Programming the statistical procedures from SAS

Prediction Following a Log Transformed Dependent Variables

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Prediction Following a Log Transformed Dependent Variables

I have the following QLIM tobit model:
Log_Y = intercept + BiX + error
I want to compute the predicted values of Y (y-hat), and I am not sure how to do that. One way is as discussed in this article, but no clear code. www2.sas.com/proceedings/forum2008/370-2008.pdf

Did anyone able to conduct this, or any other method to get the predcited values from the model's prediction of the log?


I know how to do a simple exponentiation of the log, but that way gives me an erroneous prediction (super high compared to the actual).
Any other method can also work for me as long as it has been tested before.
My code is as follows:

proc qlim data=WORK.INPUT ;
class Group Location ;
model log_y = Group Location X1 X2 X3;
endogenous log_y ~ censored(lb=0);
output out=OUT1 RESIDUAL PREDICTED;
run;

 

 

The model gives me the p_log_y, and my question is how to transform this into a "correct" value. Am I doing something wrong?

 

Thanks.

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