Improving 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 â€“ the first with continuous the second with ordered indicators - will be used to provide a walk-through the individual steps. Accessed 20,554 times on https://pareonline.net from July 09, 2014 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.
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Hirschfeld, Gerrit and von Brachel, Ruth
"Improving Multiple-Group confirmatory factor analysis in R – A tutorial in measurement invariance with continuous and ordinal indicators,"
Practical Assessment, Research, and Evaluation: Vol. 19, Article 7.
Available at: https://scholarworks.umass.edu/pare/vol19/iss1/7