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.