05-08-2015 07:36 AM
I am doing an exploratory factor analysis on multiple dichotomized variables (around 175 odd) for which I have few questions:
Additional comment: I have to iterate (choosing different number of factors to be extracted each time) the factor analysis to find the best model.
1) For some set of independent variables, the correlation matrix was non positive definite, because of which the KMO and sphericity tests were not performed. Is there a workaround to avoid/overcome this?
2) I would like to know on how to identify the best model given say 5 iterations can be found out. Is there a statistic that helps here?
3) Any pointers on which is the best method for extraction and rotation (or is it to be determined by trial and error?)?
Thanks for your comments/suggestions in advance.
05-11-2015 10:34 AM
What are you using to calculate KMO, proc factor?
I think PCA is the most common factor analysis for data miners, but you might be trying to do something beyond variable reduction using KMO. If you really want to do exploratory factor analysis using proc factor or something similar you might get better input from SAS statistical procedures community or SAS procedures support community.
Still, share a code example of what you are using right now and we will give you suggestions on how to iterate through your data.
Just curious, dichotomized variables are nominal variables with 2 levels, right? Is there any reason I cannot treat them as binary variables, or am I completely lost here?
05-15-2015 10:45 AM
Take a look to this article from a professor from UT Dallas.
Definitely worth reading.