I am having some trouble with posting due to the spam filter being continuously triggered so I also provided an attachment for the R code in addition to the data set.
I have two different questions.
My questions revolve around multiple group factor analysis (3 groups). There are a lot more groups but for the sake of the questions and computation speed, I provided the code for three groups.
Thank you for your suggestions and comments.
1. Fixing of model parameters: I fixed all the parameters in a one factor model. The code works for one group (model1) but when three groups are put into one entire run of code (mgroups), I get the warning: "Error: The job for model 'new' exited abnormally with the error message: Objective function returned a value of NaN at iteration 0.1." How could I circumvent this issue to let the code work for the three groups in one run?
2. Total of BIC from one entire code run unequal with the sum of BIC from individual models
I would like to compute the information criteria using three groups in one whole code. I specified the code for three groups in one run (newmodel) and the code for three separate groups (m1,m2,m3). I further specified the code below to compute the information criteria. The thing is, the sum of the AIC's from three separate model is exactly equal with the AIC computed from one entire code run (newmodel) but it is not the case for the BIC's. They do not correspond at all. Is the BIC computed differently when multiple groups are specified in one code or is it just ordinary to find that the sum of the BIC's from separate groups does not equal the BIC when the three groups are combined in one code?