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Emily Blood posted on Friday, December 03, 2010  7:17 pm



I am getting the same value for the regression coefficient of a predictor if I fix the intercept/threshold term at 0 and when I don't when I fit a simple probit model to data I've generated (so I know the true values). This does not happen with a logit model. Is there a reason for this? I would think they should change. If I fit the same model with Splus I get different results. My model is: results for the "z" parameter are the same with this: y on z*0.3; [y$1@0]; and this: y on z*0.3; using THETA parameterization. 


Please send the two outputs and your license number to support@statmodel.com. 


I am curious if it is possible for Mplus to yield an intercept in a probit model similar to that given in Stata (or other programs)? I have tried doing this with the input below, but receive an error (without results) saying that the mean estimation for the categorical outcome variable is ignored. Again, I just want to calculate an intercept similar to what is given in Stata so I can compare models. If there is another way, besides what I tried below great! Categorical are class1 ; Analysis: Estimator = WLSMV; Model: ! Model of Social Class class1 ON educ prestg80 paeducM maeducM NApaeduc NAmaeduc age black asian hispanic othrace ; ! First threshold of class1 fixed at 0 [class1$1@0]; ! Freeing mean of class1 [class1]; Output: Standardized; 


The negative of the Mplus threshold is the intercept so just use that. Also, you may want to use ML. 


By that I assume you mean the negative of the first threshold. Is that correct? And I will try ML, thank you. 


Are your variables ordinal? Or binary? 

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