Hello Walaa,

Unfortunately, there's not enough information in your query for me to give a helpful reply. Others, I suspect, will have the same challenge. Perhaps you could elaborate, by indicating:

1. What are the variables (both manifest/observed and latent) in your model?

2. The R-squared represents variance accounted for in which variable(s)?

What I can tell you is, in some instances, a model that accounts for 91% of variance might be considered extraordinarily good, while in others, that might be considered poor.

Good luck with your work!

dear Walaa Sarayrah The R-squared (R2) value ranges from 0 to 1 with 1 defining perfect predictive accuracy. Since R2 value is adopted in various research disciplines, there is no standard guideline to determine the level of predictive acceptance. Henseler (2009) proposed a rule of thumb for acceptable R2 with 0.75, 0.50, and 0.25 are described as substantial, moderate and weak respectively.

https://people.duke.edu/~rnau/rsquared.htm

https://blog.minitab.com/blog/adventures-in-statistics-2/how-high-should-r-squared-be-in-regression-analysis

Walaa, as David Morse already pointed out, we definitely need more information concerning your model and your variables in order to provide valuable help.

Kind regards, Karin

Dears Karin Schermelleh-Engel David Morse

I appreciate your answers, I attached the model I am working on. thanks in advance.

Dear Mohammed Habes , I read the links in your comment and the information was very insightful, thank you

Dear Walaa, I am not sure what the numbers in the circles representing factors mean. I guess they are some sort of factor reliability?

Could you also provide the unexplained variance of the factor satisfaction? It seems to be obvious that .91 is not the variance explained by the four predictor variables.

Kind regards, Karin

Walaa, now I got it. The numbers in the circles denote composite reliability.

To answer your question: Yes, these values are plausible because the factor loadings are all very large.

If you are interested in the variance of satisfaction explained by the predictor variables, this value should be provided in the output.

HTH, Karin