Anchor Detection Strategy in Moderated Non-Linear Factor Analysis for Differential Item Functioning (DIF).

ABSTRACT: Ensuring measurement invariance is crucial for fair psychological and educational assessments, particularly in detecting Differential Item Functioning (DIF). Moderated Non-linear Factor Analysis (MNLFA) provides a flexible framework for detecting DIF by modeling item parameters as functions of observed covariates. However, a significant challenge in MNLFA-based DIF detection is anchor item selection, as improperly chosen anchors can bias results. This study proposes a refined constrained-baseline anchor detection approach utilizing information criteria (IC) for model selection. The proposed three-step procedure sequentially identifies potential DIF items through the Bayesian Information Criterion (BIC) and Weighted Information Criterion (WIC), followed by DIF-free anchor items using the Ak

SUBMITTER: Lee S 

PROVIDER: S-EPMC12643905 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature