Nonparametric, or kernel, estimation of item response curve (IRC) is a concern theoretically and operationally. Accuracy of this estimation, often used in item analysis in testing programs, is biased when the observed scores are used as the regressor because the observed scores are contaminated by measurement error. In this study, we investigate…

One of the major objectives of large-scale educational surveys is reporting trends in academic achievement. For this purpose, a substantial number of items are carried from one assessment cycle to the next. The linking process that places academic abilities measured in different assessments on a common scale is usually based on a concurrent…

Item parameter estimates vary for a variety of reasons, including estimation error, characteristics of the examinee samples, and context effects (e.g., item location effects, section location effects, etc.). Although we expect variation based on theory, there is reason to believe that observed variation in item parameter estimates exceeds what…