minyuedong posted on Wednesday, December 07, 2005 - 2:14 am
I am doing a two-level SEM by using MLR estimator. For the chi-square difference anlysis, I refer to the 4-steps suggested by Bentler as shown in the web. I got higher DFs (+7) and higher adjusted chi-square values (+29.04)when compare model 2 (with restrictions) to model 1, so my question is: in order to check if the chi-square difference is significant, shall I refer to the chi-square distribution or something else?
I have carried out a series of SEM analyses with one dependent variable (latent) and a number of predictors (a combination of latent variables and observed). I am using the complex and cluster options. The output provides the MLR estimator.
Can I use the Satorra-Bentler 4-step procedure (steps 3 and 4) for testing differences between models in this case?
I use the "model constraint" option and compare models by constraining parameters (one by one) to be equal to zero, comparing with the unconstrained model. Does this sound right?
I have read carefully all the dialogues on the Satorra-Bentler test for differences between nested models. There is however, one point that is still unclear to me.
The T0 and T1 values that I use when I apply the formula, are these the chi-square values that I obtain when running the analysis with the MLR estimiation procedure, or do I have to multiply the chi square values with their respective scaling correction factors first?
I ran a Chi-Square Difference Testing Using the Loglikelihood on two models, one where the residual variances for my latent growth model was set as invariant (nested model) and one where they are set at varying (comparison model).