Alternatives to Weighted Item Fit Statistics for Establishing Measurement Invariance in Many Groups

Sean Joo, Montserrat Valdivia, Dubravka Svetina Valdivia and Leslie Rutkowski
Additional contact information
Sean Joo: University of Kansas
Leslie Rutkowski: Indiana University Bloomington

Journal of Educational and Behavioral Statistics, 2024, vol. 49, issue 3, 465-493

Abstract: Evaluating scale comparability in international large-scale assessments depends on measurement invariance (MI). The root mean square deviation (RMSD) is a standard method for establishing MI in several programs, such as the Programme for International Student Assessment and the Programme for the International Assessment of Adult Competencies. Previous research showed that the RMSD was unable to detect departures from MI when the latent trait distribution was far from item difficulty. In this study, we developed three alternative approaches to the original RMSD: equal, item information, and b -norm weighted RMSDs. Specifically, we considered the item-centered normalized weight distributions to compute the item characteristic curve difference in the RMSD procedure more efficiently. We further compared all methods’ performance via a simulation study and the item information and b -norm weighted RMSDs showed the most promising results. An empirical example is demonstrated, and implications for researchers are discussed.

Keywords: measurement invariance; differential item functioning; root mean square deviation; international large-scale assessments; PISA; PIAAC (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/10769986231183326 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:49:y:2024:i:3:p:465-493

DOI: 10.3102/10769986231183326

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().