This exploratory study investigated potential sources of setting accommodation resulting in differential item functioning (DIF) on math and reading assessments for examinees with varied learning characteristics. The examinees were those who participated in large-scale assessments and were tested in either standardized or accommodated testing conditions. The data were examined using multilevel measurement modeling, latent class analyses (LCA), and log-linear and odds ratio analyses. The results indicate that LCA models yielded substantially better fits to the observed data when they included only one covariate (total scores) than others with multiple covariates. Consistent patterns emerged from the results also show that the observed math and reading DIF can be explained by examinees' latent abilities, accommodation status, and characteristics (including gender, home language, and learning attitudes). The present study not only confirmed previous findings that examinees' characteristics are helpful in identifying sources of DIF but also addressed some limitations of previous studies by using an alternative and viable covariate strategy for LCA models.