A simulation study was conducted to explore the impact of differential item functioning (DIF) on general factor difference estimation for bifactor, ordinal data. Common analysis misspecifications in which the generated bifactor data with DIF were fitted using models with equality constraints on noninvariant item parameters were compared under data generation conditions varying by sample size, number of response categories, effect size of the general factor mean difference, and the position and the magnitude of DIF. Estimation bias in the general factor mean difference resulting from ignoring DIF mainly depended on the type of parameters with DIF. When ignoring DIF in threshold parameters, very substantial estimation bias was produced, and Type I error rates (powers) were inflated for many conditions. In contrast, when ignoring DIF in general factor loadings, a little estimation bias was produced; when ignoring DIF in specific factor loadings, almost no estimation bias was produced. All Type I error rates fell within required limits when DIF was present in factor loadings, and powers were not influenced by ignoring DIF in factor loadings.