Would the following accomplish what you are looking for: data test_&p_1 test_&p_2 test_&p_3 test_&p_4; set test_&p; index=floor(_n_ - 1,10) + 1; if index=1 then output test_&p_1;      else if index=2 then output test_&p_2;           else if index=3 then output test_&p_3;                else if index=4 then output test_&p_4; run; Steve Denham ... View more

Is the data the problem?  The vector 'replicate' copied from your input data set appears to have 7 unique values 1 to 7, so (u-1)*20 is a row vector with 7 values, which can not be added to the vector (1:20) as they do not conform. ... View more

Hello Rick, I have modified my code as you said. This is the code, but it does not creat GIB. I do not know the dimension so I do not know how to set a default matrix; proc iml; use KMM_&p; read all var{time censored  survival1 frequency y replicate } into DM; /*read the 3 variables into matrix*/ /*have to print within DM*/ close;                                                                                     /*close the link between the dataset and IML*/   replicate=DM[,6]; y=DM[,5];frequency =DM[,4]; survival1 =DM[,3]; Censored= DM[,2]; time = DM[,1];   /*Survivalival is second column*/  /*time is first column*/ n = nrow(DM); /*number of rows in the dataset = obs*/ /*THE N DOESNT NEED TO BE FIXED*/                      /*Segment equals the number of consecutive patterns*/ /*J creates a matrix in IML , it creates a 100x1 matrix of 1s, the 3rd 1 is the value in matrix*/ segment = J(nrow(DM),1,1); *print segment; do k = 1 to ncol(u); byIdx = loc(replicate=u ); /* the UNIQUE-LOC trick */ byGroup = DM[idx,]; y=byGroup[,5];freqency =byGroup[,4]; survival1 =byGroup[,3]; Censored= byGroupDM[,2]; time = timeDM[,1]; do i = 2 to nrow(DM); if ((Censored=1)=(Censored[i-1]=1)) then segment=segment[i-1];  /**/        /* coming up with unique segments for censored*****/; else if ((Censored=1)=1-(Censored[i-1]=1)) then segment=segment[i-1]+1;                      *print time survival1 censored frequency segment;                                   *print segment; end;     SurvivalM=J(nrow(survival1),1,1);       do i = 1 to n;          if censored=1 then SurvivalM=survival1; else if censored=0 then SurvivalM=survival1;  /*****Create a 1 by N -matrix of Survival ****/;              end;           *print SurvivalM;     InverseC=J(nrow(survival1),1,1);    do i = 1 to n; if censored=1 then InverseC=1/survival1; else if censored=0 then InverseC=0;  /*****survivalC is the imputed censored survival and set the real Survivalval to 1**/;          end; do i = 1 to ncol(frequency); call symputx("j", i);    m = num(symget("j"));    m=1*m; print m;  %let mm=m; end; t=InverseC[(loc(InverseC^=0))]; print t; tt=t(t); print tt; Big=SurvivalM*(tt); end; create GIB_&p from BIG[colname={COL1}];                                  append from BIG; quit; LOCK FILE NOTE: IML Ready NOTE: Closing WORK.KMM_1 ERROR: Matrix Big has not been set to a value. statement : CREATE at line 913 column 93 ERROR: No data set is currently open for output. statement : APPEND at line 913 column 133 NOTE: Exiting IML. NOTE: The SAS System stopped processing this step because of errors. NOTE: PROCEDURE IML used (Total process time):       real time           0.00 seconds       cpu time            0.01 seconds ... View more

data test; seed=-1;   alpha1 = 2.50;   beta1 = 9.50;   do i = 1 to 100;    lambdaT = 0.025; *baseline hazard;    lambdaC= .03;  *light=0.15; *heavy=0.03;    er=0+sqrt(0.0001)*rannor(1);     t = rand("WEIBULL", 0.75, lambdaT);  * time of event;     c = rand("WEIBULL", 1.25, lambdaC) ;* time of censoring;     time = min(t, c);    * which came first?;     censored =ifn(i ne 100,(c lt t),0);       obs=(t lt c); * creating observation variable from censored when       y= alpha1 + beta1*t + er;     output;   end; run; ... View more

proc iml; use kaplan; read all  var{TIME SURVIVAL1} into DM; close; SURVIVAL1 = DM[,2]; TIME = DM[,1]; n = nrow(DM);    segment = J(nrow(DM),1,1); *print segment; SS=J(nrow(survival1),1,1); do i = 1 to n ; if i=n then SS=0; else if  i< n-1 then SS=SURVIVAL1-SURVIVAL1[i+1]; end; TT=J(nrow(time),1,1); do i = 1 to n; if i=n then TT=0;                    else if i < n-1  then TT=time[i+1]-time; end; create kaplann var{time  survival1 SS TT }; append; quit; data kaplan_sum; set kaplann; sur_time=SS*TT; drop time  survival1; run; proc print data=kaplan_sum; run; ... View more

There are lots of way to get it. Here is one way. %let dsid=%sysfunc(open(sashelp.class)); %let nobs=%sysfunc(attrn(&dsid,nlobs)); %let dsid=%sysfunc(close(&dsid)); %put &nobs ; Ksharp ... View more