# How to interpret the fit of cfa (sem) outcome?

I did some CFA analyses (using R package Lavaan) on several scales in order to check the unidimensionalities. If I understood well scale 5, 6 and 7 can be considered a good fit because of the RMSEA < 0.08 and the CFI and TLI > 0.90. My question is how to interpret the fit of the first 4 scales. The RMSEA looks good, but the CFI and TLI don't. Am I allowed to say something like "almost a good fit"?

Scale   N       R2      χ2          df  SRMR    RMSEA   RMSEA con.interv.   CFI     TLI
1       1673    0.18    1470.71***  434 0.038   0.038   0.036   -   0.040   0.85    0.83
2       1672    0.19    597.81***   152 0.04    0.042   0.038   -   0.045   0.87    0.85
3       1675    0.16    586.93***   170 0.038   0.038   0.035   -   0.042   0.84    0.82
4       1677    0.25    427.43***   90  0.04    0.047   0.043   -   0.052   0.91    0.89
5       1677    0.24    280.65***   90  0.031   0.036   0.031   -   0.040   0.93    0.92
6       1670    0.26    175.35      54  0.03    0.037   0.031   -   0.043   0.95    0.93
7       1679    0.25    289.79***   104 0.03    0.033   0.028   -   0.037   0.95    0.94

• Well, I suppose the scale number six is the only one that you can consider as having good-fit considering Kline's standard (a non-significant chi-sqr). In general I tend to use the other indices to compare fit btw different models. You can say that scale 7 has a slightly better fit than the scale 4. You can also run a comparative anova in R to check whether this difference is statistically significant. – lf_araujo Jan 6 '16 at 5:26