Between Dec 19, 2024 and Jan 2, 2025, datasets can be submitted to DRUM but will not be processed until after the break. Staff will not be available to answer email during this period, and will not be able to provide DOIs until after Jan 2. If you are in need of a DOI during this period, consider Dryad or OpenICPSR. Submission responses to the UDC may also be delayed during this time.
 

A method for investigating the intersection of item response functions in Mokken's nonparametric IRT model

Loading...
Thumbnail Image

View/Download File

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

A method for investigating the intersection of item response functions in Mokken's nonparametric IRT model

Published Date

1992

Publisher

Type

Article

Abstract

For a set of k items having nonintersecting item response functions (IRFs), the H coefficient (Loevinger, 1948; Mokken, 1971) applied to a transposed persons by items binary matrix Hт has a non-negative value. Based on this result, a method is proposed for using Hт to investigate whether a set of IRFs intersect. Results from a monte carlo study support the proposed use of Hт. These results support the use of Hт as an extension to Mokken’s nonparametric item response theory approach. Index terms: double monotonicity, Hт coefficient, intersection of item response functions, item response theory, Mokken models, nonparametric models.

Keywords

Description

Related to

Replaces

License

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Sijtsma, Klaas & Meijer, Rob R. (1992). A method for investigating the intersection of item response functions in Mokken's nonparametric IRT model. Applied Psychological Measurement, 16, 149-157. doi:10.1177/014662169201600204

Other identifiers

doi:10.1177/014662169201600204

Suggested citation

Sijtsma, Klaas; Meijer, Rob R.. (1992). A method for investigating the intersection of item response functions in Mokken's nonparametric IRT model. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/115642.

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.