Sort of .. kind of. You would have to change some of the code. e.g.:
data have;
input ID $ Diag ReadmitID $;
cards;
101 4 111
102 3 222
103 5 333
111 4 .
222 4 .
333 6 .
;
DATA fmtDataset (drop=ReadmitID);
set have (rename=(id=start diag=label));
if missing(ReadmitID);
retain fmtname 'idcode' type 'C';
RUN;
PROC FORMAT CNTLIN=fmtDataset;
RUN;
DATA want;
set have;
if not missing(ReadmitID);
if put(ReadmitID,$idcode.) eq diag then same='yes';
else same='no';
RUN;
P.S. Isn't it about time that you marked some of the posts in this thread as being either helpful or correct or, minimally, at least indicate that the question has been answered.
Art,
I will not forget to do that...Thanks for the reminder
Yesterday I went home too early and could not respond to the answers posted by the team.
I am doing right away
Thanks
Maybe you would still consider this one simple:
data have;
input ID $ Diag ReadmitID $;
cards;
A 4 A'
B 3 B'
C 5 C'
A' 4 .
B' 4 .
C' 6 .
;
data first;
set have (where=(index(id,"'")=0));
run;
proc sort data=first;
by ReadmitID;
run;
data second;
set have (drop=ReadmitID
rename=(ID=ReadmitID
diag=diag2)
where=(index(ReadmitID,"'")));
run;
proc sort data=second;
by ReadmitID;
run;
data want;
merge first second;
by ReadmitID;
if diag eq diag2 then same="Yes";
else same="No";
run;
karun,
The second SET statement reads all the observations, and compares each to the observation read by the first SET statement.
The observation read by the first SET statement matches observation # _n_. The observation read by the second SET statement matches observation # _i_, since that second SET statement uses POINT=_i_ to control which observation to read.
Lots of interesting solutions here.
Good luck.
How about a little Hash() approach:
data have;
infile cards truncover;
input (ID Diag ReadmitID) (:$);
cards;
A 4 A'
B 3 B'
C 5 C'
A' 4
B' 4
C' 6
;
data want;
if _n_=1 then do;
if 0 then set have (rename=(diag=_diag id=_id) keep=id diag);
dcl hash h(dataset:"have(rename=(diag=_diag id=_id) keep=id diag)");
h.definekey('_ID');
h.definedata(all:'y');
h.definedone();
end;
set have;
if h.find(key:ReadmitID)=0 then flag=(diag=_diag);
drop _:;
run;
proc print;run;
Haikuo
If you are only interested in readmissions, and there can only be a single readmission per patient, then this will do it in one pass
Proc SQL ;
Create table readmit as
Select adm.ID
, adm.Diag
, adm.ReadmitID
, rad.Diag As ReadmitDiag
, case (rad.Diag)
When (adm.Diag)
Then 'Y'
Else 'N'
End
As Match
From admit adm
, admit rad
Where rad.ID = adm.ReadmitID
;
Quit ;
However, if you want a more general solution where the possibility of multiple readmissions exists then it would be better to recode the readmission ID to match the original admission, then process the resulting dataset for non matches. If this is the case, I could suggest some code.
Richard in Oz
HaiKuo's code maybe is the fastest way.Here is another SQL solution.
Data is from ArthurT.
data have; input ID $ Diag ReadmitID $; cards; A 4 A' B 3 B' C 5 C' A' 4 . B' 4 . C' 6 . ; run; proc sql; create table want as select h.*,case when h.diag eq (select diag from have where id eq h.ReadmitID) then 'Yes' when h.diag ne (select diag from have where id eq h.ReadmitID) then 'No' else 'No matched' end as flag length=10 from have as h ; quit;
Ksharp
Don't miss out on SAS Innovate - Register now for the FREE Livestream!
Can't make it to Vegas? No problem! Watch our general sessions LIVE or on-demand starting April 17th. Hear from SAS execs, best-selling author Adam Grant, Hot Ones host Sean Evans, top tech journalist Kara Swisher, AI expert Cassie Kozyrkov, and the mind-blowing dance crew iLuminate! Plus, get access to over 20 breakout sessions.
Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.
Find more tutorials on the SAS Users YouTube channel.