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 Eric Klopp posted on Sunday, November 02, 2008 - 1:20 pm
Hello, I did a CFA using a 7-factor model with correlated latent variables. Every one of the observed variables is specified to load on one latent variable and mesurement errors of the observed variables where set to be uncorrelated. Scaling of the latent variable was done setting the regression weight of an observed variable to one. Before testing the entire model with 7 factors every single factor has undergone a CFA with good model fit and was cross-validated. After that, the factors we put together to the above mentioned 7-factor model

Now, I have a problem with the results of the 7-factor model. Altough my chi^2 is significant (chi^2=767,149 df=474, p<0,001, N=291) the chi^2/df ratio, SRMR and RMSEA showed good to acceptable model fit (chi^2/df=1,618, SRMR=0,0680, RMSEA=0,046, CI(RMSEA)=[0,040;0,052]).

But the CFI is rather low (CFI=0,834). How can this result be explained?

Many thanks, Eric
 Linda K. Muthen posted on Monday, November 03, 2008 - 8:02 am
When you put the factors together, there may be a need for cross-loadings that impair the fit of the model. I would start with an EFA of all of the items to see if this might be the case.
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