You are definitely right in what you are saying. However, there are still couple of things that I (and my colleagues) don't understand.
I have prepared some data...
DATA data;
INPUT id var1 $ var2 $ target ;
DATALINES;
1 A X 6
2 A X 2
3 A X 4
4 A Y 6
5 A Y 3
6 A Y 3
7 A Z 0
8 A Z 1
9 A Z 2
10 B X 5
11 B X 7
12 B X 8
13 B Y 0
14 B Y 9
15 B Y 3
16 B Z 7
17 B Z 7
18 B Z 2
19 A Y 1
20 B X 3
;
RUN;
I am using Poisson regression...
proc genmod data=data;
class var1(ref = "A") var2(ref = "X");
model target = var1 var2 var1*var2
/dist=Poisson link=log type1 type3;
run;
proc hpgenselect data=data;
class var1(ref = "A") var2(ref = "X");
model target = var1 var2 var1*var2
/dist=Poisson link=log;
selection method=NONE details=all;
run;
So far, so good... both procedures give identical results. Problem appears when I want only the interaction in the model. Like this:
proc genmod data=data;
class var1(ref = "A") var2(ref = "X");
model target = var1*var2
/dist=Poisson link=log type1 type3;
run;
proc hpgenselect data=data;
class var1(ref = "A") var2(ref = "X");
model target = var1*var2
/dist=Poisson link=log;
selection method=NONE details=all;
run;
This way GENMOD gives exactly what's needed. HPGENSELECT insists on previous coding and gives estimates only for intercept, {B,Y} and {B,Z}. In my opinion, that is incorrect. Of course this way the two model give different results, predicted values etc.
As you say, I can get all interaction combinations when excluding ref setting in class statement like this...
proc hpgenselect data=data;
class var1 var2;
model target = var1*var2
/dist=Poisson link=log;
selection method=NONE details=all;
run;
The problem is that I do need to have reference categories set. Seems like dead end to me... or am I still missing something?
Thank you for your reply.
