Nonparametric or kernel regression estimation of item response curves (IRCs) is often used in item analysis in testing programs. These estimates are biased when the observed scores are used as the regressor because the observed scores are contaminated by measurement error. Accuracy of this estimation is a concern theoretically and operationally.…

In educational tests, subscores are often generated from a portion of the items in a larger test. Guidelines based on mean squared error are proposed to indicate whether subscores are worth reporting. Alternatives considered are direct reports of subscores, estimates of subscores based on total score, combined estimates based on subscores and…

This paper is the first of a series that will compare estimates of error that arises when state assessments are linked to the National Assessment of Educational Progress (NAEP). Different forms of linkage are discussed. Comparisons are made between whole-sample regression, repeated half-sample replication, bootstrap, and jackknife estimates of the…