RMSEA too high? Problems with this fit index. скачать в хорошем качестве

RMSEA too high? Problems with this fit index.

Together with CFI and SRMR, the RMSEA is one of the most popular fit indices for path analysis, CFA (confirmatory factor analysis) and SEM (structural equation modelling). Check out my STATISTICS CONSULTING services here: https://www.regorz-statistik.de/en/co... Unfortunately, the RMSEA can give seriously misleading answers to the question whether a model has an adequate fit in models with small df. Primarily, this is a problem for path analyses and simple CFA models where a small number of degrees of freedom is quite common. In that case you can get a RMSEA over 0.1 even for a correct model. A combination of high RMSEA and low SRMR is then also possible. This video explains the problem with the RMSEA in models with small df and shows possible solutions. To my other tutorials: https://www.regorz-statistik.de/en/tu... Based on: Kenny, D. A., Kaniskan, B., & McCoach, D. B. (2015). The performance of RMSEA in models with small degrees of freedom. Sociological methods & research, 44(3), 486-507. https://doi.org/10.1177/0049124114543236