Modeling effects of negatively worded items with bifactor item response theory models

Kuan Yu JIN, Wen Chung WANG

Research output: Contribution to conferencePapers

Abstract

This paper adopted the bifactor item response theory (IRT) approach to account for the wording effect in mixed-format scales, in which a general factor represents the latent construct that the test was designed to measure, and a nuisance factor indicates the wording effect. Two empirical examples from the PISA and the TIMSS were analyzed to compare the performance of the proposed approach and a standard IRT approach using WinBUGS. Results indicated moderate to large wording effects from NW items, and ignoring the wording effect not only resulted in overestimated test reliability but also dramatically changed person rankings.
Original languageEnglish
Publication statusPublished - Apr 2014

Citation

Jin, K.-Y., & Wang, W.-C. (2014, April). Modeling effects of negatively worded items with bifactor item response theory models. Paper presented at the 2014 AERA Annual Meeting, Philadelphia, Pennsylvania.

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