Hi, there:
I'm trying to analyze data using linear mixed effects model, and creating predicted mean graph with band.
I want to change band color like following code & picture, but I can't find how to do that.
For example, at X between 19.95 and 20.25 accurately, I want to change band color from blue to red.
Please help me. Thank you in advance.
data hospital;
input hospital physician x y @@;
datalines;
1 1 19.4 32.4 1 1 19.3 28.3 1 1 19.2 31.9
1 2 18.8 18.9 1 2 18.4 20.3 1 2 18.2 21.3
1 3 19.7 24.8 1 3 20.4 38.6 1 3 20.2 27.4
1 4 19.3 36.1 1 4 21.7 32.4 1 4 20.8 30.7
2 1 21.5 31.3 2 1 18.7 28.5 2 1 19.9 20.1
2 2 18.9 31.8 2 2 18.7 25.1 2 2 19.5 32.9
2 3 18.7 18.3 2 3 19.4 27.4 2 3 19.5 26.2
2 4 20.9 28.6 2 4 21.1 29.9 2 4 20.0 16.4
;
run;
proc mixed data=hospital alpha=0.1;
class hospital physician;
model y=x / ddfm=kr solution outpm=Predicted;
random int / subject=physician(hospital);
run;
proc sort data=Predicted;
by x;
run;
proc sgplot data=Predicted;
band x=x lower=Lower upper=Upper / legendlabel="90% CLM";
series x=x y=pred;
scatter x=x y=y;
run;
Hi Kenta, as i understand you need to have youe band changing at 19 even if there are noe real observations there.
The trick will be to make a new variable that always has the values that you need. The way to do that would be to predict your band making certain 19 is a value in the band. Some manipulation in setting missing and values at the right points are needded to make the graph look good.
Use 2 band plots.
Hi, Mr. Sanjay:
Thank you for your response, and so sorry for less information.
I already have tried "2 BAND Statements", but I have no idea about what structure PREDICTED dataset should have in this case.
I want to know the best structure.
Thank you.
You can also take the "grouped band" approach in this case:
data hospital;
input hospital physician x y @@;
datalines;
1 1 19.4 32.4 1 1 19.3 28.3 1 1 19.2 31.9
1 2 18.8 18.9 1 2 18.4 20.3 1 2 18.2 21.3
1 3 19.7 24.8 1 3 20.4 38.6 1 3 20.2 27.4
1 4 19.3 36.1 1 4 21.7 32.4 1 4 20.8 30.7
2 1 21.5 31.3 2 1 18.7 28.5 2 1 19.9 20.1
2 2 18.9 31.8 2 2 18.7 25.1 2 2 19.5 32.9
2 3 18.7 18.3 2 3 19.4 27.4 2 3 19.5 26.2
2 4 20.9 28.6 2 4 21.1 29.9 2 4 20.0 16.4
;
run;
proc mixed data=hospital alpha=0.1;
class hospital physician;
model y=x / ddfm=kr solution outpm=Predicted;
random int / subject=physician(hospital);
run;
proc sort data=Predicted;
by x;
run;
proc format;
value myfmt 1="Okay"
2="Critical"
;
run;
data grouped;
set Predicted;
format Areas myfmt.;
if x > 19.95 and x < 20.25 then
Areas=2;
else
Areas=1;
run;
proc sgplot data=grouped;
styleattrs datacolors=(lightblue red);
band x=x lower=Lower upper=Upper / group=Areas name="Band";
series x=x y=pred / name="Fit" legendlabel="Fit, with 90% CLM";
scatter x=x y=y;
keylegend "Fit" / position=bottomleft;
keylegend "Band" / position=bottomright;
run;
Hi, Mr. DanH:
Thank you for your response.
"Grouped Band" Approach, I didn't know, and it seems like good.
But for example, if 19 le X le 20, I couldn't create Band between 19 le X le 20 "accurately", because the data PREDICTED has no value "19". I'm sorry, but I want to create band that expresses specific range "accurately".
And blue band protrudes slightly in my result:(
Please help me.
Hi Kenta, as i understand you need to have youe band changing at 19 even if there are noe real observations there.
The trick will be to make a new variable that always has the values that you need. The way to do that would be to predict your band making certain 19 is a value in the band. Some manipulation in setting missing and values at the right points are needded to make the graph look good.
Hi, PaalNavestad:
Thank you for your response.
Thanks for your opinion, I got one idea, and I accomplished my objective.
data hospital;
input hospital physician x y @@;
datalines;
1 1 19.4 32.4 1 1 19.3 28.3 1 1 19.2 31.9
1 2 18.8 18.9 1 2 18.4 20.3 1 2 18.2 21.3
1 3 19.7 24.8 1 3 20.4 38.6 1 3 20.2 27.4
1 4 19.3 36.1 1 4 21.7 32.4 1 4 20.8 30.7
2 1 21.5 31.3 2 1 18.7 28.5 2 1 19.9 20.1
2 2 18.9 31.8 2 2 18.7 25.1 2 2 19.5 32.9
2 3 18.7 18.3 2 3 19.4 27.4 2 3 19.5 26.2
2 4 20.9 28.6 2 4 21.1 29.9 2 4 20.0 16.4
;
run;
proc mixed data=hospital;
class hospital physician;
model y=x / ddfm=kr solution outpm=Predicted alpha=.1 alphap=.1;
random int / subject=physician(hospital);
store mixed;
run;
data new;
input x @@;
datalines;
19 20
;
run;
proc plm source=mixed alpha=.1;
score data=new out=stat lclm=lower uclm=upper;
run;
data predicted_1;
set predicted(where=(19 le x le 20))
stat;
keep x lower upper;
rename x=x1 lower=lower1 upper=upper1;
run;
proc sql;
create table work.predicted_2 as
select a.*, b.*
from work.predicted as a
full join
work.predicted_1 as b
on a.x eq b.x1;
quit;
proc sort data=predicted_2;
by x;
run;
proc sgplot data=Predicted_2;
band x=x lower=Lower upper=Upper / legendlabel="90% CLM" fillattrs=(color=blue);
band x=x1 lower=lower1 upper=upper1 / legendlabel="xxxxx" fillattrs=(color=red);
series x=x y=pred;
scatter x=x y=y;
run;
I predicted for new observation by using STORE statement & PLM Procedure.
Thank you, everyone!! I did it!!
Glad it worked. Another idea would be to use a block plot to mark the areo interest.
That would create areas of different shades across the whole plot region. The documentation show good examples of how it works.
Also so nice of you showing with an example how you solved it.
Hi, PaalNavestad:
Thank you.
I searched BLOCK statement in SGPLOT.
I don't want figure like rectangular block now, but I thank you for advice.
Anyway, thank you!!
Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 25. Read more here about why you should contribute and what is in it for you!
Learn how use the CAT functions in SAS to join values from multiple variables into a single value.
Find more tutorials on the SAS Users YouTube channel.