Full-information factor analysis for polytomous item responses

Loading...
Thumbnail Image

View/Download File

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Full-information factor analysis for polytomous item responses

Published Date

1995

Publisher

Type

Article

Abstract

A full-information item factor analysis model for multidimensional polytomously scored item response data is developed as an extension of previous work by several authors. The model is expressed both in factor-analytic and item response theory parameters. Reckase’s multidimensional parameters for the model also are discussed as well as the related geometry. An EM algorithm for estimation of the model parameters is presented and results of the analysis of item response data by a computer program incorporating this algorithm are presented. Index terms: EM algorithm, full-information item factor analysis, multidimensional item response theory, polytomous response data.

Keywords

Description

Related to

Replaces

License

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Muraki, Eiji & Carlson, James E. (1995). Full-information factor analysis for polytomous item responses. Applied Psychological Measurement, 19, 73-90. doi:10.1177/014662169501900109

Other identifiers

doi:10.1177/014662169501900109

Suggested citation

Muraki, Eiji; Carlson, James E.. (1995). Full-information factor analysis for polytomous item responses. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/117440.

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.