Enhancing Precision in Predicting Magnitude of Differential Item Functioning: An M-DIF Pretrained Model Approach.

ABSTRACT: Despite numerous studies on the magnitude of differential item functioning (DIF), different DIF detection methods often define effect sizes inconsistently and fail to adequately account for testing conditions. To address these limitations, this study introduces the unified M-DIF model, which defines the magnitude of DIF as the difference in item difficulty parameters between reference and focal groups. The M-DIF model can incorporate various DIF detection methods and test conditions to form a quantitative model. The pretrained approach was employed to leverage a sufficiently representative large sample as the training set and ensure the model's generalizability. Once the pretrained model is constructed, it can be directly applied to new data. Specifically, a training dataset comprising 144

SUBMITTER: Huang S 

PROVIDER: S-EPMC11562883 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature