Farewell Reeza ! Hope one day you could come back in the future ! ... View more

Then plz post the sample dataset , so I think test it . Still using sas built-in dataset sashelp.bmt to test,and still not found any problem . Referring to the following code,maybe you could found where the problem is by yourself. proc lifetest data=sashelp.bmt plots=cif(test ) notable OUTCIF=cifnrm_out ; time t*status(0)/eventcode=1; strata group/order=internal; run; data time; do t=0 to 2500 by 100; output; end; run; proc sql; create table temp as select * from (select distinct Group from cifnrm_out),time order by 1,2; quit; data want; set cifnrm_out temp(in=inb); by Group t; retain temp; if first.Group then call missing(temp); if not missing(AtRisk) then temp=AtRisk; if inb then time_AtRisk=temp; keep Group t AtRisk CIF time_AtRisk ; run; options missing=' '; proc sgplot data=want; step x=T y=CIF/group=Group; xaxistable time_AtRisk/class=group colorgroup=Group location=inside; xaxis label='Disease-Free Survival Time' values=(0 to 2500 by 100) fitpolicy=stagger; /*fitpolicy=none*/ yaxis values=(0 to 1 by 0.2); run;   ... View more

Then tell me where is different between mine and yours ? Here is my output.   ... View more

With using the builded-in sas dataset SASHELP.BMT as a sample dataset to test your code. I think I found where the problem is: You missed T variable in your code,check my original code. data model1_tert2(keep= T Group eventstatus ); set sashelp.bmt; rename status=eventstatus; run; proc lifetest data=model1_tert2 plots=cif(test ) notable OUTCIF=cifnrm_out ; time T*eventstatus(0)/eventcode=1; strata Group/order=internal; run; data time; /*do t=0 to 3.0 by 0.5; */ do t=0 to 2500 by 500; output; end; run; proc sql; create table temp as select * from (select distinct Group from cifnrm_out),time order by 1,2; quit; data test; set cifnrm_out temp(in=inb); by Group T; /* <------- You missed the T variable*/ retain temp; if first.Group then call missing(temp); if not missing(AtRisk) then temp=AtRisk; if inb then time_AtRisk=temp; keep Group T AtRisk CIF time_AtRisk ; run; Open dataset TEST,you could see the different value from different T.     ... View more

"The data attached is a mock up data as I can't send the actual data." Where is your dataset? I don't see any attachment. ... View more

I like the idea proposed by Tom, using 'compute before _page_'+'line ' to replace title statment, to make line statement look more like title, try this one :   title; options nobyline; ods layout gridded columns=3 advance=bygroup; proc report data=sashelp.iris nowd style(report)={frame=void} style(column header)={borderwidth=2px bordertopwidth=2px}; by species; columns species sepal:; define species / group noprint; define sepal: / mean; break after species / page; compute before _page_/style={bordercolor=cxFAFBFE borderwidth=2px fontweight=bold} ; line 'Species: ' species $20.; endcomp; run; ods layout end; options byline;   ... View more

One more approach: Especially for the formula which is unable to handle by %sysevalf(). Data have; input x y z; cards; 10 20 30 15 20 200 10 30 40 ; run; data formula_tbl; input formula $20.; cards; x+y-0.1*x x+y+z ; run; proc sql; create table t1 as select * from have,formula_tbl ; quit; filename x temp; data _null_; set t1 end=last; file x; if _n_=1 then put 'data want; set t1;'; put 'if _n_=' _n_ 'then result=' formula ';'; if last then put 'run;'; run; %include x; ... View more

Plz post your sample data,so I can test it . And post your FULL code, you should notice that I have one more data step to get the number of risk before PROC SGPLOT ,but you didn't post it yet. ... View more

Data have; input x y z; cards; 10 20 30 15 20 200 10 30 40 ; run; data formula_tbl; input formula $20.; cards; x+y-0.1*x x+y+z ; run; proc sql; create table t1 as select * from have,formula_tbl ; quit; data want; set t1; length _formula $ 200; _formula=formula; array _x{*} _numeric_; do i=1 to dim(_x); _formula=tranwrd(lowcase(_formula),lowcase(vname(_x{i})),strip(_x{i})); end; result=input(resolve(cats('%sysevalf(',_formula,')')),best32.); drop i _formula; run; ... View more

Rick, I have already read your blog .GREAT ! I think you should rename this post as  Fun With SAS ODS Graphics: A normal Christmas tree to make @tc    notice it .     ... View more

OK. If you have a BIG table, try the following Hash Table:   data have; input id 1 hp_01 $ 3-5 hp_02 $ 7-9 hp_03 $ 11-13 hp_04 $ 15-17 hp_05 $ 19-21 hp_06 $ 23-25 hp_07 $ 27-29 hp_08 $ 31-33 hp_09 $ 35-37 hp_10 $ 39-41 hp_11 $ 43-45 hp_12 $ 47-49; datalines; 1 MCO MCO MCO PPO PPO PPO PPO PPO PPO PPO PPO PPO 2 PDP PDP PDP PDP PDP PDP PDP PDP PDP PDP MCO MCO 3 EDP EDP EDP EDP EDP EDP PPO PPO PPO PPO PPO PPO 4 MCO MCO MCO MCO MCO MCO MCO MCO MCO EDP EDP EDP 5 EDP EDP EDP EDP MCO MCO PPO PPO PPO PPO EDP EDP 6 MCO NET NET NET EDP EDP NET NET MCO MCO MCO MCO 7 PPO PPO PPO NET NET NET NET NET PPO PPO MCO MCO 8 EDP MCO MCO MCO PPO PPO PPO PPO PPO NET NET NET 9 NET NET NET NET PPO PPO PPO PPO PPO PPO PPO PPO ; data want; if _n_=1 then do; length key $ 80; declare hash h(); declare hiter hi('h'); h.definekey('key'); h.definedata('key','count','idx'); h.definedone(); end; set have; h.clear(); array x{*} hp_01-hp_12; do i=1 to dim(x); if not missing(x{i}) then do; key=x{i}; if h.find()=0 then count=count+1; else count=1; idx=i; h.replace(); end; end; do while(hi.next()=0); if want_count<count then do;want_key=key;want_count=count;want_idx=idx;end; else if want_count=count and want_idx<idx then do;want_key=key;want_idx=idx;end; end; drop i key count idx; run; ... View more

[EDIT] OK. Using SUM() function to replace with + operator, SUM() would take care of missing value.   data have; input id date :yymmdd10. a b c d e f; format date yymmdd10.; datalines; 1 2020-01-01 0 1 . 0 0 0 1 2018-07-06 0 1 . 0 0 1 2 2015-02-15 1 2 0 1 2 3 3 2020-02-01 1 1 1 3 3 3 3 2021-07-05 1 1 0 3 3 3 3 2021-08-09 1 1 1 3 3 3 4 2020-01-30 0 2 . 1 0 0 5 2018-10-10 1 2 0 0 1 2 5 2019-10-11 1 2 0 1 2 2 ; RUN; proc sql; create table want as select *,sum(range(a),range(b),range(c))=0 as same from have group by id; quit;   And if you also need to consider about missing and zero or other non-mssing values (id=0), check this: data have; input id date :yymmdd10. a b c d e f; format date yymmdd10.; datalines; 0 2020-01-01 0 1 . 0 0 0 0 2018-07-06 0 1 0 0 0 1 0 2018-07-06 0 1 0 0 0 1 1 2020-01-01 0 1 . 0 0 0 1 2018-07-06 0 1 . 0 0 1 2 2015-02-15 1 2 0 1 2 3 3 2020-02-01 1 1 1 3 3 3 3 2021-07-05 1 1 0 3 3 3 3 2021-08-09 1 1 1 3 3 3 4 2020-01-30 0 2 . 1 0 0 5 2018-10-10 1 2 0 0 1 2 5 2019-10-11 1 2 0 1 2 2 ; RUN; proc sql; create table want as select *, sum( count(distinct a)+(nmiss(a) ne 0), count(distinct b)+(nmiss(b) ne 0), count(distinct c)+(nmiss(c) ne 0) )=3 as same from have group by id; quit;     ... View more

It is related to Statistical Theory, better post it at Stat Forum: https://communities.sas.com/t5/Statistical-Procedures/bd-p/statistical_procedures   proc freq data=sashelp.heart; table bp_status*smoking_status/expected norow nocol nopercent nofreq; run;     ... View more