As curricular reforms are implemented, there is often urgency among scholars to swiftly evaluate curricular outcomes and establish whether desired impacts have been realized. Consequently, many evaluative studies focus on summative program outcomes without accompanying evaluations of implementation. This runs the risk of Type III errors, whereby…

The articles presented in this Special Issue provide evidence for many statistically significant relationships among error scores obtained from the Kaufman Test of Educational Achievement, Third Edition (KTEA)-3 between various groups of students with and without disabilities. The data reinforce the importance of examiners looking beyond the…

The purpose of this article was to extend the use of standard errors for equated score differences (SEEDs) to traditional equating functions. The SEEDs are described in terms of their original proposal for kernel equating functions and extended so that SEEDs for traditional linear and traditional equipercentile equating functions can be computed.…

Evidence from recent research suggests that in the UK the public perception of errors in national examinations is that they are simply mistakes; events that are preventable. This perception predominates over the more sophisticated technical view that errors arise from many sources and create an inevitable variability in assessment outcomes. The…

Some researchers have argued for the use of or have attempted to make use of randomization tests in single-subject research. To address this tide of interest, the authors of this article describe randomization tests, discuss the theoretical rationale for applying them to single-subject research, and provide an overview of the methodological…

Researchers often compare the relationship between an outcome and covariate for two or more groups by evaluating whether the fitted regression curves differ significantly. When they do, researchers need to determine the "significance region," or the values of the covariate where the curves significantly differ. In analysis of covariance (ANCOVA),…