According to PISA 2012, mathematics self-beliefs involve three dimensions: mathematics self-efficacy, mathematics self-concept and mathematics anxiety. This study utilized the multiple indicators, multiple causes (MIMIC) method, an approach for detecting whether there is a lack of measurement invariance or differential item functioning (DIF), to deal with multiple covariates, multiple dimensions, and ordered categorical variables with threshold structures to study DIF among mathematics self-beliefs items across Shanghai-China (N = 5177) and the USA (N = 4978) from Program for International Student Assessment (PISA) 2012. The MIMIC approach with mediators was also applied in the study, which helped to detect variables that could account for meaningful partial or complete DIF effects. Confirmatory factor analysis (CFA), a statistic method that can verify the number of latent traits of the dataset, indicated that the three-factor structure worked for the data. Both robust weighted least square (WLSMV) estimator and robust maximum likelihood (MLR) estimator were used in the parameter estimation to identify items with DIF and quantify the DIF effect size. It was found in the study with MIMIC method that in-school mathematics class periods and out-of-school study hours in PISA 2012 had partial effects on most items with meaningful DIF effects.