User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.970 0.552
Tucker-Lewis Index (TLI) 0.965 0.915
User Model versus Baseline Model:
Comparative Fit Index (CFI) 0.970 0.819
Tucker-Lewis Index (TLI) 0.965 0.789
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According to what I know, I should be using estimator = "WLSMV" and test = "mean.var.adjusted" due to the fact that my data is categorical (e.g., Finney and DiStefano, 2006).
I noticed the following "bug" reported in Version 0.5-21, so it may be related to that:"Bugs/glitches discovered after the release:
- the (new) robust CFI/TLI/RMSEA values as printed in the summary() output of version 0.5-21 (only) are wrong if (and only if) the test statistic is “mean.var.adjusted” or “scaled.shifted” (the latter is used when estimator = “WLSMV”, the default estimator in the categorical case)"