1. (read data into SAS and creat permanent data sets)

libname in 'C:\carsdata';

data in.recid;
   input week arrest fin age race wexp mar paro prio educ emp1-emp52;
   cards;
20 1 0 27 1 0 0 1 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
17 1 0 18 1 0 0 1 8 4 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
25 1 0 19 0 1 0 1 13 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0
0 . . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 1 23 1 1 1 1 1 5 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0
0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 0 19 0 1 0 1 3 3 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
(I ommit many lines of data here)
;
run;

libname in 'C:\carsdata';
libname out XPORT 'C:\carsdata\recid.xpt';

data out.recid;
 set in.recid;
run;
 

2. (Bayes analysis with a normal prior on beta)

data prior;
input _TYPE_ $ age; 
datalines;
Mean 5
Var  0.6
;
run;

libname mylib 'C:\carsdata';
proc phreg data=mylib.recid;
     model week*arrest(0) = age/ties=efron;
     bayes seed=123 coeffprior=normal( input=prior );
run;

3. (plot residuals)

libname mylib 'C:\carsdata';
proc phreg data = mylib.recid;
   model week*arrest(0) = age/ties=efron;
   output out=OutP  xbeta=Xb resmart=Mart resdev=Dev; 
run;

proc sgplot data=OutP;
scatter y=Dev x=Xb;
run;

4. (output a survival curve)

data covs;
input fin age prio;
cards;
0  30  2
;
run;

libname mylib 'C:\carsdata';
proc phreg data = mylib.recid;
     model week*arrest(0) = age fin prio /ties=efron;
	 output out=pred covariates=covs survival=s /nomean;  
run;

proc gplot data=pred;
plot s*week;
run;