Step 1: Calculate the differences and averages. (Actually the differences are used in the plot of identity above) using this code:
DATA BA;
input large mini;
diff=large-mini;
avg=(large+mini)/2;
datalines;
… data follow…
Step 2: Specify values for the x and y axes for the plot, and this is done with macro variables in the following code:
%let minx=100;%let maxx=700;%let tickx=50;
The “tick” variable specifies how often ticks will appear on the axis. For the X axis the minimum and maximum should reflect values that fully encompass the values of the original data (mini and large in this case.)
Step 3: Create necessary information to produce the mean line at 0 using the information in the “anno” data set shown below:
data anno;
function='move'; xsys='1'; ysys='1'; x=0; y=0; output;
function='draw'; xsys='1'; ysys='1'; color='red'; x=100; y=100; size=2;
output;
run;
Step 4: The plot of identity is produced using this code (using calculated upper and lower bound previously created.)
symbol1
i=none v=dot c=black height=1;
* X AXIS - HORIZONTAL;
axis1
length=6.5 in width=1
value=(font="Arial"
h=1) order=&minx to &maxx by &tickx;
* YAXIS - VERTICAL;
axis2
length=4.5 in width=1
value=(font="Arial"
h=1) order=&minx to &maxx by &tickx;
footnote ;
proc
gplot
data=PERF;
plot large*mini /
haxis=axis1 vaxis=axis2
vref= (&blower &bupper &bmeandiff) cvref=red;
run;