Example 1 for PROC LIFEREG

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/*          S A S   S A M P L E   L I B R A R Y                 */
/*                                                              */
/*    NAME: LIFEREX1                                            */
/*   TITLE: Example 1 for PROC LIFEREG                          */
/* PRODUCT: STAT                                                */
/*  SYSTEM: ALL                                                 */
/*    KEYS: survival data analysis                              */
/*   PROCS: LIFEREG                                             */
/*    DATA:                                                     */
/*                                                              */
/* SUPPORT: lichen                                              */
/*     REF: PROC LIFEREG, EXAMPLE 1.                            */
/*    MISC:                                                     */
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title 'Motorette Failures With Operating Temperature as a Covariate';
data motors;
   input time censor temp @@;
   if _N_=1 then
      do;
         temp=130;
         time=.;
         control=1;
         z=1000/(273.2+temp);
         output;
         temp=150;
         time=.;
         control=1;
         z=1000/(273.2+temp);
         output;
      end;
   if temp>150;
   control=0;
   z=1000/(273.2+temp);
   output;
   datalines;
8064 0 150 8064 0 150 8064 0 150 8064 0 150 8064 0 150
8064 0 150 8064 0 150 8064 0 150 8064 0 150 8064 0 150
1764 1 170 2772 1 170 3444 1 170 3542 1 170 3780 1 170
4860 1 170 5196 1 170 5448 0 170 5448 0 170 5448 0 170
 408 1 190  408 1 190 1344 1 190 1344 1 190 1440 1 190
1680 0 190 1680 0 190 1680 0 190 1680 0 190 1680 0 190
 408 1 220  408 1 220  504 1 220  504 1 220  504 1 220
 528 0 220  528 0 220  528 0 220  528 0 220  528 0 220
;
proc print data=motors;
run;
proc lifereg data=motors outest=modela covout;
   a: model time*censor(0)=z;
      output out=outa quantiles=.1 .5 .9 std=std p=predtime
         control=control;
run;
proc lifereg data=motors outest=modelb covout;
   b: model time*censor(0)=z / dist=lnormal;
      output out=outb quantiles=.1 .5 .9 std=std p=predtime
         control=control;
run;
data models;
   set modela modelb;
run;
proc print data=models;
   id _model_;
   title 'Fitted Models';
run;
data out;
   set outa outb;
run;

data out1;
   set out;
   ltime=log(predtime);
   stde=std/predtime;
   upper=exp(ltime+1.64*stde);
   lower=exp(ltime-1.64*stde);
run;
title 'Quantile Estimates and Confidence Limits';
proc print data=out1;
   id temp;
run;
title;