You can define a unique
inset for each cell of the classification panel with the INSET= and
INSETOPTS= options. The following graph builds on the last example
by adding insets:
proc template;
define statgraph panelinset;
begingraph / designwidth=495px designheight=350px;
layout datapanel classvars=(dose) / rows=1
inset=(F PROB)
insetopts=(textattrs=(size=7pt) halign=right valign=bottom) ;
layout prototype;
bandplot x=days limitupper=uclm limitlower=lclm / name="clm"
display=(fill) fillattrs=GraphConfidence
legendlabel="95% Confidence Limits";
bandplot x=days limitupper=ucl limitlower=lcl / name="cli"
display=(outline) outlineattrs=GraphPredictionLimits
legendlabel="95% Prediction Limits";
seriesplot x=days y=predicted / name="reg"
lineattrs=graphFit legendlabel="Fit";
scatterplot x=days y=response / primary=true
markerattrs=(size=5px) datatransparency=.5;
endlayout;
sidebar / align=top;
entry "Predicted Response to Dosage (mg) over Time" /
textattrs=GraphTitleText pad=(bottom=10px);
endsidebar;
sidebar / align=bottom;
discretelegend "reg" "clm" "cli" / across=3;
endsidebar;
endlayout;
endgraph;
end;
run;
data trial;
do Dose = 100 to 300 by 100;
do Days=1 to 30;
do Subject=1 to 10;
Response=log(days)*(400-dose)* .01*ranuni(1) + 50;
output;
end;
end;
end;
run;
proc glm data=trial alpha=.05 noprint outstat=outstat ;
by dose;
model response=days / p cli clm;
output out=stats
lclm=lclm uclm=uclm lcl=lcl ucl=ucl predicted=predicted;
run; quit;
data inset;
set outstat (keep=F PROB _TYPE_ where=(_TYPE_="SS1"));
label F="F Value " PROB="Pr > F ";
format F best6. PROB pvalue6.4;
run;
data stats2;
merge stats inset;
run;
ods html style=statistical;
proc sgrender data=stats2 template=panelinset;
run;
In this template definition,
-
The INSET=(F PROB) option names
two variables that contain the values for the F statistic and its
p value. The INSETOPTS= option positions the inset and sets its text
properties.
-
The OUTSTAT= option of PROC GLM
creates a data set with several statistics for each BY value.
-
The DATA INSET step selects the
appropriate three observations from the OUTSTAT data set. The F and
PROB variables are assigned labels and formats.
-
The DATA STATS2 step creates a
new input data set by performing a non-match merge on the STATS and
INSET data sets. It is important to structure the input data in this
fashion.
Adding Insets to Classification Panels discusses this topic in detail and shows the coding for
another example in which the inset information must align correctly
in a multi-row and multi-column classification panel.