Dear all,
I am trying to apply SEM (for the first time) to my graduate research, and I have been learning about SEM and lavaan from online resources and examples, but when it comes to my own research, I am having some difficulties that I am not sure how to solve.
fit2
First, check what the warning has, does data.cor1 have an inverse. Try
solve(data.cor1)
First, check what the warning has, does data.cor1 have an inverse. Try
solve(data.cor1)
btw, a lot of warnings are something to take note of, but the resulting output may be alright (or they can be "fixed" doing things like allowing more time for convergence). If the covariance matrix has no inverse it means something more likely needs to be done. Some potential causes relate to how missing values are estimated, how the observed variables are associated (e.g., one is a weighted average of others), etc.
Thank you Daniel. Yes when I run the model and analyses the output statistical data found that:
x2 = 0.00
dF= 5
p=0.001
CFI & TLI = 1.0
RMSEA = 0.00
SRMR= 0.06
R2 = 1.0, 0.99, 0.98
one more thing, the output path analysis diagram is also perfect but, some of the variables are also correlated with each other due to inner software input. Is it the model of path analysis correct or wrong..?
Please help.
Thanks.
Dear Sanjay
The person that could help you with the particular difficulties in the SEM analysis in R is Josu González Alday. He carried out those analyses in our last paper, thus he know how to do them.
The Josu e-mail is: [email protected]
Please contact with him from me
I hope he can help you
Regards
Carolina
Dear Dr. Carolina Martínez Ruiz, thank you for your support and suggestion. I will definitely contact, Dr. Josu González Alday regarding my problem related with SEM analysis using lavaan in Rstudio.
Regards
Sanjay.
Sanjay, those statistics look like there may be some computational problems. Did you check to see if the covariance matrix has an inverse? Even if it does, what does the covariance matrix look like and did anything come up when you were doing your exploratory data analysis.
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