I am conducting an exploratory factor analysis with categorical variables
VARIABLE: NAMES = v1-v60; CATEGORICAL = v1-v60;
ANALYSIS: TYPE = EFA 1 4
* The output indicates that chi-square value for ....WLSMV cannot be used....
I did some research and what I found indicated to use DIFFTEST....but I saw a post from Linda in 2012 which indicated this does not work with Type = EFA, please help. So, should I not use the Chi-Square results at all, and only focus on others such as RMSR value
I feel my post relates to this thread - hopefully I am on the right track!
My data (questionnaire data) is categorical (ordinal; 5-point Likert scale) and non-normal. After researching the best estimator for such cases, I planned to run an EFA using the WLSMV estimator. Despite this, I realised that the DIFFTEST option is not available using the WLSMV estimator when doing an EFA. After searching the discussion boards, it was suggested that to test the model difference I could run exploratory structural equation modelling in the program.
I have a1-a7 and v1-v8 items, and want to determine if the 1-factor or 2-factor model has better fit (this is preliminary and I have other subscales of a similar fashion). Does this approach sound right, or am I going down the complete wrong track? I know it is not appropriate to use the WLSMV chi-squares for difference testing, hence my line of thinking regarding DIFFTEST. In saying that, I am not sure if my models are nested?
If ESEM is appropriate, are you able to direct me to a resource that details how to run the syntax for this? I have looked at the "Exploratory Structural Equation Modeling" paper (Asparouhov & Muthén) but I getting confused as to how to specify an EFA model within this framework.
I have looked at the ex 4.2 output, which is similar to what I obtained when I ran my EFA. I observed that it has the '1-factor against 2-factor' model comparison under model summary information. Is this the same result I would obtain if I were able to run DIFFTEST with my EFA (using WLSMV)? I think when I initially looked at this model comparison I thought I could not interpret it, given the warning within the same output about the inappropriateness of using the chi-squares values for difference testing when using WLSMV.
If I am able to just use this information (which would be great!), would it still be correct to report the other model fit indices associated with the best model?