/****************************************************************/
/*          S A S   S A M P L E   L I B R A R Y                 */
/*                                                              */
/*    NAME: LIFERGS2                                            */
/*   TITLE: Getting Started Example 2 for PROC LIFEREG          */
/* PRODUCT: STAT                                                */
/*  SYSTEM: ALL                                                 */
/*    KEYS: survival data analysis, Bayesian analysis           */
/*   PROCS: LIFEREG                                             */
/*    DATA:                                                     */
/*                                                              */
/* SUPPORT: lichen                                              */
/*     REF: PROC LIFEREG, INTRODUCTORY EXAMPLE 2.               */
/*    MISC:                                                     */
/****************************************************************/

data Fan;
   input Lifetime Censor@@;
   datalines;
 450 0    460 1   1150 0   1150 0   1560 1
1600 0   1660 1   1850 1   1850 1   1850 1
1850 1   1850 1   2030 1   2030 1   2030 1
2070 0   2070 0   2080 0   2200 1   3000 1
3000 1   3000 1   3000 1   3100 0   3200 1
3450 0   3750 1   3750 1   4150 1   4150 1
4150 1   4150 1   4300 1   4300 1   4300 1
4300 1   4600 0   4850 1   4850 1   4850 1
4850 1   5000 1   5000 1   5000 1   6100 1
6100 0   6100 1   6100 1   6300 1   6450 1
6450 1   6700 1   7450 1   7800 1   7800 1
8100 1   8100 1   8200 1   8500 1   8500 1
8500 1   8750 1   8750 0   8750 1   9400 1
9900 1  10100 1  10100 1  10100 1  11500 1
;
ods graphics on;
proc lifereg data=Fan;
   model Lifetime*Censor( 1 )= / dist=lognormal;
   bayes seed=1  outpost=Post;
run;
ods graphics off;
data Prob;
   set Post;
   Frac = ProbNorm(( log(8000) - Intercept ) / Scale );
   label Frac= 'Fraction Failing in 8000 Hours';
run;

proc means data = Prob(keep=Frac) n mean p10 p25 p50 p75 p90;
run;