. Five levels of prepotency were used to generate data sets The levels of prepotency ranged from a truly unidimensional latent trait space to a very weak general latent trait. Simulated item pools with guessing and without guessing were analyzed by the LOGIST computer program The general latent trait was recovered in data sets where the prepotency of the general latent trait was only moderate. Consequently, it appears that item response theory models can be applied to moderately heterogenous item pools under the conditions simulated here.

Keywords

Description

Related to

Replaces

License

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Drasgow, Fritz & Parsons, Charles K. (1983). Application of unidimensional item response theory models to mutidimensional data. Applied Psychological Measurement, 7, 189-199. doi:10.1177/014662168300700207

Suggested citation

Drasgow, Fritz; Parsons, Charles K.. (1983). Application of unidimensional item response theory models to mutidimensional data. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/101643.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.