Thank you so much Ian This is exactly what I wont. However I received an error message which I couldn't figure it out or know how to fix it. Please see the attached file. Thank you /**AFT wiebul using Progressive TypeII censoring **/
goptions reset=all;
%macro ODSOff(); /* Call prior to BY-group processing */
ods graphics off;
ods exclude all;
ods noresults;
%mend;
%macro ODSOn(); /* Call after BY-group processing */
ods graphics on;
ods exclude none;
ods results;
%mend;
%odsoff;
proc iml;
k=100; seed=0;
B1=0;
scheme=16;n=300; m=280; R=J(m,1,0); do i=1 to m by 14; R[i]=1; end;
******************************;
odds=exp(B1);
lambda=0.5;B0=1;
**** Defining the variables for the Inference part ****;
Beta1=J(k,1,0);
Bias_B1=J(K,1,0);
MSE_B1=J(K,1,0);Var_B1=J(K,1,0);
sq1=J(K,1,0); Lower_bound=J(K,1,0); Upper_bound=J(K,1,0); Test1=J(K,1,0); odd1=J(K,1,0);
MSE_ods=J(K,1,0); Bias_ods=J(K,1,0);
**********************************************************;
Do N1=1 to K; *simulation starts here*;
** Simulation of progressive censoring ****;
hu=J(n,1,0);
Ww=J(m,1,0);X=J(m,1,0);UU1=J(m,1,0);U2=J(m,1,0);T1=J(n,1,0); V=J(n,1,0);
Y1=J(m,1,0);Z1=J(n,1,0);Z2=J(n,1,0);
Ee=J(m,1,0);Vv=J(m,1,0);ll=J(m,1,0);
** Creation of the progressive data from Uniform;
************************************************;
do i=1 to m;
Ww[i]=Uniform(seed);
ll[i]=i;
sum=0;
do j=m-i+1 to m;
sum=(R[j]+sum);
end;
Ee[i]=1/(i+sum);
Vv[i]=Ww[i]**Ee[i];
end;
do i=1 to m;
prod=1;
endloop=m-i+1 ;
do k1=m to endloop by -1;
prod=Vv[k1]*prod;
end;
UU1[i]=1-(prod);** the U's are the required progressively type II
right censored sample from U(0,1);
end;
U_obs=UU1||J(m,1,1);** progressive censored data of size m from U(0,1) with idex=1 to indicate the event occurs;
** I need the data to have a size n, so I need to generate more data from Uniform(0,1) with size of n-m;
UU0=J(n-m,1,0);
do j=1 to n-m;
UU0[j]=Uniform(seed);
end;
U_Cen=UU0||J(n-m,1,0); * These are the censored data with idex 0;
U=J(n,2,0);
U=U_obs//U_cen;
U_1=U[,1];* This is the first column of the matrix U which represents the data from Uniform both(observed + censored);
U_2=U[,2];* This is the index (1:failure OR 0:Censored);
** Simulate SRS data from Weibull **;
do jj=1 to n;
hu[jj]=Uniform(1111);
end;
Z1=quantile('Normal', hu);
C=B0+B1#Z1;
T1=exp(C)#(-log(U_1))##lambda; /*Weibull mixed between progressive and ordinary data**;
/* (1) To use the values of my r.v. in proc lifereg, we need to write them to a SAS data set using CREATE and APPEND
statements. These statements create data set AFT;*/
create AFT var { "U_obs", "U_Cen", "U" , "U_1" ,"U_2","T1", "Z1"};
append;
close AFT;
* (2) Next, the lifereg procedure is called from within IML by using SUBMIT and ENDSUBMIT statements. ;
submit;
proc lifereg data=AFT;
model T1*U_2(0) = Z1/ distribution = llogistic;
run;
proc sql noprint;
select intercept format=best20.,
Z1 format=best20.,
_SCALE_ format=best20. into
:p1 TRIMMED, :p2 TRIMMED, :p3 TRIMMED from est;
quit;
%put &=p1 &=p2 &=p3;
proc lifereg data=AFT outest=AFT_out covout ;
model T1*U_2(0) = Z1 / itprint dist=WEIBULL
intercept=&p1 initial=&p2 scale=&p3;
run;
data new_AFT;
set AFT_out;
keep Z1;
run;
proc transpose data=new_AFT out=idnumber name=Test
prefix=sn;
run;
endsubmit;
* (3) To read the results back to SAS/IML we write "use", "read", and "close";
Use idnumber;
read all var {Sn1 Sn2 Sn3 Sn4};
Close idnumber;
Beta1[N1]=Sn1;
Var_B1[N1]=Sn3;
Use AFT;
read all var {U_2};
Close AFT;
********** Inference ***********;
Beta1[N1]=Sn1;
odd1[N1]=exp(Sn1);
Var_B1[N1]=Sn3;
MSE_B1[N1]=(Beta1[N1]-B1)**2;
MSE_ods[N1]=(odd1[N1]-odds)**2;
end; *end of simulation loop (NN);
%odson
** Estimation of Beta1 ** ;
************************* ;
Beta1_hat=(Beta1[:]);
Bias_B1=abs(Beta1[:]-B1);
Bias_Beta1=round(Bias_B1,0.00001);
MSE_Beta1=round(MSE_B1[:],0.00001);
** Estimation of hazards ration OR Odds ** ;
****************************************** ;
odd1_hat=(odd1[:]);
Biasodd1=abs(odd1_hat-Odds);
Bias_odd1=round(Biasodd1,0.00001);
MSE_Odd1=round(MSE_ods[:],0.00001);
print Bias_Beta1 MSE_Beta1 Bias_odd1 MSE_Odd1;
Quit;
... View more
