A Monte Carlo Confidence Interval Method for Testing Measurement Invariance

We propose a new method, the Monte Carlo confidence interval (MCCI) method, for studying measurement invariance. This method allows researchers to examine the invariance of all items simultaneously by comparing the observed between-group differences in parameters with those obtained under the null hypothesis of invariance. We compare the performance of our method to two other methods: the multigroup confirmatory factor analysis (MG-CFA) and the forward method using confidence intervals (forward CI). The results show that our method performed better than the MG-CFA method and comparably with the forward CI method. The code to implement our method and an empirical example are provided in the Supplementary materials.