/*  The data we examine are the drug amounts and reaction times */
/* from the example we studied in class                         */

/* As in class, suppose we want to calculate CIs for mean reaction time   */
/* and prediction intervals for reaction time at particular drug amounts. */

/* The options clm and cli will give us CIs for E(Y) and PIs for Y, for the values        */
/* of X (the drug amounts) in the data set.                                               */
/* But suppose we were interested in the 95% CI for mean reaction time and 95% prediction */
/* interval for reaction time, for a person who had 3.5 % drug amount.     	          */
/* Note that 3.5 is not among the drug amounts in the data set, so we create a "new"      */
/* observation with DRUG_X=3.5 and TIME_Y=. (missing):                                    */

/* Note that I'm giving this data set a new name, PREDSTIM: */

DATA PREDSTIM;
INPUT DRUG_X TIME_Y;
CARDS;
        1         1
        2         1
        3         2
        4         2
        5         4
        3.5       .
;

PROC REG DATA=PREDSTIM;
MODEL TIME_Y=DRUG_X /clm cli;
RUN; 

/* Look at the last line of the "Output Statistics".  This shows the prediction        */
/* for the person with 3.5 % drug amount.  We see the predicted 	               */
/* reaction time for this person is 2.35 seconds.  The 95% CI for mean reaction time   */
/* for all people with 3.5 % drug amount is between 1.44 and 3.26 seconds.             */
/* The prediction interval for the reaction time for a new person who has drug         */
/* amount 3.5 % is (0.22, 4.48) in seconds.  These results match what we saw in class. */