Because assessment methods for differential item functioning (DIF) have been developed and thoroughly investigated, the focus in DIF research has shifted to explaining DIF phenomena. Experts in this field are recruited to tap possible sources of DIF. Quantitative analysis results help experts reviewing DIF to locate sources for DIF items. This study aimed to demonstrate the use of the differential facet functioning (DFF) procedure implemented using the linear logistic test model (LLTM) and random effects linear logistic test model (LLTM-R) to explain possible DIF sources. The efficiency of LLTM and LLTM-R in detecting DFF under various conditions was also evaluated. The simulation results indicated that the DIF effect was significantly influenced by the DFF effect of item properties. Moreover, as the design matrices had a high density (e.g., 60%), Type-I error rates of DIF assessment were seriously inflated. We also demonstrated the procedure of DFF analysis with an empirical data. The result showed that most DIF items were related to two item properties, which would be provided as possible DIF sources in the item-review meeting. Researchers should implement DFF assessment using LLTM-R to help explain DIF sources.