I am university student trying to understand the interpretation of SEM. Specifically, I'd like to understand how the study of Seo & Park (2018) applied SEM in their study. The link of the study is this: Article A study on the effects of social media marketing activities ...
This is the part I'm having trouble understanding:
χ^2 = 576.887, df = 219, CMIN/DF = 2.634, p < 0.001, GFI = 0.855, AGFI = 0.817, RMR = 0.085, CFI = 0.918, TLI = 0.906, and RMSEA = 0.074
What is χ^2, df, CMIN/DF, p, GFI, AGFI, RMR, CFI, TLI, and RMSEA?
I'd appreciate any help.
Hello Ram,
Timo Mandler 's response is on target. I would just add that measures of model-data fit address the general question: How well do the estimated model indices/parameters allow one to reproduce the observed relationships (e.g., correlations or covariances) among the measured variables in the data set? Closer is better!
David Kenny's web page is also a quick overview of most of the fit indices used in SEM applications: http://davidakenny.net/cm/fit.htm
Good luck with your work.
Dear Timo Mandler ,
Thank you for providing me these references. It has certainly cleared up a lot of my confusion on SEM since I am still new to this.
Best regards,
Ram
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