Dallas posted on Wednesday, June 29, 2011 - 7:05 am
I have a model with 10 categorical (binary) items. I'd like to run the model allowing local dependence between two of the items. I'm using ML estimation. So, I get the following message "Variances for categorical outcomes can only be specified using PARAMETERIZATION=THETA with estimators WLS, WLSM, or WLSMV."
How can I go about specifying correlated errors in Mplus using ML estimation?
The Theta parameterization is for weighted least squares analysis. With maximum likelihood each residual covariance requires one dimension of integration. To specify a residual covariance in this case, say