anon9210 posted on Saturday, September 11, 2010 - 7:38 am
Hi, I am running EFAs and CFAs on some nominal survey data and have a couple of questions about that:
1.) I have specified TYPE=COMPLEX in my analyses, and have specified clustering, stratification and weight variables. Based on the output, MPlus does seem to be taking these into account - the output lists these under "VARIABLES WITH SPECIAL FUNCTIONS". However, despite this, the output seems to be printing out only the "unweighted" N. For example, the unweighted N of my sample is 3197, and the weighted N is approximately 2980. However, I see only 3197 in the output. Is this because Mplus is scaling the weights in some way?
2.) While I get RMSEA, WRMR, CFI and TLI, as part of my output, I don't get AIC and BIC for the CFAs that I have been running. Do I need to add some special command for these?
2. AIC and BIC are based on the loglikelihood. Weighted least squares does not use a loglikelihood.
anon9210 posted on Saturday, September 11, 2010 - 4:24 pm
Could I calculate AIC/BIC using the model chi square instead? I have seen it reported in some other articles. Here's an example where the author did use WLS, but has reported AIC and BIC. I am assuming he used the chi-square value for doing so...? See table 2 in the following article - http://archpsyc.ama-assn.org/cgi/content/full/56/10/921
I don't know of any methods investigation regarding computing BIC from chi-square with weighted least squares regression.
Corey Savage posted on Saturday, January 30, 2016 - 11:35 am
If I have AIC and BIC values in the tens of thousands (e.g. 64,659) what would be an appropriate amount to differentiate between values? Both indices continue to decrease through the 8 class model. The decrease, however, is only about 80-100 units once comparing the 6 vs 7 for example.
I have not yet found where the BIC begins to decrease. I am using a number of Rasch scales and count variables as indiciators, some of which have a fair amount of skewness and some are multi-modal.