A large-scale empirical investigation of measurement invariance decisions under multiple-group item response theory and multiple-group confirmatory factor analysis

Measurement invariance (MI) testing is essential for ensuring valid cross-group comparisons in international large-scale assessments (ILSA). There are two major frameworks for establishing MI: multiple-group confirmatory factor analysis (MGCFA) and multiple-group item response theory (MGIRT). This study compares the results of MGCFA and MGIRT in examining measurement invariance using survey data from the International Computer and Information Literacy Study (ICILS) 2023. This study goes beyond p