Information-Weighted and Normal Density-Weighted Haebara Linking

Linking methods based on item response theory aim to place item parameters from different groups, test forms, or test administrations onto a common scale. Information-weighted Haebara linking has been proposed as an alternative to the widely used standard Haebara linking method. This study compares its performance against Haebara linking with weights based on the normal distribution. Simulations using the two-parameter logistic model indicate that while information-weighted Haebara linking outperforms the uniformly weighted variant, it does not surpass normal density-weighted Haebara linking in terms of bias and root mean square error. The results suggest that normal density weights should be preferred over both uniform and information-based approaches. Additionally, standard errors were derived for both methods, yielding satisfactory coverage rates.

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Information
Published
2025-03-28
DOI
https://doi.org/10.3390/info16040273
Citations
1
Primary Topic
Anomaly Detection Techniques and Applications
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article
Field-Weighted Citation Impact
2.48
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article

Information-Weighted and Normal Density-Weighted Haebara Linking

Alexander Robitzsch
1 citations
Information
Anomaly Detection Techniques and Applications
2.48
article

Information-Weighted and Normal Density-Weighted Haebara Linking

Alexander Robitzsch
article en
1 citations

Abstract

Linking methods based on item response theory aim to place item parameters from different groups, test forms, or test administrations onto a common scale. Information-weighted Haebara linking has been proposed as an alternative to the widely used standard Haebara linking method. This study compares its performance against Haebara linking with weights based on the normal distribution. Simulations using the two-parameter logistic model indicate that while information-weighted Haebara linking outperforms the uniformly weighted variant, it does not surpass normal density-weighted Haebara linking in terms of bias and root mean square error. The results suggest that normal density weights should be preferred over both uniform and information-based approaches. Additionally, standard errors were derived for both methods, yielding satisfactory coverage rates.

InformationVol. 16(4)
Leibniz Institute for Science and Mathematics Education (DE)
Openalex Percentile: Top 11%
Anomaly Detection Techniques and Applications
2.48
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Information-Weighted and Normal Density-Weighted Haebara Linking — Alexander Robitzsch · Information (2025) | TGRS Research Map | TGRS