Hi Dr. Muthen, I am trying to run a regression model with both binary and continuous predictors in the same model. Can I read the STDY output to get the estimates of the binary predictors and the STDYX output for the estimates of continuous predictors OR is there another way to get the estimates of binary and continuous predictors?
Thank you for responding so quickly. I just want to make sure that I understand what you mean. 1) Are you suggesting that in the final output that's generated, I read the StdY output for binary predictors and StdYX output for continuous predictors OR
2) Is there any way to specify in the syntax that I need Stdy for binary predictors and StdYX for continuous?
In my model I have X1 = Gender (binary) X2 = Race (binary) X3 = SES (continuous) X4 = Diversity (continuous)
My Model statement looks like:
Y1 ON X1 X2 X3 X4; Y2 ON X1 X2 X3 X4; Y3 ON X1 X2 X3 X4; Y4 ON X1 X2 X3 X4; Y5 ON X1 X2 X3 X4;
and in the output I mention: OUTPUT: standardized;
Where in this syntax can I indicate that I need Stdy for binary predictors and StdYX for continuous.
we are conducting linear regression analyses (no mediators) with ML estimation. We are requesting stdyx-standardization as well as stdy-standardization in the output-command, but regression coefficients for stdyx and stdy are identical.
The formulas for stdyx and stdy provided in the User's Guide are:
StdYX = b*SD(x)/SD(y) StdY = b/SD(y);
After using these formulas to calculate stdyx and stdy manually, we detected that the coefficients for both stdyx and stdy in the MPlus-output refer to the stdyx-formula. The stdy-coefficients that we calculated manually differ distinctively from the stdy-coefficients in the MPlus-output.
This problem is occuring in MPlus v8.0 and in MPlus v8.1.
Do you have any advice why stdyx- and stdy-coefficients are the same?