Bias-Corrected Fixed Item Parameter Calibration, with an Application to PISA Data
Year: 2025
Type: article
Abstract: Fixed item parameter calibration (FIPC) is commonly used to compare groups or countries using an item response theory model with a common set of fixed item parameters. However, FIPC has been shown to produce biased estimates of group means and standard deviations in the presence of random differential item functioning (DIF). To address this, a bias-corrected variant of FIPC, called BCFIPC, is introduced in this article. BCFIPC eliminated the bias of FIPC with only minor efficiency losses in certain simulation conditions, but substantial precision gains in many others, particularly for estimating group standard deviations. Finally, a comparison of both methods using the PISA 2009 dataset revealed relatively large differences in country means and standard deviations.
Source: Stats
DOI: 10.3390/stats8020029
Author: Alexander Robitzsch
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,930
OpenAlex ID: W4409768684