Multiple-Group confirmatory factor analysis in R -- A tutorial in measurement invariance with continuous and ordinal indicators

Multiple-group confirmatory factor analysis (MG-CFA) is among the most productive extensions of structural equation modeling. Many researchers conducting cross-cultural or longitudinal studies are interested in testing for measurement and structural invariance. The aim of the present paper is to provide a tutorial in MG-CFA using the freely available R-packages lavaan, semTools, and semPlot. The combination of these packages enable a highly efficient analysis of the measurement models both for normally distributed as well as ordinal data. Data from two freely available datasets -- the first with continuous the second with ordered indicators - will be used to provide a walk-through the individual steps.