Let\'s assume that you run the linear probability model and save the estimates of coefficients in a data set called sample

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* Well, it is not easy for SAS to print out something that is not part of its procedure. Let's assume that you run the linear probability model and save the estimates of coefficients in a data set called sample, with the constant renamed to b0 and slope coefficient of spread renamed to b1. (You can consult earlier SAS reading materials if you are not sure about it.)

data tmp;

set sample;

pre = b0+b1*10;

file print;

put 'Predicted probability of winning by LPM is' /

run;

pre;

The file print; statement makes sure that the output by the put command would be printed out in the output windows. The default place for the output of the put command is the log window.

* The following code would run a probit model for you.

proc logistic descending

outest = sample (keep = intercept spread

rename= (intercept = b0 spread = b1));

model favwin = spread / link=normit; test intercept = 0;

run;

Why logistic? SAS does offer a procedure called probit. You can try it out. However, the probit procedure offers very limited functionality while the logistic procedure is much more versatile. The trick here is the option link=normit in the model statement. Without this option, the logistic procedure would estimate the logit model, as its title suggests.

* After you save the estimates in a SAS dataset from the probit model in the previous block of code, you can use the following block of code to print out the prediction. data tmp;

set sample;

+ b1*10;

pre = b0 +

pre = probnorm(pre);

file print;

put 'Predicted probability of winning by the probit model is' /

run;

pre;

Note that probnorm is a SAS function which can be used to calculate the cumulative probability function of the standard normal distribution.

 

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