## Proc GENMOD Effectplot plotby

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Posts: 10

# Proc GENMOD Effectplot plotby

I am using sas v9.3 proc genmod to model a continuous outcome:

``````PROC GENMOD;
class number train bl/param=glm;
model y= train age mt pn eo tncc bl;
effectplot fit (x=mt plotby=train)/obs;
repeated subject=number/type=ar rupdate=2;
run;``````

My class variable train has 8 levels, but the effectplot displays on trainer 1, 4, 5, 6, 7, and 8. Trainers 2 and 3 are ommited for some reason. If a perform a slicefit plotby train, all levels are displayed, but that isn't the graph I really want. Any reason two levels of my class variable are being omitted?

Thanks!

Katy

Accepted Solutions
Solution
‎12-06-2017 12:24 PM
SAS Super FREQ
Posts: 4,239

## Re: Proc GENMOD Effectplot plotby

Most likely reason is that you have insufficient observations to fit a model for those levels, due to missing value in other variables. The following simulated data has a similar structure to what you have specified. Run it and see if you get 8 plots.  If so, the problem is probably related to your data:

``````data have;
call streaminit(1);
do number=1 to 4;
age = 20 + ceil(20*rand("uniform"));
do train=1 to 8;
do j = 1 to 4;
mt = rand("Normal");
y = 2 + age + 3*train - mt + rand("normal");
output;
end;
end;
end;
run;

PROC GENMOD data=have;
class number train /param=glm;
model y= train age mt;
effectplot fit (x=mt plotby=train)/obs;
repeated subject=number/type=ar rupdate=2;
run;``````

All Replies
Solution
‎12-06-2017 12:24 PM
SAS Super FREQ
Posts: 4,239

## Re: Proc GENMOD Effectplot plotby

Most likely reason is that you have insufficient observations to fit a model for those levels, due to missing value in other variables. The following simulated data has a similar structure to what you have specified. Run it and see if you get 8 plots.  If so, the problem is probably related to your data:

``````data have;
call streaminit(1);
do number=1 to 4;
age = 20 + ceil(20*rand("uniform"));
do train=1 to 8;
do j = 1 to 4;
mt = rand("Normal");
y = 2 + age + 3*train - mt + rand("normal");
output;
end;
end;
end;
run;

PROC GENMOD data=have;
class number train /param=glm;
model y= train age mt;
effectplot fit (x=mt plotby=train)/obs;
repeated subject=number/type=ar rupdate=2;
run;``````
☑ This topic is solved.