Angel Arias posted on Tuesday, January 29, 2019 - 10:44 am
Asparouhov and Muthén (2018, p.3) stated that "to establish approximate fit [one] should include an inspection of the Mplus residual output to verify that the residuals are many small values and there are no large residual values at all". My question is what can we consider a large residual value? Are there any guidelines for this? what do you recommend?
Anything above 0.3 by absolute value on a correlation metric should be considered substantial/non - ignorable. Apart from that it is somewhat subjective but values below 0.1 are commonly accepted as ignorable. Values between 0.1 and 0.3 could be considered important if substantive meaning can be found. Alternatively, record all absolute value residuals and plot them. Values that look like outliers mean + 3*st dev (from the residual distribution) if above 0.2 should be considered important and possibly included in the model. Approximate fit is somewhat subjective - the above looks reasonable to me.
Angel Arias posted on Tuesday, January 29, 2019 - 3:15 pm
Thanks for the prompt and detailed response, cheers!