The variable y have five more predictors in the second model. The regression coefficients are partial regression coefficients controlling for all of the predictors. This is why the indirect effect changes.
I would like to calculate the standardized indirect coefficient using the WLSMV estimator. I have used "Model Constraint" command because one of the dependent variables was binary, and sampling weights and multiple imputation were used. I would like to calculate the standardized indirect coefficient for the path from hp(binary)--> na -->dp.
DATA: FILE IS "data.dat" ; Type=Imputation; VARIABLE: Names are hp dp sa1-sa5 cont1 -cont5 ; Categorical= hp; Missing are all (-9999); Weight= RWTR; ANALYSIS: Estimator= WLSMV; MODEL: na by sa1 - sa5 ; dp on hp na (a1) cont1 -cont5 ; na on hp (b1) cont1 - cont5 ; hp on cont1 - cont5; dp (v2); hp (v1); Model Constraint: New(a1b1 stdab ); a1b1=a1* b1; stdab = a1b1*SQRT(v1)/SQRT(a1b1**2*v1+v2);
When I ran this syntax, I received an error message saying that " PARAMETERIZATION=THETA" was needed. However, when I added theta parameterization to the analysis command, all of the standard errors and p-values for coefficients were zero. I was wondering if my specification for the standardization of indirect path is incorrect and how I could fix this problem.