In this paper, the "standard error of equating difference" (SEED) is described in terms of originally proposed kernel equating functions (von Davier, Holland, & Thayer, 2004) and extended to incorporate traditional linear and equipercentile functions. These derivations expand on prior developments of SEEDs and standard errors of equating and…

In the equating literature, a recurring concern is that equating functions that utilize a single anchor to account for examinee groups' nonequivalence are biased when the groups are extremely different and/or when the anchor only weakly measures what the tests measure. Several proposals have been made to address this equating bias by incorporating…

This study compared the accuracies of four differential item functioning (DIF) estimation methods, where each method makes use of only one of the following: raw data, logistic regression, loglinear models, or kernel smoothing. The major focus was on the estimation strategies' potential for estimating score-level, conditional DIF. A secondary focus…

The robustness and power of 9 strategies for testing the differences in groups' regression slopes were assessed under nonnormality and residual variance heterogeneity. For the conditions considered, the most robust strategies were the trimmed and Winsorized slope estimates used with the James second-order test, the Theil-Sen slope estimates used…