A Regression Discontinuity Design Framework for Controlling Selection Bias in Evaluations of Differential Item Functioning.

ABSTRACT: Differential item functioning (DIF) is often used to examine validity evidence of alternate form test accommodations. Unfortunately, traditional approaches for evaluating DIF are prone to selection bias. This article proposes a novel DIF framework that capitalizes on regression discontinuity design analysis to control for selection bias. A simulation study was performed to compare the new framework with traditional logistic regression, with respect to Type I error and power rates of the uniform DIF test statistics and bias and root mean square error of the corresponding effect size estimators. The new framework better controlled the Type I error rate and demonstrated minimal bias but suffered from low power and lack of precision. Implications for practice are discussed.

SUBMITTER: Koziol NA 

PROVIDER: S-EPMC9619321 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature