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To ensure test fairness and validity, it is crucial for test practitioners to assess differential item functioning (DIF) simultaneously for all grouping variables to avoid omitted variable bias (OVB) (Chao et al., 2018). In testing practice, however, we often face challenges due to insufficient information, such as the absence of DIF-free anchor items, while conducting DIF assessment. To address this issue, this study proposed the parallel DIF-free-then-DIF (p-DFTD) strategy, which selects DIF-free items simultaneously for each grouping variable and utilizes them as anchors for DIF assessment. According to the simulation study, the results revealed that the p-DFTD strategy successfully identified DIF-free anchor items and effectively controlled Type I errors while maintaining satisfactory statistical power in most conditions.