Evaluating Person Fit for Cognitive Diagnostic Assessment

Abstract

Methods evaluating person fit for cognitive diagnostic assessment are an important area of research because failing to detect misfitting responses can lead to the misinterpretation of students’ attribute profiles, which may result in faulty remediation decisions. This article aims to examine ways of detecting person misfit for cognitive diagnostic assessments. The authors first investigated whether the well-known lz statistic, developed under the framework of item response theory, can be extended for use in the context of cognitive diagnostic models. The authors also introduce a new person fit statistic, response conformity index (RCI), developed for detecting misfitting response patterns for cognitive diagnostic assessments. The authors conduct both simulation and real data studies to compare the detection rates of lz and our new statistic.