ruben milla posted on Wednesday, March 26, 2008 - 10:53 am
Dear all, i am running a SEM analysis which includes 1 latent continuous variable and 12 dependent variables (3 of them categorical). I am using MLR as estimator.
When i run the script, i obtain parameter estimates, with their corresponding estandar errors. But i dont get chi-square, CFI or TLI to be able to assess overall model fit. I only get loglikelihood and information criteria values as output under the "tests of model fit" subheading. I am not comparing alternative models, but just trying to assess the overall fit of my data to 1 model.
You will not obtain these fit statistics because numerical integration is required for your analysis. You could use the default estimator WLSMV.
ruben milla posted on Thursday, March 27, 2008 - 4:44 am
thanks a lot, but we have a modest sample size (190), and, as i understand, WLS-related estimators require larger sample sizes than ML (is this correct?). Thus, i run my model using WLSMV, and get the "NO CONVERGENCE. NUMBER OF ITERATIONS EXCEEDED." output. Also, i need an estimator robust to multivariate non-normality any alternative suggestion? would simplification of the model increase the likelihood of it to converge using WLSMV?
I'm using MLR to run a mediation model with a continuos IV, one categorical and one continuous mediator and a continuous outcome. Since Mplus does not provide the standard GOF indices, due the use of numerical integration, I was wondering how would you go about reporting overall model fit. I've been asked to report on that, but I'm not really sure how to proceed or whether that is absolutely necesary. (I'm using MLR because of non-normality issues)