I've fitted a one-factor model to data originating from a unidimensional 8-item scale; sample size is 400. Because the scale uses a Likert response format, and data does not follow a multivariate normal distribution, I have used DWLS. I have gotten non-significant results for Chi-squared, and therefore extremely good values for the rest of the fit indexes I have calculated. Since this is the first time I am seeing these type of results, I wonder: is it possible? Am I missing something? Should I instead use robust estimation methods (WLSMV)?
lavaan 0.6-5 ended normally after 29 iterations Estimator DWLS Optimization method NLMINB Number of free parameters 16 Number of observations 400 Model Test User Model: Test statistic 16.916 Degrees of freedom 20 P-value (Chi-square) 0.658 Model Test Baseline Model: Test statistic 4000.700 Degrees of freedom 28 P-value 0.000 User Model versus Baseline Model: Comparative Fit Index (CFI) 1.000 Tucker-Lewis Index (TLI) 1.001