A55233.sas

/*-----------------------------------------------------------------*/
/* Survival Analysis Using the SAS System: A Practical Guide       */
/* by Paul D. Allison                                              */
/*                                                                 */
/* SAS Publications order # 55233                                  */
/* ISBN 1-55544-279-X                                              */
/* Copyright 1995 by SAS Institute Inc., Cary, NC, USA             */
/*                                                                 */
/* SAS Institute does not assume responsibility for the accuracy   */
/* of any material presented in this file.                         */
/*-----------------------------------------------------------------*/


/*
This file contains programs and data sets from the book, "Survival
Analysis Using the SAS System: A Practical Guide" by Paul D. Allison,
Ph.D.  The file lists, in order,

-- data sets used in the book
-- programs used in the book
-- macros used in the book.

*************************************************************************
*************************************************************************

DATA SETS USED IN THIS BOOK


-------------
MYEL Data Set
-------------
*/

/* Data described in Chapter 3 of P.D. Allison, "Survival Analysis
   Using the SAS System: A Practical Guide."                       */


data myel;
input id dur status treat renal;
cards;
1  8 1 1 1
2 180 1 2 0
3 632 1 2 0
4 852 0 1 0
5 52  1 1 1
6 2240 0 2 0
7 220 1 1  0
8 63  1 1  1
9 195 1 2 0
10 76 1 2 0
11 70 1 2 0
12 8 1 1 0
13 13 1 2 1
14 1990 0 2 0
15 1976 0 1 0
16 18 1 2 1
17 700 1 2 0
18 1296 0 1 0
19 1460 0 1 0
20  210 1 2 0
21  63 1 1 1
22  1328 0 1 0
23  1296 1 2 0
24  365 0 1 0
25  23 1 2 1
;






--------------
RECID Data Set
--------------

/* Data described in Chapter 3 of P. Allison, "Survival Analysis
   Using the SAS System." */


data 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
52 0 0 24 1 1 0 0 2 4 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 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 0 0 0 0 0
23 1 0 25 1 1 1 1 0 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 1 21 1 1 0 1 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 1 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 22 1 0 0 0 6 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 0 0
0 0 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
52 0 0 20 1 1 0 0 0 5 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 26 1 0 0 1 3 3 0 0 0 0 0 0 0 0 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 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1
52 0 0 40 1 1 0 0 2 5 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
37 1 0 17 1 1 0 1 5 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 1 0 0 0 0 0 0 0 0 . . . . . . . . . . . . . . .
52 0 0 37 1 1 0 0 2 3 0 0 0 0 0 0 0 0 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 1 1 1 1 1 1 1 1 1 1 1 1 1
25 1 0 20 1 0 0 1 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 0 0
. . . . . . . . . . . . . . . . . . . . . . . . . . .
46 1 1 22 1 1 0 1 2 3 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 . . . . . .
28 1 0 19 1 0 0 0 7 3 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0
0 0 0 . . . . . . . . . . . . . . . . . . . . . . . .
52 0 0 20 1 0 0 0 2 3 0 0 0 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 25 1 0 0 1 12 3 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 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 24 0 1 0 1 1 3 0 1 1 0 0 0 0 0 1 1 1 1 1 1 0 0 0 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 0 0 0 0 0 0
52 0 0 23 1 0 0 1 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
52 0 1 44 1 1 1 1 0 3 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 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 1
24 1 1 29 1 1 0 1 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 1 28 0 1 0 1 1 3 1 1 1 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 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1
52 0 1 21 1 1 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 0
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
52 0 1 19 1 1 0 1 2 3 0 0 0 0 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 0 33 1 1 0 1 1 4 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 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
52 0 0 19 1 0 0 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 19 1 0 0 1 3 3 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 23 1 1 1 1 9 3 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
1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 23 1 0 0 1 3 5 0 0 0 0 0 0 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 19 1 0 0 1 1 3 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 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 1
52 0 1 42 1 1 0 0 0 5 0 0 1 1 1 1 0 0 0 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 0 0 0 0 0
52 0 0 23 1 1 1 0 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 0
52 0 0 24 1 1 0 0 3 4 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
50 1 1 20 1 1 0 1 2 3 0 0 1 1 1 1 0 0 0 0 1 1 1 1 1 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 1 1 1 1 1 . .
52 0 0 22 1 1 0 1 5 3 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 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
52 0 0 27 1 1 0 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 19 1 0 0 0 4 3 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 28 1 1 0 1 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 33 1 1 1 0 9 3 0 1 1 1 1 1 0 0 0 0 0 0 0 1 1 1 1 1 1 1 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 0 0 0 0 0
52 0 0 24 1 1 0 1 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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 0 0 0 0 0 0
10 1 0 21 1 0 0 1 14 3 0 0 0 0 0 0 1 1 1 1 . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 0 22 1 0 0 1 2 3 0 0 0 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 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 19 1 0 0 1 2 4 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 22 1 0 0 0 2 4 0 0 0 0 0 0 0 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 22 1 0 0 0 15 3 0 0 0 0 0 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 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0
20 1 1 23 1 1 0 1 5 3 0 0 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 0 32 1 1 1 1 2 2 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 27 1 1 0 1 0 4 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 36 1 1 0 0 0 3 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 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 1
52 0 1 22 1 1 0 1 1 4 0 0 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 32 1 1 0 1 1 3 0 0 1 0 0 0 0 0 0 0 0 0 0 0 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 1 1 1 1 1 1 1
50 1 1 19 1 1 0 0 10 3 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 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 . .
52 0 0 28 1 1 1 1 1 5 0 0 0 0 0 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1
52 0 0 32 0 1 0 0 3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 33 1 1 1 1 1 4 0 0 0 0 1 1 1 1 1 1 1 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 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 26 1 0 0 1 1 2 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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 1 1
52 0 1 20 1 1 0 1 0 3 0 0 0 0 0 0 0 1 0 1 1 0 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 1 1 1 1 1 1 1 1 1
52 0 1 42 1 1 0 0 9 4 0 0 0 0 0 0 0 0 0 0 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 1 1 1 1 1 1 1 1 1 1 1
6 1 0 19 1 0 0 0 6 3 0 0 0 0 0 0 . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 0 22 1 1 0 0 2 4 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 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 0
52 0 0 22 1 0 0 1 5 4 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0
0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 36 1 0 0 0 11 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0
52 1 0 23 1 1 0 0 2 4 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0
52 0 1 27 1 1 0 1 3 3 0 0 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 0 0 0 0 0 0 0 0 1 1 1 1 1 1
52 0 1 21 1 0 0 1 1 3 0 0 0 0 0 0 0 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 22 1 1 0 1 2 3 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
49 1 0 35 1 1 0 1 3 2 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 . . .
52 0 0 21 1 1 0 1 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 25 1 1 0 1 5 3 0 1 1 1 1 1 1 1 0 0 1 1 1 0 0 0 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 0 0 0 0 0 0 0
52 0 0 18 1 0 0 1 0 3 0 0 0 0 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 26 1 1 0 1 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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 1 1 1 1 1 1 1
52 0 0 30 1 1 0 0 4 2 0 0 0 0 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 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1
52 0 0 20 1 0 0 1 2 4 0 0 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 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 43 1 1 0 1 1 4 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
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 1 1
43 1 0 23 1 1 1 1 4 3 1 1 0 0 0 0 0 0 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 . . . . . . . . .
52 0 0 42 0 1 0 0 2 6 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 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 1
52 0 0 21 0 0 0 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
5 1 0 19 1 0 0 0 3 3 0 0 0 0 0 . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
27 1 0 29 1 0 0 0 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 0 30 1 1 0 1 3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 21 0 1 1 1 10 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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 1 1 1
52 0 0 20 1 0 0 1 7 3 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
22 1 1 19 1 0 0 1 10 3 0 0 0 0 1 1 1 1 1 1 1 0 0 0 0 0 0 1 0 0 0 0 . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 1 22 1 1 0 1 1 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 25 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 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
18 1 0 22 1 0 0 0 4 4 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 1 22 1 1 0 1 4 3 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 1 1 1 0 0 0 0 0 0
0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0
52 0 1 24 1 0 0 1 2 4 0 0 0 0 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0
52 0 0 39 1 1 1 1 4 3 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
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 1 1
52 0 0 21 1 1 0 1 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 1 1 1 1 1 0 0 0 0 0 1 1 1 0 0 1 1 1 1 1 1 1 1 1
52 0 1 20 1 1 0 1 2 3 0 0 0 1 1 1 1 0 0 0 0 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1
52 0 1 24 1 0 0 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 1 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 1 1 1 1 1 1 1 1 1 1 1
52 0 0 25 1 1 0 1 2 6 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
24 1 1 21 1 1 0 0 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 1 20 1 0 0 1 1 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 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 1 1 1 1
52 0 1 19 1 0 0 1 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0
0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
52 0 1 24 1 0 0 0 2 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 24 1 1 0 1 1 4 0 0 0 0 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1
2 1 0 44 1 1 0 1 2 5 0 0 . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
26 1 0 32 1 1 0 0 2 4 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 . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 0 23 1 1 0 0 3 3 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
49 1 1 19 1 0 0 1 1 4 0 0 0 0 0 0 0 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 0 0 0 0 0 0 0 0 0 0 0 . . .
52 0 0 20 1 0 0 1 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1
21 1 0 27 1 1 0 1 0 3 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
48 1 0 19 1 0 0 0 6 3 0 0 0 0 0 0 0 0 0 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 . . . .
52 0 1 21 1 1 0 0 1 3 0 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 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
52 0 0 20 1 0 0 1 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 25 1 0 0 1 3 2 0 0 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 0 20 1 0 0 1 6 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0
52 0 1 23 1 1 0 1 3 4 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 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 1
52 0 0 20 1 0 0 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 0 1
0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 30 1 1 0 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0
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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 1 1
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. . . . . . . . . . . . . . . . . . . . . . . . . . .
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1 1 1 1 1 1 1 1 1 1 1 1 1 1 . . . . . . . . . . . . .
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19 1 1 22 1 0 0 1 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 . . . . . .
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48 1 1 24 0 1 0 0 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 . . . .
37 1 1 26 0 0 0 0 11 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 . . . . . . . . . . . . . . .
20 1 1 26 1 1 0 1 1 4 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 0 . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 0 25 0 1 0 1 1 6 0 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 26 1 1 0 1 1 4 0 0 0 0 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
36 1 1 23 1 0 0 0 3 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 . . . . . . . . . . . . . . . .
52 0 1 28 1 0 0 1 4 3 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 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 1 1 1 1 1
52 0 0 27 1 1 0 1 0 5 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 23 1 0 0 0 3 4 0 1 1 1 0 0 0 0 0 0 0 0 0 0 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 1 1 1 1 0 0 0
52 0 0 17 1 0 0 1 7 3 0 0 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0
52 0 0 20 0 0 0 1 4 5 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 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 0 0 0 0
52 0 1 20 1 0 0 1 5 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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 0 0 0
52 0 1 20 0 0 0 1 9 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
30 1 1 22 1 1 0 1 2 4 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 . . . . . . . . . . . . . . . . . . . . . .
52 0 0 31 1 0 0 1 1 3 0 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 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
52 0 0 43 1 1 0 0 1 5 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
1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 29 1 1 0 0 1 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 21 1 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 24 0 1 0 0 2 3 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 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 30 1 1 1 0 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 22 1 1 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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 0 0 0
52 0 1 26 1 1 1 0 1 4 0 0 0 0 0 1 1 1 1 1 1 1 1 0 0 0 1 1 1 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 1 1 1 1 1
42 1 1 20 1 1 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 1 1 1
1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 . . . . . . . . . .
52 0 0 23 1 1 0 0 6 4 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 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 25 1 1 0 1 5 3 0 0 0 0 0 0 0 0 0 0 0 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 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1
52 0 1 40 1 1 0 1 2 5 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0
0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 30 1 1 1 1 0 3 0 0 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
26 1 0 22 1 0 1 1 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 . . . . . . . . . . . . . . . . . . . . . . . . . .
40 1 0 18 1 0 0 1 2 4 0 0 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 0 . . . . . . . . . . . .
52 0 0 18 1 0 0 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 24 1 1 0 1 2 5 0 1 1 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 25 1 1 1 1 2 5 0 0 0 0 0 0 0 0 0 0 0 0 1 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 1 1 1 1 1 1 1 1
35 1 1 19 1 0 0 1 2 3 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 1 1 0 0 0 0 0 0 . . . . . . . . . . . . . . . . .
52 0 0 24 1 1 0 1 2 3 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 1 1 1 1 1 1 1 1 1 1 1 1 1
46 1 0 24 1 0 1 1 2 3 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 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 1 . . . . . .
52 0 0 18 1 1 0 1 3 5 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 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
49 1 1 18 1 1 0 1 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 . . .
52 0 0 23 1 1 0 0 0 3 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
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 1 1
52 0 0 20 1 0 0 1 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
49 1 1 18 1 1 0 1 1 3 0 0 0 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 . . .
52 0 0 23 1 1 0 1 2 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 1 20 1 0 0 1 1 3 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 23 1 0 0 0 5 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 23 1 1 0 1 1 4 0 0 0 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 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 0 0 23 1 1 1 1 2 3 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
35 1 0 20 1 1 0 1 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 . . . . . . . . . . . . . . . . .
52 0 1 26 1 1 1 0 4 2 0 0 0 0 0 0 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 30 1 0 0 0 1 3 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
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 1 1
52 0 1 36 0 1 0 0 4 3 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 1 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
52 0 1 43 1 1 0 0 4 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
27 1 0 20 0 1 0 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
0 0 . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 1 24 1 1 0 1 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 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
52 0 0 22 1 1 0 0 1 2 0 0 0 0 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 20 1 0 1 0 1 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
52 1 0 21 1 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
45 1 1 18 1 0 0 0 5 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 . . . . . . .
4 1 0 18 1 1 0 0 1 4 0 0 0 0 . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 1 0 33 1 1 0 1 2 4 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
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 1 1
36 1 1 19 1 0 0 1 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 . . . . . . . . . . . . . . . .
52 0 1 21 0 1 0 1 1 5 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 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 21 1 0 0 1 1 4 0 1 0 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
8 1 1 21 1 1 0 1 4 3 0 0 0 1 1 1 1 1 . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
15 1 1 22 1 0 0 1 3 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 0 18 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 0 0 0 0 0
0 1 1 0 1 1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 1 1 1 1 1 1 1
19 1 0 18 1 0 0 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 0 24 1 1 0 1 2 4 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 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 1
12 1 1 22 1 1 1 1 2 4 0 0 0 0 1 1 0 0 0 0 0 0 . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . .
52 0 1 31 0 1 0 1 3 3 0 0 0 0 0 0 0 0 0 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 1 1 1 1 1 1 0 0 0 0 0 0
52 0 0 20 1 0 0 1 1 4 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 0 0 0 0 0
52 0 1 20 1 1 1 1 1 3 0 0 1 1 1 0 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 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 1 0 0 0 0
52 0 0 29 1 1 0 1 3 4 1 1 1 1 1 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 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
52 0 1 24 1 1 0 1 1 4 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 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 1 1 1 1 1
;

-------------
STAN Data Set
-------------

/* Data described in Ch. 5 of P. Allison, "Survival Analysis
   Using the SAS System: A Practical Guide."*/


data stan;
input dob mmddyy9. doa mmddyy9. dot mmddyy9. dls mmddyy9.
   id age dead dur surg trans wtime m1 m2 m3 reject;
surv1=dls-doa;
surv2=dls-dot;
wait=dot-doa;
agetrans=(dot-dob)/365.25;
ageaccpt=(doa-dob)/365.25;
if wait = . then wait = 10000;
agels=(dls-dob)/365.25;
cards;
01/10/37 11/15/67     .    01/03/68 1 30 1 50 0 0 . . . . .
03/02/16 01/02/68     .    01/07/68 2 51 1 6 0 0 . . . . .
09/19/13 01/06/68 01/06/68 01/21/68 3 54 1 16 0 1 1 2 0 1.110 0
12/23/27 03/28/68 05/02/68 05/05/68 4 40 1 39 0 1 36 3 0 1.660 0
07/28/47 05/10/68     .    05/27/68 5 20 1 18 0 0 . . . . .
11/08/13 06/13/68     .    06/15/68 6 54 1 3 0 0 . . . . .
08/29/17 07/12/68 08/31/68 05/17/70 7 50 1 675 0 1 51 4 0 1.320 1
03/27/23 08/01/68     .    09/09/68 8 45 1 40 0 0 . . . . .
06/11/21 08/09/68     .    11/01/68 9 47 1 85 0 0 . . . . .
02/09/26 08/11/68 08/22/68 10/07/68 10 42 1 58 0 1 12 2 0 0.610 1
08/22/20 08/15/68 09/09/68 01/14/69 11 47 1 153 0 1 26 1 0 0.360 0
07/09/15 09/17/68     .    09/24/68 12 53 1 8 0 0 . . . . .
02/22/14 09/19/68 10/05/68 12/08/68 13 54 1 81 0 1 17 3 0 1.890 1
09/16/14 09/20/68 10/26/68 07/07/72 14 53 1 1386 0 1 37 1 0 0.870 1
12/04/14 09/27/68     .    09/27/68 15 53 1 1 1 0 . . . . .
05/16/19 10/26/68 11/22/68 08/29/69 16 49 1 308 0 1 28 2 0 1.120 1
06/29/48 10/28/68     .    12/02/68 17 20 1 36 0 0 . . . . .
12/27/11 11/01/68 11/20/68 12/13/68 18 56 1 43 0 1 20 3 0 2.050 0
10/04/09 11/18/68     .    12/24/68 19 59 1 37 0 0 . . . . .
10/19/13 01/29/69 02/15/69 02/25/69 20 55 1 28 0 1 18 3 1 2.760 1
09/29/25 02/01/69 02/08/69 11/29/71 21 43 1 1032 0 1 8 2 0 1.130 1
06/05/26 03/18/69 03/29/69 05/07/69 22 42 1 51 0 1 12 3 0 1.380 1
12/02/10 04/11/69 04/13/69 04/13/71 23 58 1 733 0 1 3 3 0 0.960 1
07/07/17 04/25/69 07/16/69 11/29/69 24 51 1 219 0 1 83 3 1 1.620 1
02/06/36 04/28/69 05/22/69 04/01/74 25 33 0 1799 0 1 25 2 0 1.060 0
10/18/38 05/01/69     .    03/01/73 26 30 0 1400 0 0 . . . . .
07/21/60 05/04/69     .    01/21/70 27 8 1 263 0 0 . . . . .
05/30/15 06/07/69 08/16/69 08/17/69 28 53 1 72 0 1 71 2 0 0.470 0
02/06/19 07/14/69     .    08/17/69 29 50 1 35 0 0 . . . . .
09/20/24 08/19/69 09/03/69 12/18/71 30 44 1 852 0 1 16 4 0 1.580 1
10/04/14 08/23/69     .    09/07/69 31 54 1 16 0 0 . . . . .
04/02/05 08/29/69 09/14/69 11/13/69 32 64 1 77 0 1 17 4 0 0.690 1
01/01/21 11/27/69 01/16/70 04/01/74 33 48 0 1586 0 1 51 3 0 0.910 0
05/24/29 12/12/69 01/03/70 04/01/74 34 40 0 1571 0 1 23 2 0 0.380 0
08/04/26 01/21/70     .    02/01/70 35 43 1 12 0 0 . . . . .
05/01/21 04/04/70 05/19/70 07/12/70 36 48 1 100 0 1 46 2 0 2.090 1
10/24/08 04/25/70 05/13/70 06/29/70 37 61 1 66 0 1 19 3 1 0.870 1
11/14/28 05/05/70 05/08/70 05/09/70 38 41 1 5 0 1 5 3 0 0.870 0
11/12/19 05/20/70 05/21/70 07/11/70 39 50 1 53 0 1 2 . . . .
11/30/21 05/25/70 07/04/70 04/01/74 40 48 0 1407 1 1 41 4 0 0.750 0
04/30/25 08/19/70 10/15/70 04/01/74 41 45 0 1321 1 1 58 2 0 0.980 0
03/13/34 08/21/70     .    08/23/70 42 36 1 3 0 0 . . . . .
06/01/27 10/22/70     .    10/23/70 43 43 1 2 1 0 . . . . .
05/02/28 11/30/70     .    01/08/71 44 42 1 40 1 0 . . . . .
10/30/34 01/05/71 01/05/71 02/18/71 45 36 1 45 0 1 1 1 0 0.000 0
06/01/22 01/10/71 01/11/71 10/01/73 46 48 1 995 1 1 2 2 0 0.810 1
12/28/23 02/02/71 02/22/71 04/14/71 47 47 1 72 0 1 21 3 0 1.380 1
01/23/15 02/05/71     .    02/13/71 48 56 1 9 0 0 . . . . .
06/21/34 02/15/71 03/22/71 04/01/74 49 36 0 1141 1 1 36 4 0 1.350 0
03/28/25 02/15/71 05/08/71 10/21/73 50 45 1 979 1 1 83 . . . .
06/29/22 03/24/71 04/24/71 01/02/72 51 48 1 285 0 1 32 4 1 1.080 1
01/24/30 04/25/71     .    08/04/71 52 41 1 102 0 0 . . . . .
02/27/24 07/02/71 08/11/71 01/05/72 53 47 1 188 0 1 41 . . . .
09/16/23 07/02/71     .    07/04/71 54 47 1 3 0 0 . . . . .
02/24/19 08/09/71 08/18/71 10/08/71 55 52 1 61 0 1 10 2 0 1.510 1
12/05/32 09/03/71 11/08/71 04/01/74 56 38 0 941 0 1 67 4 0 0.980 0
06/08/30 09/13/71     .    02/08/72 57 41 1 149 0 0 . . . . .
09/17/23 09/23/71 10/13/71 08/30/72 58 47 1 342 1 1 21 2 1 1.820 1
05/12/30 09/29/71 12/15/71 04/01/74 59 41 0 915 1 1 78 2 0 0.190 0
10/29/22 11/18/71 11/20/71 01/24/72 60 49 1 68 0 1 3 3 0 0.660 1
05/12/19 12/04/71     .    12/05/71 61 52 1 2 0 0 . . . . .
08/01/32 12/09/71     .    02/15/72 62 39 1 69 0 0 . . . . .
04/15/39 12/12/71 01/07/72 04/01/74 63 32 0 841 0 1 27 3 1 1.930 0
04/09/23 02/01/72 03/04/72 09/06/73 64 48 1 583 1 1 32 1 0 0.120 0
11/19/20 03/06/72 03/17/72 05/22/72 65 51 1 78 0 1 12 2 0 1.120 1
01/02/19 03/20/72     .    04/20/72 66 53 1 32 0 0 . . . . .
09/03/52 03/23/72 05/18/72 01/01/73 67 19 1 285 0 1 57 3 0 1.020 0
01/10/27 04/07/72 04/09/72 06/13/72 68 45 1 68 0 1 3 3 1 1.680 1
06/05/24 06/01/72 06/10/72 04/01/74 69 47 0 670 0 1 10 2 0 1.200 0
06/17/19 06/17/72 06/21/72 07/16/72 70 52 1 30 0 1 5 3 1 1.680 1
02/22/25 07/21/72 08/20/72 04/01/74 71 47 0 620 0 1 31 3 0 0.970 0
11/22/45 08/14/72 08/17/72 04/01/74 72 26 0 596 0 1 4 3 1 1.460 0
05/13/16 09/11/72 10/07/72 12/09/72 73 56 1 90 0 1 27 3 1 2.160 1
07/20/43 09/18/72 09/22/72 10/04/72 74 29 1 17 0 1 5 1 0 0.610 0
07/25/20 09/29/72     .    09/30/72 75 52 1 2 0 0 . . . . .
09/03/20 10/04/72 11/18/72 04/01/74 76 52 0 545 1 1 46 3 1 1.700 0
08/27/31 10/06/72     .    10/26/72 77 41 1 21 0 0 . . . . .
02/20/24 11/03/72 05/31/73 04/01/74 78 48 0 515 0 1 210 3 0 0.810 0
02/18/19 11/30/72 02/04/73 03/05/73 79 53 1 96 0 1 67 2 0 1.080 1
06/27/26 12/06/72 12/31/72 04/01/74 80 46 0 482 1 1 26 3 0 1.410 0
02/21/20 01/12/73 01/17/73 04/01/74 81 52 0 445 0 1 6 4 1 1.940 0
08/19/42 11/01/71     .    01/01/73 82 29 0 427 0 0 . . . . .
10/04/19 01/24/73 02/24/73 04/13/73 83 53 1 80 0 1 32 4 0 3.050 0
05/13/30 01/30/73 03/07/73 12/29/73 84 42 1 334 0 1 37 4 0 0.600 1
02/13/25 02/06/73     .    02/10/73 85 47 1 5 0 0 . . . . .
03/30/24 03/01/73 03/08/73 04/01/74 86 48 0 397 0 1 8 3 1 1.440 0
12/19/26 03/21/73 05/19/73 07/08/73 87 46 1 110 0 1 60 2 0 2.250 1
11/16/18 03/28/73 04/27/73 04/01/74 88 54 0 370 0 1 31 3 0 0.680 0
03/19/22 04/05/73 08/21/73 10/28/73 89 51 1 207 0 1 139 4 1 1.330 1
03/25/21 04/06/73 09/12/73 10/08/73 90 52 1 186 1 1 160 3 1 0.820 0
09/08/25 04/13/73     .    03/18/74 91 47 1 340 0 0 . . . . .
05/03/28 04/27/73 03/02/74 04/01/74 92 44 0 340 0 1 310 1 0 0.160 0
10/10/25 07/11/73 08/07/73 04/01/74 93 47 0 265 0 1 28 2 0 0.330 0
11/11/29 09/14/73 09/17/73 02/25/74 94 43 1 165 1 1 4 3 0 1.200 1
06/11/33 09/22/73 09/23/73 10/07/73 95 40 1 16 0 1 2 . . . .
02/09/47 10/04/73 10/16/73 04/01/74 96 26 0 180 0 1 13 2 0 0.460 0
04/11/50 11/22/73 12/12/73 04/01/74 97 23 0 131 0 1 21 3 1 1.780 0
04/28/45 12/14/73 03/19/74 04/01/74 98 28 0 109 0 1 96 4 1 0.770 0
02/24/24 12/25/73     .    01/14/74 99 49 1 21 0 0 . . . . .
01/31/39 02/22/74 03/31/74 04/01/74 100 35 0 39 1 1 38 3 0 0.670 0
08/25/24 03/02/74     .    04/01/74 101 49 0 31 0 0 . . . . .
10/30/33 03/22/74     .    04/01/74 102 40 0 11 0 0 . . . . .
05/20/28 09/13/67     .    09/18/67 103 39 1 6 0 0 . . . . .
;



---------------
BREAST Data Set
---------------

/* This data set is displayed in Output 5.4 of P.D. Allison, "Survival
   Analysis Using the SAS System: A Practical Guide."                  */


data breast;
input surv dead x;
cards;
5       1       1
8       1       1
10      1       1
13      1       1
18      1       1
23      1       0
24      1       1
25      1       1
26      1       1
31      1       1
35      1       1
40      1       1
41      1       1
47      1       0
48      1       1
50      1       1
59      1       1
61      1       1
68      1       1
69      1       0
70      0       0
71      0       0
71      1       1
76      0       1
100     0       0
101     0       0
105     0       1
107     0       1
109     0       1
113     1       1
116     0       1
118     1       1
143     1       1
148     1       0
154     0       1
162     0       1
181     1       0
188     0       1
198     0       0
208     0       0
212     0       0
212     0       1
217     0       1
224     0       0
225     0       1
;








---------------
JOBDUR Data Set
---------------

/* The data set is analyzed in Output 5.9 of P.D. Allison, "Survival
    Analysis Using the SAS System: A Practical Guide."               */


data jobdur;
input dur event ed prestige salary;
cards;
1 1 7 3 19
4 1 14 62 17
5 0 16 70 18
2 1 12 43 135
3 1 9 18 12
1 1 11 31 12
1 1 13 26 6
1 1 10 1 4
2 1 12 28 17
3 1 7 25 4
3 1 13 45 15
3 1 17 65 10
3 1 11 37 13
1 1 7 10 9
5 0 11 67 10
2 1 13 45 17
2 2 11 78 8
5 0 11 42 18
2 1 12 24 30
2 1 12 30 9
1 1 10 6 6
1 1 12 23 26
2 1 9 18 8
2 1 14 36 17
3 1 12 42 12
5 1 15 72 6
3 1 12 48 14
2 1 13 52 12
3 1 12 49 105
1 1 9 9 22
1 1 14 37 4
2 1 12 16 7
2 2 10 64 89
1 2 9 73 19
1 2 11 93 16
3 1 8 37 15
4 2 15 100 26
4 1 10 39 32
5 0 17 88 19
1 2 13 50 16
2 1 13 28 15
5 1 18 81 5
5 1 13 51 22
3 1 12 27 17
5 0 17 84 33
1 1 7 23 21
1 2 16 84 26
3 2 17 100 18
4 1 18 46 27
2 1 9 41 7
5 0 18 80 14
2 1 13 30 13
2 1 6 25 6
1 1 15 34 9
3 1 13 40 18
1 2 12 80 38
3 1 13 46 30
3 2 10 63 8
1 1 13 10 7
4 1 17 55 40
3 1 14 50 12
2 1 15 52 7
5 0 14 74 9
1 2 13 85 21
1 1 7 12 16
1 1 16 38 5
5 0 13 67 11
3 1 9 45 15
1 1 11 21 8
5 0 16 68 29
1 2 13 98 35
5 1 12 44 11
5 0 12 52 29
5 0 12 51 53
2 1 9 1 31
2 2 8 36 10
2 1 11 18 8
1 1 8 10 5
1 1 11 10 3
2 1 13 34 14
5 0 15 53 13
1 1 9 42 9
3 1 12 54 15
4 1 10 45 13
5 0 14 63 79
3 2 8 54 27
5 0 15 49 64
4 1 11 50 23
2 1 13 26 9
4 1 17 69 10
3 2 13 90 19
3 1 12 47 14
5 0 14 40 106
5 0 13 71 7
4 1 12 47 51
1 1 11 25 21
5 0 10 52 15
1 1 9 22 19
1 1 16 40 13
1 1 10 17 37
;




-------------
ALCO Data Set
-------------

/* Data set ALCO is displayed in Output 5.14 of P.D. Allison, "Survival
   Analysis Using the SAS System: A Practical Guide."                 */


data alco;
   input surv dead time2-time10 pt1-pt10;
   cards;
 90 0  7 20 26 35 44 50 56 80 83 23.9 20.8 23.6 23.6 24.0 22.5 24.6
25.1 29.4 27.9
 80 0  6 36 42 54 67 78  .  .  . 29.6 15.1 15.4 16.3 13.9 14.6 16.1
.    .    .
 36 0 17 28 34  .  .  .  .  .  . 25.9 24.4 24.8 24.3   .    .    .
.    .    .
 68 0 15 20 26 32 51  .  .  .  . 26.8 27.9 26.5 26.5 26.8 26.6   .
.    .    .
 62 0 22 40 46  .  .  .  .  .  . 23.0 25.2 27.1 27.8   .    .    .
.    .    .
 47 0  5 12 24 35 46  .  .  .  . 25.8 26.0 25.2 24.9 26.3 26.6   .
.    .    .
 84 0  8 27 31 43 76  .  .  .  . 14.2 11.5 12.9 12.6 12.5 18.6   .
.    .    .
 57 0  6 21 27 34 39 45 51  .  . 27.6 27.5 28.0 27.8 29.1 28.2 28.3
28.4   .    .
  7 0  4  7  .  .  .  .  .  .  . 25.0 25.1 24.7   .    .    .    .
.    .    .
 49 0 16  .  .  .  .  .  .  .  . 25.5 27.4   .    .    .    .    .
.    .    .
 55 0  3  9 15 21 33 42 49  .  . 14.8 16.7 16.9 17.7 13.8 13.8 13.7
14.2   .    .
 43 0  6 11 18 24 42  .  .  .  . 20.6 19.9 20.3 20.2 19.7 27.1   .
.    .    .
 42 0  6 12 18 23 29 35  .  .  . 27.6 27.0 28.1 28.8 29.0 28.4 28.8
.    .    .
 11 0  9  .  .  .  .  .  .  .  . 25.3 27.8   .    .    .    .    .
.    .    .
 36 1 16 22 28  .  .  .  .  .  . 22.5 22.3 25.2 26.4   .    .    .
.    .    .
 36 1  9 26 32  .  .  .  .  .  . 26.9 26.9 24.2 26.2   .    .    .
.    .    .
  2 1  .  .  .  .  .  .  .  .  . 19.2   .    .    .    .    .    .
.    .    .
 23 1  7 13  .  .  .  .  .  .  . 21.8 20.3 23.8   .    .    .    .
.    .    .
 10 1  6  .  .  .  .  .  .  .  . 21.6 22.3   .    .    .    .    .
.    .    .
 29 1 21 27  .  .  .  .  .  .  . 18.7 20.2 22.5   .    .    .    .
.    .    .
 16 1  6 12  .  .  .  .  .  .  . 28.4 28.7 28.7   .    .    .    .
.    .    .
 15 1  7 12  .  .  .  .  .  .  . 17.8 17.7 17.4   .    .    .    .
.    .    .
  5 1  3  .  .  .  .  .  .  .  . 20.7 22.6   .    .    .    .    .
.    .    .
 15 1  6  .  .  .  .  .  .  .  . 28.0 28.8   .    .    .    .    .
.    .    .
  1 1  .  .  .  .  .  .  .  .  . 31.6   .    .    .    .    .    .
.    .    .
 13 1  4 10  .  .  .  .  .  .  . 26.0 22.7 25.4   .    .    .    .
.    .    .
 39 1 22 35  .  .  .  .  .  .  . 25.5 29.0 29.2   .    .    .    .
.    .    .
 20 1 12  .  .  .  .  .  .  .  . 21.3 21.0   .    .    .    .    .
.    .    .
 45 1 18 24 38  .  .  .  .  .  . 23.9 28.7 29.5 30.2   .    .    .
.    .    .
;




----------------
LEADERS Data Set
----------------

/* Data described in Chapter 6 of P. D. Allison, "SAS System for
   Survival Analysis: A Practical Guide."                         */


data leaders;
input years lost manner start military age conflict loginc growth
  pop land literacy region;
cards;
3 2 1 975 0 53 1 5.7990926545 -5.7 8 1247 20 1
8 0 0 979 0 37 1 5.7990926545 -5.7 8 1247 20 1
3 3 0 960 0 44 1 4.7004803658 1 4 112 11 1
1 3 0 964 0 51 1 4.7004803658 1 4 112 11 1
1 3 1 965 1 56 1 4.7004803658 1 4 112 11 1
0 3 1 967 1 37 1 4.7004803658 1 4 112 11 1
1 3 1 968 0 50 1 4.7004803658 1 4 112 11 1
15 0 1 972 1 39 1 4.7004803658 1 4 112 11 1
13 2 0 966 0 45 0 5.4380793089 8.5 1.2 600 30 1
7 0 0 980 0 55 0 5.4380793089 8.5 1.2 600 30 1
3 3 0 962 0 50 1 4.3820266347 2.1 5.2 28 30 1
0 3 1 966 0 19 1 4.3820266347 2.1 5.2 28 30 1
9 3 1 966 1 26 1 4.3820266347 2.1 5.2 28 30 1
10 3 1 976 1 30 1 4.3820266347 2.1 5.2 28 30 1
0 0 1 987 1 38 1 4.3820266347 2.1 5.2 28 30 1
22 1 0 960 0 36 1 5.5214609179 2.7 11 475 65 1
5 0 0 982 0 49 1 5.5214609179 2.7 11 475 65 1
12 0 0 975 0 51 1 5.0751738152 2.4 0.4 4 37 1
5 3 0 960 0 30 0 5.0751738152 0.1 2.7 623 20 1
13 3 1 965 1 44 0 5.0751738152 0.1 2.7 623 20 1
6 0 1 981 1 45 0 5.0751738152 0.1 2.7 623 20 1
15 3 0 960 0 42 1 4.3820266347 -5.8 5 1284 17 1
3 3 1 975 1 43 1 4.3820266347 -5.8 5 1284 17 1
3 3 0 979 0 35 1 4.3820266347 -5.8 5 1284 17 1
5 0 1 982 1 40 1 4.3820266347 -5.8 5 1284 17 1
2 3 0 972 0 53 0 5.1929568509 -0.6 0.43 2.1 15 1
0 1 1 975 0 . 0 5.1929568509 -0.6 0.43 2.1 15 1
2 3 0 976 0 38 0 5.1929568509 -0.6 0.43 2.1 15 1
3 1 0 960 0 43 1 5.8289456176 3.5 2.1 342 80 1
4 3 1 963 0 42 1 5.8289456176 3.5 2.1 342 80 1
8 3 1 968 1 30 1 5.8289456176 3.5 2.1 342 80 1
1 3 1 977 1 38 1 5.8289456176 3.5 2.1 342 80 1
7 0 0 979 1 36 1 5.8289456176 3.5 2.1 342 80 1
9 0 0 977 0 61 1 7.6778635007 -3.6 0.32 22 20 1
10 3 1 968 0 44 1 5.7990926545 -1.3 0.35 28 55 1
8 0 1 979 1 37 1 5.7990926545 -1.3 0.35 28 55 1
2 3 1 974 1 53 1 4.4998096703 0.5 48 1221 35 1
10 0 1 977 1 42 1 4.4998096703 0.5 48 1221 35 1
7 2 0 960 0 58 0 7.1777824162 3.2 1 267 65 1
19 0 1 967 0 32 0 7.1777824162 3.2 1 267 65 1
22 0 0 965 0 41 0 4.8675344505 1.4 0.8 11 12 1
3 3 1 966 1 51 1 5.7037824747 -2.1 14 238 30 1
2 3 0 969 0 56 1 5.7037824747 -2.1 14 238 30 1
1 3 0 970 0 64 1 5.7037824747 -2.1 14 238 30 1
6 3 1 972 1 41 1 5.7037824747 -2.1 14 238 30 1
0 3 1 978 1 41 1 5.7037824747 -2.1 14 238 30 1
2 3 0 979 0 45 1 5.7037824747 -2.1 14 238 30 1
5 0 1 981 1 34 1 5.7037824747 -2.1 14 238 30 1
0 3 0 984 1 61 1 4.7004803658 1.1 7 245 20 1
3 0 1 984 1 61 1 4.7004803658 1.1 7 245 20 1
6 3 1 974 0 43 1 4.9416424226 2.4 1 36 9 1
6 0 1 980 1 41 1 4.9416424226 2.4 1 36 9 1
27 0 0 960 0 55 0 5.9401712527 1 11 322 24 1
14 2 0 963 0 74 1 5.1357984371 2.3 23 583 47 1
9 0 0 978 0 54 1 5.1357984371 2.3 23 583 47 1
19 3 0 966 0 52 0 4.605170186 6.3 1.6 30 65 1
1 0 1 986 1 . 0 4.605170186 6.3 1.6 30 65 1
8 3 0 971 0 58 1 5.7365722975 0.8 2.5 111 20 1
7 0 1 980 1 28 1 5.7365722975 0.8 2.5 111 20 1
11 3 0 960 0 48 1 5.0106352941 -1.2 11 587 53 1
2 3 0 972 1 62 1 5.0106352941 -1.2 11 587 53 1
12 0 0 975 1 39 1 5.0106352941 -1.2 11 587 53 1
23 0 0 964 0 58 1 4.7004803658 2.2 7.7 118 25 1
8 3 0 960 0 45 0 4.248495242 1.2 8.7 1240 10 1
19 0 1 968 1 32 0 4.248495242 1.2 8.7 1240 10 1
17 3 0 960 0 36 1 5.2983173665 0.3 2 1030 17 1
0 3 1 978 1 42 1 5.2983173665 0.3 2 1030 17 1
0 3 1 979 1 36 1 5.2983173665 0.3 2 1030 17 1
4 3 1 980 1 40 1 5.2983173665 0.3 2 1030 17 1
2 0 1 984 1 39 1 5.2983173665 0.3 2 1030 17 1
14 1 0 968 0 68 1 6.0161571597 2.8 1 1.9 79 1
5 0 0 982 0 52 1 6.0161571597 2.8 1 1.9 79 1
11 2 1 975 1 42 1 5.1357984371 0.1 15 801 14 1
0 0 0 986 1 47 1 5.1357984371 0.1 15 801 14 1
13 3 0 960 0 44 0 4.605170186 -1.2 7 1267 8 1
13 0 1 974 1 43 0 4.605170186 -1.2 7 1267 8 1
5 3 0 960 0 48 1 5.3471075307 3.2 112 923 30 1
0 3 1 966 1 42 1 5.3471075307 3.2 112 923 30 1
9 3 1 966 1 32 1 5.3471075307 3.2 112 923 30 1
0 3 1 975 1 38 1 5.3471075307 3.2 112 923 30 1
3 1 1 976 1 39 1 5.3471075307 3.2 112 923 30 1
4 3 0 979 0 54 1 5.3471075307 3.2 112 923 30 1
1 3 1 983 1 41 1 5.3471075307 3.2 112 923 30 1
2 0 1 985 1 44 1 5.3471075307 3.2 112 923 30 1
11 3 0 962 0 38 1 4.248495242 2.3 7 26 37 1
14 0 1 973 1 33 1 4.248495242 2.3 7 26 37 1
12 0 1 975 1 38 0 6.1944053911 -1.3 0.11 1 50 1
20 1 0 960 0 54 1 5.5214609179 -0.5 7.3 196 10 1
6 0 0 981 0 46 1 5.5214609179 -0.5 7.3 196 10 1
0 3 0 976 0 37 0 6.4134589572 3.4 0.07 0.5 60 1
10 0 1 977 0 42 0 6.4134589572 3.4 0.07 0.5 60 1
3 2 0 961 0 65 1 5.0751738152 1.1 4 72 15 1
2 1 0 964 0 54 1 5.0751738152 1.1 4 72 15 1
0 3 1 967 1 45 1 5.0751738152 1.1 4 72 15 1
1 3 1 967 1 36 1 5.0751738152 1.1 4 72 15 1
17 1 0 968 0 63 1 5.0751738152 1.1 4 72 15 1
2 0 0 985 1 48 1 5.0751738152 1.1 4 72 15 1
3 1 0 960 0 41 0 4.3820266347 -0.8 8 638 60 1
3 1 0 964 0 40 0 4.3820266347 -0.8 8 638 60 1
18 0 1 969 1 48 0 4.3820266347 -0.8 8 638 60 1
12 1 0 966 0 46 1 6.9565454432 1.6 35 1221 65 1
9 0 0 978 0 62 1 6.9565454432 1.6 35 1221 65 1
14 2 0 968 0 69 1 5.7990926545 2.6 0.7 17 65 1
2 3 1 961 0 37 1 5.7990926545 2.6 0.7 17 65 1
1 0 0 986 0 18 1 5.7990926545 2.6 0.7 17 65 1
24 1 0 961 0 39 0 4.8675344505 0.9 24 945 79 1
2 0 0 985 0 60 0 4.8675344505 0.9 24 945 79 1
2 3 0 960 0 58 1 5.1929568509 1.1 3.3 57 18 1
3 3 1 963 0 50 1 5.1929568509 1.1 3.3 57 18 1
20 0 1 967 1 30 1 5.1929568509 1.1 3.3 57 18 1
8 3 0 962 0 37 1 5.0106352941 -4.4 16 236 52 1
8 3 1 971 1 46 1 5.0106352941 -4.4 16 236 52 1
0 3 1 979 0 67 1 5.0106352941 -4.4 16 236 52 1
0 3 0 979 0 59 1 5.0106352941 -4.4 16 236 52 1
0 3 1 985 1 72 1 5.0106352941 -4.4 16 236 52 1
0 0 1 986 1 43 1 5.0106352941 -4.4 16 236 52 1
5 3 0 960 0 39 1 4.248495242 1.4 8.5 274 7 1
14 3 1 966 1 50 1 4.248495242 1.4 8.5 274 7 1
1 3 1 980 1 48 1 4.248495242 1.4 8.5 274 7 1
0 3 1 982 1 44 1 4.248495242 1.4 8.5 274 7 1
4 3 1 983 1 34 1 4.248495242 1.4 8.5 274 7 1
0 0 1 987 1 38 1 4.248495242 1.4 8.5 274 7 1
5 3 0 960 0 43 1 4.248495242 -1.3 33 2345 40 1
1 3 0 960 0 35 1 4.248495242 -1.3 33 2345 40 1
0 1 1 960 1 30 1 4.248495242 -1.3 33 2345 40 1
0 3 1 960 0 42 1 4.248495242 -1.3 33 2345 40 1
2 3 1 961 0 40 1 4.248495242 -1.3 33 2345 40 1
1 3 0 960 0 35 1 4.248495242 -1.3 33 2345 40 1
1 3 1 964 0 45 1 4.248495242 -1.3 33 2345 40 1
0 3 0 965 0 39 1 4.248495242 -1.3 33 2345 40 1
23 0 0 964 0 40 1 6.0637852087 -1.3 7.5 752 54 1
0 3 0 963 0 33 0 4.8675344505 0.9 0.01 2.4 79 1
0 1 1 964 0 59 0 4.8675344505 0.9 0.01 2.4 79 1
7 0 0 980 0 56 1 6.0637852087 1.5 9.7 391 50 1
2 3 0 962 0 43 1 6.3456363608 3.6 24 2381 52 0
12 2 1 965 1 40 1 6.3456363608 3.6 24 2381 52 0
8 0 0 979 1 50 1 6.3456363608 3.6 24 2381 52 0
16 0 0 971 0 38 1 7.668561108 2.1 0.5 0.6 40 0
11 3 0 970 1 52 1 5.5214609179 4.2 53 1001 45 0
6 0 0 981 1 53 1 5.5214609179 4.2 53 1001 45 0
8 0 1 979 0 79 1 6.7684932116 4.2 51 1648 48 0
3 2 1 963 1 49 1 6.7452363495 7.6 18 435 55 0
2 3 0 966 0 50 1 6.7452363495 7.6 18 435 55 0
11 1 1 968 1 56 1 6.7452363495 7.6 18 435 55 0
8 0 0 979 1 42 1 6.7452363495 7.6 18 435 55 0
6 2 0 963 0 68 1 8.0096953577 2.9 4.3 20 80 0
5 1 0 969 0 71 1 8.0096953577 2.9 4.3 20 80 0
3 1 0 974 0 52 1 8.0096953577 2.9 4.3 20 80 0
0 1 0 979 0 56 1 8.0096953577 2.9 4.3 20 80 0
4 1 0 979 0 66 1 8.0096953577 2.9 4.3 20 80 0
0 1 0 983 0 68 1 8.0096953577 2.9 4.3 20 80 0
4 2 0 961 0 66 0 9.3968199389 0.2 2 18 71 0
12 2 0 965 0 51 0 9.3968199389 0.2 2 18 71 0
10 0 0 977 0 47 0 9.3968199389 0.2 2 18 71 0
6 1 0 964 0 53 1 6.8458798753 -6 2.7 10 75 0
6 1 0 970 0 60 1 6.8458798753 -6 2.7 10 75 0
6 1 0 976 0 52 1 6.8458798753 -6 2.7 10 75 0
0 3 0 982 0 34 1 6.8458798753 -6 2.7 10 75 0
5 0 0 982 0 40 1 6.8458798753 -6 2.7 10 75 0
18 0 1 969 1 27 0 8.1690531499 -0.9 4 1760 55 0
26 0 0 961 0 32 1 5.7683209958 2.9 25 447 28 0
17 0 0 970 0 30 1 6.7334018918 6.5 1.3 212 20 0
1 3 0 971 0 54 0 9.3413686344 -7 0.3 11 40 0
15 0 0 972 0 35 0 9.3413686344 -7 0.3 11 40 0
11 3 0 964 0 19 0 7.383989458 6.7 15 2149 52 0
7 2 0 975 0 61 0 7.383989458 6.7 15 2149 52 0
5 0 0 982 0 32 0 7.383989458 6.7 15 2149 52 0
1 1 0 965 0 57 1 4.8675344505 1.3 24 2506 20 0
0 1 0 966 0 30 1 4.8675344505 1.3 24 2506 20 0
16 3 1 969 1 39 1 4.8675344505 1.3 24 2506 20 0
0 3 1 961 0 47 1 5.9914645471 4.9 12 185 47 0
0 3 1 961 1 . 1 5.9914645471 4.9 12 185 47 0
1 3 0 961 0 55 1 5.9914645471 4.9 12 185 47 0
0 1 1 962 1 . 1 5.9914645471 4.9 12 185 47 0
0 3 1 963 1 37 1 5.9914645471 4.9 12 185 47 0
3 3 1 963 1 52 1 5.9914645471 4.9 12 185 47 0
4 3 0 966 1 37 1 5.9914645471 4.9 12 185 47 0
17 0 1 970 1 42 1 5.9914645471 4.9 12 185 47 0
0 0 1 987 1 51 1 6.1312264895 5 8 164 62 0
1 1 1 960 1 65 0 6.3969296552 3 54 781 70 0
6 3 0 965 0 41 0 6.3969296552 3 54 781 70 0
2 1 1 971 1 71 0 6.3969296552 3 54 781 70 0
0 1 0 974 0 48 0 6.3969296552 3 54 781 70 0
0 1 0 974 0 70 0 6.3969296552 3 54 781 70 0
4 1 1 979 1 61 0 6.3969296552 3 54 781 70 0
4 0 0 983 0 56 0 6.3969296552 3 54 781 70 0
1 3 0 961 0 33 1 5.5214609179 5.7 6.7 195 15 0
5 3 1 962 1 45 1 5.5214609179 5.7 6.7 195 15 0
7 3 0 967 0 32 1 5.5214609179 5.7 6.7 195 15 0
3 3 1 974 1 29 1 5.5214609179 5.7 6.7 195 15 0
1 3 0 977 1 . 1 5.5214609179 5.7 6.7 195 15 0
9 0 1 978 1 36 1 5.5214609179 5.7 6.7 195 15 0
2 3 0 967 0 . 0 5.6347896032 6 2.4 333 25 0
7 3 0 971 0 37 0 5.6347896032 6 2.4 333 25 0
0 1 1 978 0 . 0 5.6347896032 6 2.4 333 25 0
2 1 0 978 0 41 0 5.6347896032 6 2.4 333 25 0
6 3 0 980 0 41 0 5.6347896032 6 2.4 333 25 0
1 0 1 986 0 47 0 5.6347896032 6 2.4 333 25 0
16 0 0 971 0 55 0 9.5460980677 -1.2 2 84 68 0
10 3 1 963 0 43 1 4.4998096703 0.5 14 648 12 2
0 3 1 978 0 61 1 4.4998096703 0.5 14 648 12 2
0 3 0 979 0 50 1 4.4998096703 0.5 14 648 12 2
7 3 1 979 0 50 1 4.4998096703 0.5 14 648 12 2
1 0 1 986 1 39 1 4.4998096703 0.5 14 648 12 2
3 3 0 971 0 51 1 4.3820266347 0.5 109 144 29 2
0 3 1 975 0 56 1 4.3820266347 0.5 109 144 29 2
0 3 1 975 1 . 1 4.3820266347 0.5 109 144 29 2
2 3 1 975 0 59 1 4.3820266347 0.5 109 144 29 2
3 3 1 978 1 42 1 4.3820266347 0.5 109 144 29 2
0 3 0 981 0 75 1 4.3820266347 0.5 109 144 29 2
5 0 1 982 1 52 1 4.3820266347 0.5 109 144 29 2
15 0 0 972 0 17 0 4.248495242 0.1 1.5 47 5 2
20 0 0 967 0 22 0 9.3413686344 7.4 0.3 6 45 2
1 1 0 976 0 56 1 4.7874917428 4.4 1088 9596 75 2
9 0 0 978 0 74 1 4.7874917428 4.4 1088 9596 75 2
17 1 0 970 0 50 1 6.4769723629 3.4 0.74 18 80 2
0 3 0 987 0 52 1 6.4769723629 3.4 0.74 18 80 2
0 1 1 987 1 38 1 6.4769723629 3.4 0.74 18 80 2
0 3 0 987 0 69 1 6.4769723629 3.4 0.74 18 80 2
4 1 0 960 0 61 0 8.1969879273 4.8 122 372 99 2
8 1 0 964 0 63 0 8.1969879273 4.8 122 372 99 2
2 1 0 972 0 54 0 8.1969879273 4.8 122 372 99 2
2 1 0 974 0 67 0 8.1969879273 4.8 122 372 99 2
2 1 0 976 0 71 0 8.1969879273 4.8 122 372 99 2
2 2 0 978 0 68 0 8.1969879273 4.8 122 372 99 2
2 1 0 980 0 69 0 8.1969879273 4.8 122 372 99 2
5 1 0 982 0 65 0 8.1969879273 4.8 122 372 99 2
0 0 0 987 0 63 0 8.1969879273 4.8 122 372 99 2
1 2 0 964 0 60 1 4.7874917428 1.5 816 3288 36 2
11 1 0 966 0 49 1 4.7874917428 1.5 816 3288 36 2
2 1 0 977 0 81 1 4.7874917428 1.5 816 3288 36 2
0 1 0 979 0 77 1 4.7874917428 1.5 816 3288 36 2
3 0 0 984 0 40 1 4.7874917428 1.5 816 3288 36 2
21 0 1 966 1 46 1 4.8675344505 5 184 1919 62 2
5 3 1 970 1 57 0 4.248495242 -6.8 7 181 48 2
3 0 1 975 0 47 0 4.248495242 -6.8 7 181 48 2
8 0 1 979 1 44 0 4.248495242 -6.8 7 181 48 2
3 1 0 979 0 29 1 5.8141305318 1.3 0.01 0.7 90 2
0 1 0 982 0 . 1 5.8141305318 1.3 0.01 0.7 90 2
0 1 1 960 0 64 1 5.9914645471 6.7 43 98 95 2
0 1 0 960 0 63 1 5.9914645471 6.7 43 98 95 2
18 3 0 961 0 60 1 5.9914645471 6.7 43 98 95 2
0 1 0 979 0 60 1 5.9914645471 6.7 43 98 95 2
8 0 1 979 1 48 1 5.9914645471 6.7 43 98 95 2
1 1 1 960 0 48 1 4.0943445622 3.1 4 236 85 2
1 1 1 964 1 . 1 4.0943445622 3.1 4 236 85 2
12 0 1 975 0 55 1 4.0943445622 3.1 4 236 85 2
5 2 0 970 0 48 1 6.3456363608 4.5 16 330 65 2
5 1 0 976 0 51 1 6.3456363608 4.5 16 330 65 2
6 0 0 981 0 55 1 6.3456363608 4.5 16 330 65 2
13 3 1 965 0 39 0 4.7874917428 1.4 0.2 0.3 36 2
9 0 1 978 0 38 0 4.7874917428 1.4 0.2 0.3 36 2
3 0 0 984 0 58 1 6.7569323892 3.6 2 1565 80 2
8 1 0 968 0 45 0 5.8141305318 1.3 0.008 0.02 99 2
2 1 0 976 0 30 0 5.8141305318 1.3 0.008 0.02 99 2
0 1 0 978 0 55 0 5.8141305318 1.3 0.008 0.02 99 2
0 1 0 986 0 . 0 5.8141305318 1.3 0.008 0.02 99 2
15 0 0 972 0 37 1 4.4998096703 0.1 18 140 20 2
5 1 0 975 0 39 0 6.0161571597 0.9 3.6 461 32 2
2 1 0 980 0 40 0 6.0161571597 0.9 3.6 461 32 2
2 0 0 985 0 34 0 6.0161571597 0.9 3.6 461 32 2
2 1 0 969 1 52 1 4.7874917428 2.5 107 803 26 2
5 3 0 971 0 43 1 4.7874917428 2.5 107 803 26 2
10 0 1 977 1 53 1 4.7874917428 2.5 107 803 26 2
4 1 0 961 0 51 1 5.6347896032 2.9 63 300 88 2
20 1 0 965 0 48 1 5.6347896032 2.9 63 300 88 2
1 0 1 986 0 53 1 5.6347896032 2.9 63 300 88 2
24 0 0 963 0 40 0 7.5120712458 7.8 2.6 0.6 86 2
3 1 0 978 0 35 1 5.8141305318 1.3 0.3 28 60 2
3 1 0 981 0 38 1 5.8141305318 1.3 0.3 28 60 2
1 0 0 986 0 . 1 5.8141305318 1.3 0.3 28 60 2
5 1 0 960 0 54 1 4.7874917428 2.9 17 66 87 2
10 0 0 977 0 71 1 4.7874917428 2.9 17 66 87 2
12 0 0 975 1 65 1 6.492239835 4.6 20 35 94 2
10 1 0 963 1 52 1 5.598421959 4.3 54 514 82 2
1 1 0 973 0 66 1 5.598421959 4.3 54 514 82 2
0 1 0 975 0 70 1 5.598421959 4.3 54 514 82 2
1 1 0 975 0 64 1 5.598421959 4.3 54 514 82 2
1 3 1 976 1 . 1 5.598421959 4.3 54 514 82 2
2 3 1 977 1 60 1 5.598421959 4.3 54 514 82 2
7 0 0 980 1 60 1 5.598421959 4.3 54 514 82 2
22 0 0 965 0 47 0 5.8141305318 1.3 0.1 0.7 95 2
3 1 0 978 0 36 0 5.8141305318 1.3 0.08 0.03 45 2
6 1 0 981 0 . 0 5.8141305318 1.3 0.08 0.03 45 2
8 0 0 979 0 45 1 5.8141305318 1.3 0.08 0.03 45 2
17 2 0 969 0 61 1 4.248495242 -6 65 330 78 2
0 1 0 986 0 79 1 4.248495242 -6 65 330 78 2
1 0 0 986 0 73 1 4.248495242 -6 65 330 78 2
0 3 1 963 1 47 1 5.0751738152 -3 65 330 78 2
1 3 1 964 1 37 1 5.0751738152 -3 65 330 78 2
0 3 1 965 0 62 1 5.0751738152 -3 65 330 78 2
0 3 1 965 1 38 1 5.0751738152 -3 65 330 78 2
10 3 1 965 1 42 1 5.0751738152 -3 65 330 78 2
8 1 0 962 0 41 0 5.8579331545 1.3 0.18 2.9 90 2
3 1 0 970 0 48 0 5.8579331545 1.3 0.18 2.9 90 2
6 1 0 976 0 58 0 5.8579331545 1.3 0.18 2.9 90 2
0 1 0 982 0 . 0 5.8579331545 1.3 0.18 2.9 90 2
3 1 0 982 0 58 0 5.8579331545 1.3 0.18 2.9 90 2
6 0 0 981 0 70 0 6.6066501862 -0.4 0.08 0.44 90 3
1 1 0 962 0 52 0 7.4024515208 0.5 30.5 2767 94 3
3 3 0 963 0 63 0 7.4024515208 0.5 30.5 2767 94 3
4 3 1 966 1 52 0 7.4024515208 0.5 30.5 2767 94 3
0 3 1 970 1 50 0 7.4024515208 0.5 30.5 2767 94 3
2 1 1 971 1 53 0 7.4024515208 0.5 30.5 2767 94 3
0 1 0 973 0 57 0 7.4024515208 0.5 30.5 2767 94 3
2 3 0 974 0 43 0 7.4024515208 0.5 30.5 2767 94 3
4 1 1 976 1 51 0 7.4024515208 0.5 30.5 2767 94 3
1 1 0 980 1 55 0 7.4024515208 0.5 30.5 2767 94 3
0 1 0 981 1 54 0 7.4024515208 0.5 30.5 2767 94 3
1 1 0 982 0 54 0 7.4024515208 0.5 30.5 2767 94 3
4 0 0 983 0 58 0 7.4024515208 0.5 30.5 2767 94 3
20 0 0 967 0 36 0 8.1047034684 -1.8 0.23 14 95 3
10 1 0 966 0 46 0 6.907755279 3.8 0.25 0.43 99 3
9 2 0 976 0 44 0 6.907755279 3.8 0.25 0.43 99 3
1 1 0 985 0 53 0 6.907755279 3.8 0.25 0.43 99 3
0 0 0 987 0 50 0 6.907755279 3.8 0.25 0.43 99 3
3 1 0 981 0 62 1 6.6200732065 3.6 0.16 23 93 3
3 0 0 984 0 43 1 6.6200732065 3.6 0.16 23 93 3
0 3 1 964 1 42 1 5.4380793089 0.6 6.4 1099 63 3
0 3 1 965 1 47 1 5.4380793089 0.6 6.4 1099 63 3
0 3 0 969 0 44 1 5.4380793089 0.6 6.4 1099 63 3
0 3 1 970 1 49 1 5.4380793089 0.6 6.4 1099 63 3
7 3 1 971 1 45 1 5.4380793089 0.6 6.4 1099 63 3
0 3 1 978 1 47 1 5.4380793089 0.6 6.4 1099 63 3
0 1 1 979 1 54 1 5.4380793089 0.6 6.4 1099 63 3
0 3 0 979 0 68 1 5.4380793089 0.6 6.4 1099 63 3
0 1 1 979 1 53 1 5.4380793089 0.6 6.4 1099 63 3
0 1 0 979 0 58 1 5.4380793089 0.6 6.4 1099 63 3
1 3 1 980 0 50 1 5.4380793089 0.6 6.4 1099 63 3
0 1 1 981 1 48 1 5.4380793089 0.6 6.4 1099 63 3
0 3 0 982 1 45 1 5.4380793089 0.6 6.4 1099 63 3
0 1 0 961 0 44 1 6.6333184333 5 135.6 8512 76 3
2 3 0 961 0 43 1 6.6333184333 5 135.6 8512 76 3
3 1 1 964 1 64 1 6.6333184333 5 135.6 8512 76 3
2 3 0 967 1 65 1 6.6333184333 5 135.6 8512 76 3
4 1 1 969 1 64 1 6.6333184333 5 135.6 8512 76 3
5 1 0 974 1 66 1 6.6333184333 5 135.6 8512 76 3
6 2 0 979 1 60 1 6.6333184333 5 135.6 8512 76 3
2 0 0 985 0 54 1 6.6333184333 5 135.6 8512 76 3
6 1 0 964 0 53 0 6.579251212 -0.1 12.1 757 94 3
2 3 0 970 0 62 0 6.579251212 -0.1 12.1 757 94 3
14 0 1 973 1 58 0 6.579251212 -0.1 12.1 757 94 3
4 1 0 962 1 62 1 6.0867747269 3.2 28.4 1139 88 3
4 1 0 966 0 58 1 6.0867747269 3.2 28.4 1139 88 3
4 1 0 970 0 57 1 6.0867747269 3.2 28.4 1139 88 3
4 1 0 974 0 60 1 6.0867747269 3.2 28.4 1139 88 3
4 1 0 978 0 62 1 6.0867747269 3.2 28.4 1139 88 3
4 0 0 982 0 59 1 6.0867747269 3.2 28.4 1139 88 3
4 1 0 962 0 55 0 6.56526497 2.1 2.6 51 93 3
4 1 0 966 0 50 0 6.56526497 2.1 2.6 51 93 3
4 1 0 974 0 53 0 6.56526497 2.1 2.6 51 93 3
4 1 0 978 0 51 0 6.56526497 2.1 2.6 51 93 3
4 1 0 982 0 56 0 6.56526497 2.1 2.6 51 93 3
1 0 0 986 0 45 0 6.56526497 2.1 2.6 51 93 3
0 1 0 978 0 41 0 6.1527326947 3.9 0.078 1 80 3
0 1 0 979 0 36 0 6.1527326947 3.9 0.078 1 80 3
7 0 0 980 0 61 0 6.1527326947 3.9 0.078 1 80 3
1 3 0 961 0 54 0 6.2538288116 3.9 6.4 49 74 3
1 1 1 962 0 57 0 6.2538288116 3.9 6.4 49 74 3
0 3 0 963 0 54 0 6.2538288116 3.9 6.4 49 74 3
0 3 1 963 0 . 0 6.2538288116 3.9 6.4 49 74 3
2 3 1 963 0 40 0 6.2538288116 3.9 6.4 49 74 3
0 3 1 965 0 . 0 6.2538288116 3.9 6.4 49 74 3
0 3 1 965 1 45 0 6.2538288116 3.9 6.4 49 74 3
0 1 1 965 1 32 0 6.2538288116 3.9 6.4 49 74 3
0 1 0 965 0 44 0 6.2538288116 3.9 6.4 49 74 3
4 2 0 978 0 67 0 6.2538288116 3.9 6.4 49 74 3
4 1 0 982 0 56 0 6.2538288116 3.9 6.4 49 74 3
1 3 1 961 0 42 0 5.9401712527 4.6 9.4 284 85 3
2 3 1 963 1 48 0 5.9401712527 4.6 9.4 284 85 3
0 1 1 966 0 62 0 5.9401712527 4.6 9.4 284 85 3
1 1 0 966 0 45 0 5.9401712527 4.6 9.4 284 85 3
4 3 1 972 1 49 0 5.9401712527 4.6 9.4 284 85 3
2 1 1 976 1 50 0 5.9401712527 4.6 9.4 284 85 3
1 1 0 978 1 . 0 5.9401712527 4.6 9.4 284 85 3
2 2 0 979 0 38 0 5.9401712527 4.6 9.4 284 85 3
3 1 0 981 0 41 0 5.9401712527 4.6 9.4 284 85 3
3 0 0 984 0 53 0 5.9401712527 4.6 9.4 284 85 3
0 3 1 960 1 . 1 5.8579331545 -0.2 4.8 21 65 3
0 3 1 961 1 . 1 5.8579331545 -0.2 4.8 21 65 3
0 1 1 961 1 . 1 5.8579331545 -0.2 4.8 21 65 3
5 1 0 962 1 40 1 5.8579331545 -0.2 4.8 21 65 3
5 1 0 967 1 50 1 5.8579331545 -0.2 4.8 21 65 3
5 1 0 972 1 45 1 5.8579331545 -0.2 4.8 21 65 3
2 3 0 977 1 43 1 5.8579331545 -0.2 4.8 21 65 3
1 3 1 979 1 43 1 5.8579331545 -0.2 4.8 21 65 3
1 1 1 980 0 55 1 5.8579331545 -0.2 4.8 21 65 3
2 1 0 982 0 56 1 5.8579331545 -0.2 4.8 21 65 3
5 3 0 974 0 52 0 6.0402547113 0.9 0.1 0.34 85 3
4 3 1 979 0 36 0 6.0402547113 0.9 0.1 0.34 85 3
0 3 1 983 1 . 0 6.0402547113 0.9 0.1 0.34 85 3
1 1 1 983 0 44 0 6.0402547113 0.9 0.1 0.34 85 3
3 0 0 984 0 66 0 6.0402547113 0.9 0.1 0.34 85 3
3 1 1 963 1 55 1 6.2146080984 2.1 8 109 50 3
4 1 0 966 1 51 1 6.2146080984 2.1 8 109 50 3
4 1 0 970 1 52 1 6.2146080984 2.1 8 109 50 3
4 1 0 974 1 44 1 6.2146080984 2.1 8 109 50 3
4 1 0 978 0 54 1 6.2146080984 2.1 8 109 50 3
0 3 0 982 1 56 1 6.2146080984 2.1 8 109 50 3
1 3 1 982 1 56 1 6.2146080984 2.1 8 109 50 3
3 1 1 983 1 53 1 6.2146080984 2.1 8 109 50 3
1 0 0 986 0 44 1 6.2146080984 2.1 8 109 50 3
18 2 0 966 0 43 1 6.0161571597 0.5 0.79 215 85 3
2 0 0 985 0 56 1 6.0161571597 0.5 0.79 215 85 3
15 3 0 971 0 20 1 5.2983173665 1.1 5.9 28 23 3
1 0 1 985 1 54 1 5.2983173665 1.1 5.9 28 23 3
11 3 1 963 1 42 1 5.7683209958 0.6 4.4 112 56 3
3 3 1 975 1 44 1 5.7683209958 0.6 4.4 112 56 3
3 1 1 978 1 . 1 5.7683209958 0.6 4.4 112 56 3
4 1 0 982 0 48 1 5.7683209958 0.6 4.4 112 56 3
1 0 0 986 0 59 1 5.7683209958 0.6 4.4 112 56 3
5 1 0 962 0 78 0 6.8977049431 -0.5 2.2 11 74 3
0 2 0 967 0 55 0 6.8977049431 -0.5 2.2 11 74 3
5 1 0 967 0 44 0 6.8977049431 -0.5 2.2 11 74 3
8 1 0 972 0 48 0 6.8977049431 -0.5 2.2 11 74 3
7 0 0 980 0 50 0 6.8977049431 -0.5 2.2 11 74 3
6 1 0 964 0 53 0 6.7912214627 3.2 78.8 1973 88 3
6 1 0 970 0 48 0 6.7912214627 3.2 78.8 1973 88 3
6 1 0 976 0 52 0 6.7912214627 3.2 78.8 1973 88 3
5 0 0 982 0 48 0 6.7912214627 3.2 78.8 1973 88 3
3 2 1 963 0 53 0 6.2915691396 -1.8 3.3 130 88 3
0 3 0 966 0 66 0 6.2915691396 -1.8 3.3 130 88 3
11 3 1 967 1 34 0 6.2915691396 -1.8 3.3 130 88 3
6 0 1 981 0 36 1 6.2915691396 -1.8 3.3 130 88 3
4 3 0 964 0 59 0 6.82437367 2.9 2.2 77 90 3
0 1 1 968 0 . 0 6.82437367 2.9 2.2 77 90 3
0 1 0 968 0 63 0 6.82437367 2.9 2.2 77 90 3
12 2 1 968 1 39 0 6.82437367 2.9 2.2 77 90 3
0 3 1 981 1 . 0 6.82437367 2.9 2.2 77 90 3
0 3 1 982 1 48 0 6.82437367 2.9 2.2 77 90 3
5 0 1 982 1 . 0 6.82437367 2.9 2.2 77 90 3
0 3 0 962 0 67 1 6.429719478 0.1 18.6 1285 80 3
0 3 1 962 1 59 1 6.429719478 0.1 18.6 1285 80 3
0 1 1 963 1 . 1 6.429719478 0.1 18.6 1285 80 3
5 3 0 963 0 50 1 6.429719478 0.1 18.6 1285 80 3
6 3 1 968 1 58 1 6.429719478 0.1 18.6 1285 80 3
4 1 1 975 1 54 1 6.429719478 0.1 18.6 1285 80 3
2 0 0 985 0 36 1 6.429719478 0.1 18.6 1285 80 3
4 0 0 983 0 47 0 6.551080335 3.1 0.043 0.26 80 3
0 1 0 979 0 53 0 6.3456363608 3.1 0.136 0.62 78 3
2 1 0 979 0 62 0 6.3456363608 3.1 0.136 0.62 78 3
0 1 0 981 0 55 0 6.3456363608 3.1 0.136 0.62 78 3
0 1 0 982 0 36 0 6.3456363608 3.1 0.136 0.62 78 3
5 1 0 979 0 64 0 5.8579331545 1.8 0.119 0.39 82 3
3 0 0 984 0 53 0 5.8579331545 1.8 0.119 0.39 82 3
6 3 0 973 0 37 1 7.2225660188 4.5 0.393 163 65 3
1 1 1 980 0 43 1 7.2225660188 4.5 0.393 163 65 3
6 0 0 981 1 . 1 7.2225660188 4.5 0.393 163 65 3
19 2 0 962 0 50 1 6.8772960715 3.4 1.2 5 98 3
5 1 1 981 0 49 1 6.8772960715 3.4 1.2 5 98 3
1 0 0 986 0 60 1 6.8772960715 3.4 1.2 5 98 3
1 1 0 960 0 . 0 6.8564619846 2 3 176 94 3
1 1 0 961 0 . 0 6.8564619846 2 3 176 94 3
1 1 0 962 0 . 0 6.8564619846 2 3 176 94 3
1 1 0 963 0 . 0 6.8564619846 2 3 176 94 3
0 2 0 964 0 70 0 6.8564619846 2 3 176 94 3
0 1 0 965 0 50 0 6.8564619846 2 3 176 94 3
1 1 0 965 0 . 0 6.8564619846 2 3 176 94 3
0 1 0 966 0 50 0 6.8564619846 2 3 176 94 3
0 1 0 966 0 . 0 6.8564619846 2 3 176 94 3
0 1 0 967 1 66 0 6.8564619846 2 3 176 94 3
4 1 0 967 0 47 0 6.8564619846 2 3 176 94 3
5 3 0 971 0 43 0 6.8564619846 2 3 176 94 3
0 3 1 976 0 80 0 6.8564619846 2 3 176 94 3
5 3 1 976 0 72 0 6.8564619846 2 3 176 94 3
3 1 1 981 1 56 0 6.8564619846 2 3 176 94 3
2 0 0 985 0 49 0 6.8564619846 2 3 176 94 3
5 1 0 964 0 58 0 7.3963352938 1.5 17.3 912 86 3
5 1 0 969 0 53 0 7.3963352938 1.5 17.3 912 86 3
5 1 0 974 0 52 0 7.3963352938 1.5 17.3 912 86 3
5 1 0 979 0 53 0 7.3963352938 1.5 17.3 912 86 3
4 0 0 984 0 59 0 7.3963352938 1.5 17.3 912 86 3
;





-------------
RANK Data Set
-------------

/* Data described in Ch. 7 of P. Allison, "Survival Analysis Using
   the SAS System: A Practical Guide."                             */


data rank;
input dur event undgrad phdmed phdprest art1-art10 cit1-cit10 prest1
prest2 jobtime;
cards;
10 0 7 0 2.21 0 0 2 2 2 2 2 2 2 2 0 0 1 1 1 1 1 1 1 1 2.36 2.36 .
4 1 6 0 2.21 8 10 14 18 . . . . . . 27 44 57 63 . . . . . . 1.84 2.88 3
4 0 4.95 0 2.21 0 0 0 2 . . . . . . 0 0 0 2 . . . . . . 2.4 2.4 .
10 0 2 1 4.54 2 3 3 3 3 4 6 6 6 6 11 17 17 17 17 20 24 24 24 24 2.56 2.56 .
7 1 5 1 2.15 1 1 1 2 2 3 5 . . . 14 14 14 19 19 20 23 . . . 2.4 2.4 .
6 1 4.95 0 4.54 0 2 3 5 5 6 . . . . 0 0 2 6 6 11 . . . . 3.36 3.36 .
10 0 6 1 4.54 5 5 5 5 5 5 5 6 6 6 29 29 29 29 29 29 29 31 31 31 2.88 1.94 4
6 1 4 1 2.96 3 4 7 8 8 9 . . . . 19 26 37 45 45 56 . . . . 2.2 2.2 .
4 0 4 1 1.63 8 8 10 11 . . . . . . 41 41 67 70 . . . . . . 3.2 3.2 .
5 1 5 1 2.96 0 1 1 1 2 . . . . . 0 0 0 0 5 . . . . . 2.72 2.72 .
6 1 5 1 1.63 8 10 12 18 20 24 . . . . 28 54 64 132 167 189 . . . . 2.11 2.11 .
6 0 4.95 1 2.86 6 9 12 14 21 25 . . . . 36 39 52 64 105 127 . . . . 3.2 3.2 .
7 1 5 1 3.36 11 17 18 19 20 23 32 . . . 62 91 101 106 107 119 165 . . .
3.68 3.68 .
6 1 4.95 1 4.54 1 1 2 3 8 10 . . . . 13 13 14 14 44 53 . . . . 3.68 3.68 .
5 1 5 1 3.54 12 13 14 15 17 . . . . . 140 142 146 151 162 . . . . . 2.12 2.12 .
4 1 5 1 4.54 0 0 0 1 . . . . . . 0 0 0 1 . . . . . . 1.94 1.94 .
7 0 5 0 3.69 1 3 3 3 3 3 4 . . . 31 66 66 66 66 66 67 . . . 2.72 2.72 .
7 1 5 1 2.32 1 1 1 1 2 5 5 . . . 3 3 3 3 6 24 24 . . . 2.52 2.52 .
5 1 5 1 1.95 5 7 8 10 13 . . . . . 115 136 143 191 244 . . . . . 3.52 3.52 .
5 1 6 1 1.86 3 4 7 7 8 . . . . . 17 21 40 40 52 . . . . . 1.79 1.79 .
3 1 5 1 2.54 3 3 3 . . . . . . . 7 7 7 . . . . . . . 1.96 1.47 3
10 0 4.95 0 3.4 2 2 2 2 2 2 3 4 6 6 17 17 17 17 17 17 29 39 42 42 3.52 1 10
6 1 4 0 4.54 8 8 9 12 14 15 . . . . 75 75 80 110 111 120 . . . . 4.48 2.36 4
10 0 3 1 2.12 1 1 1 1 1 1 2 2 2 2 0 0 0 0 0 0 2 2 2 2 2.72 3.2 4
7 1 5 1 2.32 1 1 1 1 3 4 4 . . . 2 2 2 2 7 9 9 . . . 2.56 2.56 .
4 1 6 1 2.96 11 12 12 12 . . . . . . 75 75 75 75 . . . . . . 2.2 2.2 .
9 0 6 1 3.69 4 6 7 8 10 12 12 13 13 . 47 51 62 74 86 111 111 112 112 . 3.36 1 9
5 1 5 1 2.39 7 7 7 7 7 . . . . . 16 16 16 16 16 . . . . . 1.48 1.48 .
5 1 7 0 3.36 6 7 7 11 14 . . . . . 130 143 143 167 197 . . . . . 3.52 3.52 .
8 1 5 1 3.69 7 7 8 9 10 12 15 15 . . 70 70 89 107 109 133 169 169 . . 3.36
2.24 8
5 1 4.95 0 3.92 2 3 6 8 9 . . . . . 0 7 19 30 36 . . . . . 2.39 3.2 5
8 1 6 1 1.95 6 6 8 8 9 9 9 11 . . 61 61 72 72 78 78 78 106 . . 2.36 3.2 8
4 1 4 0 2.96 2 2 2 2 . . . . . . 7 7 7 7 . . . . . . 2.56 2.56 .
4 1 1 0 3.92 5 6 7 7 . . . . . . 78 82 85 85 . . . . . . 2.56 2.56 .
4 1 4.95 1 4.62 8 11 11 11 . . . . . . 264 421 421 421 . . . . . . 4.64 4.64 .
4 0 3 0 1.52 1 2 2 2 . . . . . . 0 1 1 1 . . . . . . 1.68 1.68 .
4 1 6 1 3.54 8 9 14 21 . . . . . . 106 116 153 238 . . . . . . 3.04 3.04 .
8 1 4.95 1 4.54 7 8 9 11 12 14 14 24 . . 56 71 87 102 107 120 120 188 . .
3.36 3.36 .
10 0 4 1 2.5 2 4 4 6 7 8 9 9 9 10 25 42 42 51 52 55 56 56 56 58 2.11 2.11 .
4 1 6 1 4.54 12 13 15 17 . . . . . . 138 142 153 157 . . . . . . 2.36 2.36 .
5 0 3 1 3.92 2 2 2 3 5 . . . . . 27 27 27 44 70 . . . . . 2.18 2.18 .
9 1 5 1 3.4 0 1 1 1 1 3 3 3 6 . 0 7 7 7 7 13 13 13 24 . 1.97 1.97 .
6 1 7 0 3.54 7 7 9 9 10 12 . . . . 78 78 95 95 111 135 . . . . 3.68 2.88 2
5 1 5 0 4.62 5 6 10 13 15 . . . . . 36 46 53 61 67 . . . . . 2.72 2.72 .
3 0 7 1 1.78 9 10 10 . . . . . . . 45 45 45 . . . . . . . 2.56 2.56 .
5 1 3 1 2.51 11 15 15 17 18 . . . . . 52 60 60 65 81 . . . . . 2.21 2.21 .
8 1 5 1 2.51 10 10 11 12 12 12 12 13 . . 89 89 92 103 103 103 103 107 . .
3.68 1.72 8
5 0 3 1 1.22 1 1 1 1 1 . . . . . 2 2 2 2 2 . . . . . 2.72 2.72 .
3 0 4 0 1.86 2 2 2 . . . . . . . 32 32 32 . . . . . . . 1.05 1.05 .
5 1 7 1 4.62 22 25 28 31 35 . . . . . 209 237 272 290 396 . . . . . 4.64 4.64 .
4 0 4.95 1 2.87 4 4 7 7 . . . . . . 28 28 44 44 . . . . . . 2.47 3.84 2
6 1 5 0 3.4 9 10 12 13 16 17 . . . . 97 109 132 140 164 180 . . . . 3.52 2.26 3
4 1 3 0 2.58 2 6 9 13 . . . . . . 24 51 62 68 . . . . . . 1.99 1.99 .
3 0 4 0 1.68 1 1 1 . . . . . . . 4 4 4 . . . . . . . 1.68 1.68 .
4 1 6 0 3.92 7 8 11 12 . . . . . . 86 105 143 147 . . . . . . 2.11 2.11 .
4 1 6 1 3.54 3 3 5 8 . . . . . . 19 19 23 36 . . . . . . 2.72 2.72 .
6 1 6 1 1.78 10 11 12 12 16 18 . . . . 98 106 106 106 135 139 . . . . 3.2 3.2 .
5 1 7 1 3.92 5 9 10 11 14 . . . . . 22 73 84 92 153 . . . . . 3.2 3.2 .
10 0 5 1 4.54 2 3 3 3 3 4 4 4 4 6 18 24 24 24 24 24 24 24 24 30 2.72 4.32 4
4 1 4 1 3.36 4 5 5 7 . . . . . . 47 47 47 69 . . . . . . 1.26 1.26 .
4 1 4.95 1 3.92 18 26 36 44 . . . . . . 117 234 350 419 . . . . . . 3.36 3.36 .
7 1 4.95 0 4.25 6 10 15 16 19 21 28 . . . 143 178 185 185 204 227 266 . . .
4.48 3.2 7
10 0 4 1 1.76 6 6 6 6 7 7 7 7 8 9 13 13 13 13 13 13 13 13 16 16 1.9 1.9 .
5 1 6 0 2.87 7 7 7 8 8 . . . . . 84 84 84 94 94 . . . . . 2.72 2.72 .
9 0 4 0 3.4 0 0 2 3 3 3 4 5 5 . 0 0 11 21 21 21 21 22 22 . 2.35 1 9
7 1 6 1 3.69 2 4 5 6 8 8 11 . . . 24 31 34 37 58 58 94 . . . 3.36 1.26 7
4 1 4 1 1.76 6 7 7 10 . . . . . . 62 67 67 78 . . . . . . 2.88 2.88 .
10 1 7 0 4.25 4 4 4 4 6 6 6 7 8 11 73 73 73 73 84 84 84 90 92 106 4.48 1.95 10
6 1 7 1 2.58 4 4 5 6 7 8 . . . . 24 24 28 42 55 80 . . . . 2.5 2.5 .
6 1 6 1 2.83 1 1 1 1 2 3 . . . . 9 9 9 9 25 56 . . . . 3.36 3.04 6
3 1 6 1 3.4 18 21 23 . . . . . . . 344 381 400 . . . . . . . 4.64 3.36 3
6 1 5 0 2.86 0 0 0 2 3 3 . . . . 0 0 0 6 12 12 . . . . 3.2 3.2 .
9 1 7 0 4.62 0 1 1 1 1 1 1 2 3 . 0 20 20 20 20 20 20 22 28 . 3.04 3.04 .
8 1 4 0 2.86 3 4 4 5 7 7 8 8 . . 31 47 47 50 52 52 56 56 . . 1.4 2.39 4
7 0 7 1 3.69 1 4 6 6 6 7 7 . . . 20 27 47 47 47 73 73 . . . 3.52 3.52 .
4 1 3 1 3.92 3 3 4 5 . . . . . . 10 10 10 14 . . . . . . 3.52 3.52 .
5 1 6 1 2.87 5 16 17 18 19 . . . . . 17 181 196 278 312 . . . . . 3.84 2.88 5
3 0 4 1 2.54 3 3 4 . . . . . . . 22 22 30 . . . . . . . 2.88 2.88 .
9 0 3 1 2.83 4 5 6 6 6 7 8 8 8 . 26 26 31 31 31 43 46 46 46 . 3.04 3.68 4
9 0 4 1 4.62 6 8 9 15 20 20 32 44 49 . 133 149 157 216 294 294 496 724 864
. 2.52 2.52 .
9 1 5 1 3.4 4 5 9 10 10 12 13 15 15 . 17 24 38 59 59 67 69 75 75 . 3.52 2.52 5
7 0 6 1 3.54 2 2 2 2 2 2 2 . . . 37 37 37 37 37 37 37 . . . 2.15 2.15 .
4 1 2 1 1.51 4 5 6 6 . . . . . . 8 11 13 13 . . . . . . 2.88 2.88 .
8 1 5 0 2 1 1 5 8 10 12 14 16 . . 6 6 11 19 21 29 34 39 . . 1.74 2.39 3
6 0 4 1 1.68 1 1 1 3 6 9 . . . . 7 7 7 18 23 31 . . . . 1.9 1.9 .
5 1 7 1 4.62 11 12 14 20 28 . . . . . 166 185 236 306 428 . . . . . 4.64 3.52 5
10 1 1 1 1.68 5 5 5 11 14 16 18 18 18 18 14 14 14 57 120 176 194 194 194
194 2.11 2.11 .
5 1 7 1 2.83 4 5 5 8 8 . . . . . 18 18 18 94 94 . . . . . 1.53 1.37 3
6 1 7 0 4.14 2 5 7 7 10 11 . . . . 16 32 36 36 51 55 . . . . 4.32 3.52 6
7 1 7 0 4.14 1 1 3 3 5 7 8 . . . 20 20 29 29 35 83 83 . . . 3.68 3.68 .
7 0 4.95 1 4.62 2 2 2 2 2 5 5 . . . 28 28 28 28 28 84 84 . . . 2.52 2.52 .
3 1 6 1 3.36 0 1 1 . . . . . . . 0 10 10 . . . . . . . 2.88 1.5 3
5 1 4 0 4.54 2 2 2 3 3 . . . . . 11 11 11 11 11 . . . . . 1.65 1.65 .
5 1 6 1 2.54 1 1 5 7 7 . . . . . 0 0 7 8 8 . . . . . 1.91 1.47 5
5 1 5 0 2 2 2 3 3 4 . . . . . 9 9 15 15 36 . . . . . 2.56 3.2 4
4 1 7 0 4.54 10 10 10 12 . . . . . . 59 59 59 66 . . . . . . 2.45 2.56 2
4 1 4.95 0 4.54 4 6 6 8 . . . . . . 13 38 38 44 . . . . . . 1.94 1.94 .
3 1 6 0 1.42 3 3 5 . . . . . . . 1 1 5 . . . . . . . 1.75 1.75 .
7 1 7 1 4.62 3 7 7 7 7 7 8 . . . 28 77 77 77 77 77 82 . . . 1.68 1.68 .
2 0 4 1 2.96 0 1 . . . . . . . . 0 5 . . . . . . . . 2.88 2.88 .
8 1 6 1 3.47 1 2 2 3 4 6 8 9 . . 1 1 1 11 11 16 21 23 . . 2.88 2.88 .
10 0 4 1 4.29 2 2 2 2 2 4 6 8 8 8 6 6 6 6 6 6 8 19 19 19 2.21 2.21 .
7 1 4 1 2.61 0 1 2 3 3 3 3 . . . 0 2 3 7 7 7 7 . . . 1.22 1.94 7
6 1 4 0 2.76 6 8 9 13 13 17 . . . . 29 31 40 61 61 83 . . . . 3.2 1.47 6
6 1 6 1 4.29 2 3 3 4 5 6 . . . . 1 1 1 1 6 9 . . . . 2.1 2.1 .
5 0 5 1 2.1 1 3 3 4 4 . . . . . 3 12 12 18 18 . . . . . 1.63 1.63 .
7 1 4.95 1 3.62 3 3 5 10 14 23 31 . . . 3 3 14 26 45 93 149 . . . 3.04 3.04 .
6 1 4 1 3.59 5 6 6 8 8 8 . . . . 14 16 16 29 29 29 . . . . 3.68 3.2 6
8 1 7 1 3.41 4 8 14 16 21 22 23 23 . . 29 95 146 208 329 340 366 366 . .
2.11 2.88 6
3 1 5 1 3.59 10 11 13 . . . . . . . 84 98 101 . . . . . . . 3.36 3.36 .
4 1 7 0 4.29 2 3 6 7 . . . . . . 3 3 9 11 . . . . . . 3.36 3.36 .
6 1 6 1 2.15 4 6 8 8 10 11 . . . . 12 22 27 27 29 30 . . . . 3.04 3.04 .
5 1 5 1 4.29 4 4 4 5 6 . . . . . 19 19 19 31 37 . . . . . 2.1 2.1 .
8 1 6 1 4.29 4 4 4 4 7 8 9 13 . . 3 3 3 3 21 21 23 55 . . 1.94 1.94 .
8 0 4.95 1 4.29 0 0 0 0 0 0 0 0 . . 0 0 0 0 0 0 0 0 . . 2.72 2.72 .
10 0 6 1 4.29 5 6 8 11 13 15 17 17 20 23 23 23 27 32 35 39 45 45 67 97 3.36
3.36 .
7 1 6 0 3.62 5 6 7 8 10 11 13 . . . 23 38 42 49 60 62 74 . . . 2.56 2.18 7
6 1 7 0 2.61 3 6 11 13 20 29 . . . . 54 100 137 149 178 222 . . . . 3.68 3.68 .
5 1 5 1 2.5 3 5 5 7 7 . . . . . 8 16 16 23 23 . . . . . 2.72 3.2 5
4 1 5 1 4.29 0 0 1 2 . . . . . . 0 0 7 10 . . . . . . 1.9 3.36 4
7 1 6 1 2.14 0 0 1 3 4 6 7 . . . 0 0 5 33 46 90 164 . . . 1.96 1.96 .
9 0 5 0 4.29 2 2 3 3 9 11 17 19 26 . 26 26 35 35 70 78 95 113 152 . 2.56 2.56 .
3 0 7 0 3.41 5 6 8 . . . . . . . 65 101 139 . . . . . . . 3.52 1 3
4 0 5 1 4.29 5 7 7 7 . . . . . . 30 31 31 31 . . . . . . 3.36 3.36 .
6 1 3 0 4.29 0 0 0 1 2 4 . . . . 0 0 0 4 5 7 . . . . 1.5 1.5 .
6 0 5 1 2.36 1 1 1 2 4 5 . . . . 2 2 2 5 8 8 . . . . 2.72 2.72 .
5 1 5 1 2.76 5 5 5 6 7 . . . . . 80 80 80 95 104 . . . . . 3.2 3.2 .
3 1 5 0 4.29 0 0 0 . . . . . . . 0 0 0 . . . . . . . 2.72 3.36 3
5 1 4.95 1 4.29 0 0 1 2 4 . . . . . 0 0 1 5 27 . . . . . 2.72 3.36 5
3 0 4 0 2.05 1 1 1 . . . . . . . 0 0 0 . . . . . . . 1.32 1 3
8 1 3 1 4.29 0 1 3 4 6 8 10 10 . . 0 2 18 21 45 53 58 58 . . 2.56 2.56 .
2 0 3 0 3.59 12 15 . . . . . . . . 333 375 . . . . . . . . 3.84 1 2
10 0 4 0 4.29 5 5 7 8 9 11 11 11 11 12 24 24 28 40 44 57 57 57 57 72 2.5 2.5 .
5 1 5 0 4.29 5 9 13 17 25 . . . . . 78 99 127 159 185 . . . . . 3.04 3.04 .
5 1 5 1 3.41 12 12 14 14 15 . . . . . 420 420 566 566 579 . . . . . 3.36 3.36 .
7 1 6 1 3.59 0 0 0 0 1 2 2 . . . 0 0 0 0 9 12 12 . . . 3.04 3.04 .
10 1 7 1 2.26 1 1 2 2 2 2 2 2 2 3 1 1 3 3 3 3 3 3 3 3 3.68 3.68 .
6 0 4 0 4.47 0 1 1 4 5 6 . . . . 0 3 3 14 14 14 . . . . 3.36 3.36 .
5 1 5 1 3.19 2 2 2 2 2 . . . . . 13 13 13 13 13 . . . . . 1.56 1.56 .
4 1 4 1 3.47 6 7 7 10 . . . . . . 14 16 16 19 . . . . . . 3.36 3.36 .
3 1 5 1 4.29 5 5 5 . . . . . . . 9 9 9 . . . . . . . 2.02 2.02 .
6 1 4 0 2.1 1 1 2 2 4 6 . . . . 0 0 0 0 3 6 . . . . 3.52 3.52 .
7 1 6 0 3.59 3 3 4 4 6 8 9 . . . 8 8 8 8 12 19 22 . . . 3.04 3.68 7
4 1 5 0 4.29 0 1 1 6 . . . . . . 0 5 5 23 . . . . . . 3.84 3.84 .
4 1 3 1 1.81 3 4 4 7 . . . . . . 15 18 18 54 . . . . . . 1.94 1.94 .
6 1 6 1 3.59 6 8 11 15 18 20 . . . . 80 89 140 255 389 424 . . . . 3.36 3.36 .
4 0 4 0 4.29 10 12 14 14 . . . . . . 95 100 101 101 . . . . . . 1.63 1.63 .
10 0 6 1 2.1 2 2 2 2 2 3 3 3 5 6 7 7 7 7 7 14 14 14 26 30 2.37 2.37 .
4 1 7 0 4.29 7 8 8 11 . . . . . . 196 209 209 262 . . . . . . 3.84 3.84 .
10 0 3 1 2.51 4 5 6 7 10 13 18 22 27 29 8 8 13 14 39 62 86 100 134 141 1.96
1.96 .
3 1 5 0 3.15 9 12 13 . . . . . . . 179 188 205 . . . . . . . 3.2 3.2 .
4 1 4 0 3.15 5 5 6 9 . . . . . . 34 34 35 44 . . . . . . 1.9 1.9 .
5 0 7 1 4.62 3 3 3 7 8 . . . . . 105 105 105 120 131 . . . . . 2.23 2.23 .
5 1 5 1 1.86 1 1 2 3 4 . . . . . 5 5 6 7 7 . . . . . 1.53 1.53 .
6 1 3 1 2.56 4 5 5 6 6 7 . . . . 31 40 40 41 41 45 . . . . 0.65 0.65 .
3 1 7 1 4.25 4 5 6 . . . . . . . 72 78 82 . . . . . . . 2.56 2.56 .
3 1 3 1 2.96 21 27 36 . . . . . . . 105 126 173 . . . . . . . 2.56 2.56 .
5 1 5 1 3.54 6 7 10 11 11 . . . . . 68 71 84 84 84 . . . . . 1.9 1.9 .
5 1 7 0 2.96 3 6 7 9 10 . . . . . 34 56 74 94 99 . . . . . 1.86 1.86 .
6 1 4 1 4.54 5 6 7 9 9 11 . . . . 59 61 80 114 114 150 . . . . 2.3 2.3 .
2 1 4.95 1 2.83 7 8 . . . . . . . . 18 18 . . . . . . . . 3.2 3.2 .
6 1 4 1 2.39 2 2 3 3 6 6 . . . . 6 6 9 9 13 13 . . . . 1.53 1.53 .
5 1 4.95 0 3.69 2 2 3 5 6 . . . . . 20 20 25 48 57 . . . . . 4 4 .
7 1 4 1 3.4 1 1 1 1 1 1 1 . . . 20 20 20 20 20 20 20 . . . 3.52 3.52 .
9 1 6 1 1.97 7 8 9 10 12 14 15 16 17 . 35 47 48 61 67 95 130 160 218 . 3.52
3.52 .
6 1 7 1 3.36 4 4 5 6 7 8 . . . . 36 36 38 41 45 45 . . . . 2.02 2.02 .
6 1 7 1 2.83 5 5 5 6 6 8 . . . . 32 32 32 32 32 43 . . . . 2.72 2.72 .
5 1 4 0 4.54 3 3 4 6 10 . . . . . 70 70 72 86 117 . . . . . 2.88 2.88 .
5 1 4 0 4.62 1 2 4 4 4 . . . . . 5 13 32 32 32 . . . . . 2.09 1.99 3
6 1 5 1 2.5 7 9 10 11 12 15 . . . . 37 43 49 53 56 62 . . . . 1.48 1.48 .
9 1 3 1 2.58 6 9 9 9 11 13 14 17 21 . 66 66 66 66 73 91 103 154 233 . 2.11
2.11 .
7 1 4 0 1.72 8 11 13 13 13 14 16 . . . 61 76 91 91 91 92 104 . . . 1.84 1.84 .
4 1 7 1 3.69 3 3 4 6 . . . . . . 123 123 138 182 . . . . . . 2.3 2.3 .
10 0 5 1 3.92 8 9 9 9 10 10 10 10 10 10 125 126 126 126 126 126 126 126 126
126 2.56 2.56 .
6 0 4 0 1.22 0 1 1 3 7 7 . . . . 0 2 2 4 7 7 . . . . 1.44 1 6
4 0 4.95 1 1.68 0 0 0 0 . . . . . . 0 0 0 0 . . . . . . 1.1 1 4
6 0 3 0 2.96 0 1 1 1 1 1 . . . . 0 0 0 0 0 0 . . . . 1.4 1.4 .
7 1 5 1 2.96 2 3 3 3 3 9 10 . . . 6 24 24 24 24 49 50 . . . 2.4 2.4 .
6 1 5 1 3.15 8 8 10 10 10 11 . . . . 59 59 66 66 66 86 . . . . 1.7 1.7 .
4 1 4 1 2.51 4 7 8 8 . . . . . . 89 149 165 165 . . . . . . 3.84 1.37 3
5 1 4.95 1 4.54 15 15 17 20 22 . . . . . 103 103 121 221 238 . . . . . 2.36
2.36 .
6 0 4 0 4.54 5 5 5 5 5 5 . . . . 27 27 27 27 27 27 . . . . 3.04 3.04 .
5 1 5 0 2.96 1 3 4 5 5 . . . . . 1 3 17 17 17 . . . . . 2.24 2.24 .
9 0 3 1 1.42 0 0 0 0 0 1 1 3 4 . 0 0 0 0 0 2 2 4 6 . 1.84 1.84 .
7 1 5 0 3.09 7 8 9 11 14 18 22 . . . 35 36 39 47 59 70 74 . . . 2.24 2.24 .
10 0 5 1 2.54 11 11 13 13 15 16 17 17 18 18 187 187 199 199 199 244 245 245
245 245 1.47 1.47 .
4 1 4 1 4.14 0 0 6 7 . . . . . . 0 0 26 26 . . . . . . 3.2 3.2 .
3 0 5 1 2.21 2 2 2 . . . . . . . 18 18 18 . . . . . . . 2.49 2.49 .
4 0 4 1 2 1 1 2 4 . . . . . . 1 1 19 35 . . . . . . 2.56 2.56 .
3 0 1 1 1.18 0 0 0 . . . . . . . 0 0 0 . . . . . . . 1.5 1.5 .
3 0 7 1 3.69 4 7 7 . . . . . . . 100 143 143 . . . . . . . 3.36 3.36 .
6 1 6 1 2.21 8 8 8 10 11 11 . . . . 173 173 173 186 190 190 . . . . 2.4 2.56 6
2 0 7 0 3.36 1 1 . . . . . . . . 1 1 . . . . . . . . 2.52 2.52 .
3 1 7 1 3.4 6 7 7 . . . . . . . 35 45 45 . . . . . . . 2.56 2.56 .
4 1 4 1 2.86 10 13 16 16 . . . . . . 38 40 46 46 . . . . . . 1.48 1.48 .
7 1 5 1 2.2 0 0 0 0 2 2 2 . . . 0 0 0 0 1 1 1 . . . 2.15 2.15 .
6 1 4.95 0 2.54 12 14 14 15 22 25 . . . . 154 175 175 180 238 257 . . . .
3.52 3.52 .
7 0 7 0 4.25 8 9 9 10 10 12 14 . . . 263 267 267 268 268 287 313 . . . 2.88 1 7
2 0 7 1 1.76 4 4 . . . . . . . . 40 40 . . . . . . . . 1.94 1.94 .
7 1 4.95 1 3.69 5 6 9 10 11 12 16 . . . 30 35 68 76 83 117 169 . . . 3.36 3.36 .
5 1 4.95 1 2.51 2 3 5 9 10 . . . . . 17 22 37 64 77 . . . . . 3.84 3.84 .
7 1 2 1 1.68 3 3 5 5 6 6 6 . . . 6 6 11 11 13 13 13 . . . 1.8 1.8 .
4 1 7 0 2.83 5 6 6 7 . . . . . . 59 79 79 91 . . . . . . 3.36 3.36 .
5 1 4.95 0 4.54 7 8 9 11 12 . . . . . 73 80 97 113 113 . . . . . 2.88 2.88 .
4 0 4 0 2.87 4 4 5 6 . . . . . . 39 39 44 50 . . . . . . 2.22 2.22 .
7 1 5 0 3.4 4 4 4 5 7 10 13 . . . 42 42 42 56 68 94 108 . . . 3.52 3.52 .
5 0 4.95 1 2.56 1 5 11 17 23 . . . . . 22 47 89 155 187 . . . . . 2.72 2.72 .
4 1 5 0 2.96 2 2 2 3 . . . . . . 0 0 0 4 . . . . . . 3.04 3.04 .
7 1 5 0 4.54 1 1 2 3 4 6 7 . . . 5 5 13 22 31 40 41 . . . 2.47 2.47 .
6 1 6 1 0.92 0 1 1 1 3 5 . . . . 0 22 22 22 25 62 . . . . 0.98 2.24 3
3 1 4 0 2.96 8 10 13 . . . . . . . 23 25 29 . . . . . . . 1.82 1.82 .
5 1 6 1 3.54 3 3 5 6 6 . . . . . 11 11 27 30 30 . . . . . 1.94 1.94 .
6 1 7 0 3.69 4 4 5 7 8 8 . . . . 48 48 49 68 76 76 . . . . 3.68 1.58 6
6 1 7 1 4.62 8 9 10 10 12 16 . . . . 60 60 61 61 72 102 . . . . 4.64 4.64 .
7 1 6 1 3.15 4 5 7 7 9 10 10 . . . 58 71 82 82 90 94 94 . . . 3.2 3.2 .
3 1 7 1 4.62 8 12 16 . . . . . . . 45 183 227 . . . . . . . 3.52 3.52 .
1 0 4 0 2.96 10 . . . . . . . . . 165 . . . . . . . . . 3.52 3.52 .
4 1 5 1 4.25 4 5 8 12 . . . . . . 46 70 96 129 . . . . . . 3.52 3.52 .
5 0 4 1 1.97 2 2 2 2 2 . . . . . 3 3 3 3 3 . . . . . 3.52 3.52 .
10 0 4.95 1 2.51 0 0 0 0 1 1 2 3 4 4 0 0 0 0 0 0 1 2 9 9 2.1 2.1 .
2 0 5 0 2.96 0 0 . . . . . . . . 0 0 . . . . . . . . 3.2 3.2 .
6 1 4.95 1 2.39 3 4 5 5 5 5 . . . . 10 12 20 20 20 20 . . . . 3.36 1.4 6
7 1 5 0 3.09 5 6 6 7 8 9 10 . . . 44 53 53 60 63 66 71 . . . 2.56 2.56 .
7 1 4 0 2.55 1 5 5 5 5 7 8 . . . 7 54 54 54 54 65 72 . . . 1.88 1.88 .
10 0 7 0 4.14 1 1 1 1 2 4 6 6 6 7 1 1 1 1 5 6 10 10 10 10 3.04 1.4 9
4 1 4.95 0 2.86 10 14 18 21 . . . . . . 16 20 23 69 . . . . . . 2.52 2.72 2
10 0 5 1 2.32 1 1 2 2 2 2 3 3 3 5 4 4 4 4 4 4 6 6 6 26 3.04 3.04 .
3 0 4 0 1.52 0 0 3 . . . . . . . 0 0 2 . . . . . . . 1.3 1.3 .
6 1 3 0 2.55 2 4 7 9 9 11 . . . . 2 4 28 37 37 39 . . . . 1.32 1.32 .
5 1 6 1 4.62 4 7 7 7 7 . . . . . 20 40 40 40 40 . . . . . 2.52 2.52 .
5 0 4 0 3.19 3 3 3 3 3 . . . . . 31 31 31 31 31 . . . . . 2.56 1 5
5 0 5 0 4.29 0 0 0 3 3 . . . . . 0 0 0 20 20 . . . . . 1.94 1.94 .
10 0 1 0 2.76 2 2 3 3 4 6 6 8 8 11 2 2 3 3 3 6 6 7 7 16 2.72 2.18 4
10 0 5 1 2.12 1 1 2 2 2 2 2 2 2 2 4 4 7 7 7 7 7 7 7 7 4 1.84 3
4 1 7 1 4.34 3 6 10 12 . . . . . . 16 26 66 80 . . . . . . 2.12 2.12 .
7 0 5 0 4.29 2 2 3 4 5 7 8 . . . 2 2 2 3 3 5 7 . . . 1.84 1.84 .
8 1 3 1 4.29 4 4 5 6 10 13 17 18 . . 21 21 24 35 44 52 72 77 . . 3.36 3.36 .
10 0 1 1 2.61 2 3 3 3 4 4 5 5 5 5 11 14 14 14 19 19 23 23 23 23 2.88 2.88 .
5 1 6 1 3.47 3 3 6 7 11 . . . . . 27 27 70 101 124 . . . . . 3.2 3.2 .
6 1 6 1 2.5 3 6 8 10 11 12 . . . . 2 11 15 20 21 21 . . . . 1.9 1.9 .
5 1 4.95 1 1.81 3 3 4 4 6 . . . . . 21 21 37 37 58 . . . . . 1.94 1.94 .
6 1 5 0 4.29 0 0 0 0 0 0 . . . . 0 0 0 0 0 0 . . . . 2.72 2.72 .
6 1 5 0 2.1 0 1 1 2 2 2 . . . . 0 1 1 3 3 3 . . . . 1.53 1.53 .
7 1 5 1 1.8 7 8 8 8 8 10 11 . . . 40 41 41 41 41 47 49 . . . 2.16 2.16 .
7 1 7 0 4.29 4 4 6 8 13 16 20 . . . 25 25 34 59 97 126 160 . . . 3.04 3.04 .
7 1 4.95 1 2.26 0 3 5 5 5 8 9 . . . 0 3 12 12 12 34 38 . . . 2.11 2.11 .
10 1 6 1 2.58 0 1 1 1 1 1 1 2 3 4 0 15 15 15 15 15 15 28 36 45 2.56 2.08 3
5 1 4 1 3.47 8 9 10 14 16 . . . . . 222 225 245 299 301 . . . . . 3.04 3.04 .
6 1 3 0 4.29 3 4 10 12 17 18 . . . . 19 44 86 97 127 136 . . . . 4.16 3.04 3
2 0 5 0 2.76 0 1 . . . . . . . . 0 9 . . . . . . . . 1.86 1.86 .
1 1 6 1 2.1 2 . . . . . . . . . 155 . . . . . . . . . 2.4 2.4 .
10 0 3 1 1.75 1 2 2 2 2 2 2 3 4 4 0 19 19 19 19 19 19 22 25 25 2.49 2.49 .
5 1 7 0 3.59 2 2 2 5 5 . . . . . 62 62 62 88 88 . . . . . 2.02 2.02 .
9 1 5 0 2.1 0 0 1 1 2 3 3 3 7 . 0 0 1 1 3 10 10 10 34 . 2.56 2.56 .
5 1 7 1 3.59 3 4 6 8 12 . . . . . 21 27 39 45 69 . . . . . 3.52 2.22 5
6 1 3 0 1.25 4 5 7 9 10 15 . . . . 13 14 21 32 35 55 . . . . 1.53 1.53 .
6 1 4.95 1 3.47 13 13 16 18 23 27 . . . . 235 235 282 312 375 430 . . . .
3.52 3.52 .
8 1 4.95 1 1.81 4 6 8 9 12 13 15 19 . . 6 13 43 68 118 119 157 241 . . 1.94
1.84 3
3 1 4.95 1 3.59 7 7 7 . . . . . . . 281 281 281 . . . . . . . 3.04 3.04 .
6 1 3 0 1.74 1 1 2 3 4 6 . . . . 0 0 3 7 21 27 . . . . 1.72 1.72 .
8 1 5 0 3.19 3 3 3 3 3 3 4 7 . . 8 8 8 8 8 8 14 18 . . 3.04 3.04 .
5 1 5 0 4.29 1 1 3 5 5 . . . . . 6 6 10 17 17 . . . . . 1.58 1.58 .
6 1 7 1 3.41 7 7 8 9 11 12 . . . . 53 53 64 71 85 88 . . . . 3.2 3.2 .
5 1 7 1 4.34 4 5 9 12 16 . . . . . 15 37 79 115 137 . . . . . 3.36 3.36 .
8 1 4.95 1 2.1 7 7 8 9 9 12 12 15 . . 23 23 37 48 48 71 71 75 . . 3.2 3.2 .
9 1 7 0 4.29 1 1 1 1 1 1 3 3 3 . 4 4 4 4 4 4 7 7 7 . 2.56 1.9 9
5 1 4.95 1 4.29 4 8 8 10 13 . . . . . 55 79 79 82 120 . . . . . 2.56 2.72 3
4 1 4.95 0 1.75 2 4 4 7 . . . . . . 8 45 45 55 . . . . . . 1.98 1.98 .
5 1 7 1 4.34 9 9 11 14 15 . . . . . 212 212 267 352 356 . . . . . 3.52 3.52 .
3 1 4.95 0 3.47 7 9 14 . . . . . . . 64 64 124 . . . . . . . 3.84 1.72 3
6 1 4 1 4.34 5 7 10 12 16 19 . . . . 121 154 162 163 259 341 . . . . 4.64 4.64 .
3 0 4 1 1.25 2 2 2 . . . . . . . 7 7 7 . . . . . . . 2.08 2.08 .
4 1 5 0 4.29 0 1 5 8 . . . . . . 0 7 33 46 . . . . . . 2.72 2.72 .
7 1 7 1 3.62 6 11 15 19 24 28 32 . . . 50 74 116 143 155 174 191 . . . 2.1 2.1 .
5 1 4 0 4.29 2 5 5 6 7 . . . . . 31 82 82 90 95 . . . . . 1.53 3.84 5
10 0 6 1 3.34 0 3 3 3 4 5 5 5 6 7 0 58 58 58 60 61 61 61 63 65 3.52 2.1 7
5 1 5 0 4.29 2 2 2 2 3 . . . . . 5 5 5 5 8 . . . . . 2.56 2.56 .
5 1 6 1 3.42 1 2 3 5 5 . . . . . 4 12 21 61 61 . . . . . 1.95 1.95 .
6 1 5 1 3.59 19 21 23 26 29 36 . . . . 112 131 134 159 163 179 . . . . 1.26
1.26 .
4 1 2 0 4.29 4 6 7 7 . . . . . . 18 150 152 152 . . . . . . 3.2 3.2 .
4 1 4 0 4.29 3 4 5 8 . . . . . . 3 4 6 10 . . . . . . 3.2 3.2 .
5 0 5 1 2.1 4 5 5 5 5 . . . . . 9 10 10 10 10 . . . . . 3.04 3.04 .
3 1 7 1 1.8 3 5 7 . . . . . . . 93 114 121 . . . . . . . 1.94 1.94 .
10 0 2 0 4.29 4 4 6 6 13 19 22 27 33 35 107 107 114 114 222 270 316 424 505
566 3.04 3.04 .
3 1 7 0 3.85 9 13 16 . . . . . . . 111 152 164 . . . . . . . 3.2 3.2 .
8 0 5 1 2.1 1 2 2 4 7 7 9 11 . . 18 25 25 32 33 33 36 36 . . 2.1 2.1 .
4 1 4 1 2.26 4 4 5 5 . . . . . . 60 60 67 67 . . . . . . 1.94 1.94 .
5 1 4 1 4.29 6 6 6 8 11 . . . . . 28 28 28 40 53 . . . . . 2.12 2.12 .
4 1 5 0 4.29 2 2 3 12 . . . . . . 6 6 14 39 . . . . . . 3.84 3.84 .
7 1 4.95 1 3.85 5 6 6 7 8 11 11 . . . 42 47 47 51 61 100 100 . . . 3.52 3.36 7
5 1 4 1 4.34 3 3 3 4 5 . . . . . 39 39 39 44 55 . . . . . 1.83 1.83 .
5 1 5 1 2.76 5 7 9 11 15 . . . . . 13 22 53 62 195 . . . . . 2.11 2.11 .
10 0 4.95 0 4.29 0 1 1 1 2 3 4 4 4 4 0 1 1 1 3 3 8 8 8 8 3.84 3.84 .
4 1 4.95 1 2.58 6 6 7 8 . . . . . . 23 23 32 34 . . . . . . 2.88 2.88 .
4 0 7 1 2.12 1 1 4 4 . . . . . . 5 5 16 16 . . . . . . 1.84 1 2
6 1 6 0 3.59 3 6 6 8 8 9 . . . . 34 84 84 177 177 177 . . . . 3.52 2.52 2
6 1 4.95 1 1.81 1 1 1 2 3 4 . . . . 4 4 4 4 5 5 . . . . 1.94 1.94 .
4 1 7 1 3.59 3 3 4 4 . . . . . . 15 15 20 20 . . . . . . 4.64 4.64 .
8 1 7 0 3.85 5 5 6 9 10 11 13 19 . . 58 58 67 109 114 118 131 259 . . 3.52
3.84 4
5 1 7 1 4.29 5 6 7 9 9 . . . . . 43 59 81 92 92 . . . . . 1.89 2.56 5
3 0 3 1 1.38 4 8 9 . . . . . . . 20 34 46 . . . . . . . 1.89 1.89 .
;




----------------
JOBMULT Data Set
----------------

/* Data analyzed in Chapter 8 of P.D.  Allison, "Survival Analysis
   Using the SAS System: A Practical Guide."                        */


data jobmult;
input id event ed j duration prestige logsal;
cards;
1 1 7 1 2.3574626115 27 2.302585093
1 1 7 2 4.5454248125 31 1.3862943611
1 1 7 3 1.0863848663 8 2.0794415417
1 1 7 4 3.5893252019 22 2.8332133441
1 1 7 5 4.6676423688 30 3.4011973817
1 0 7 6 3.753760139 24 3.1354942159
2 0 14 1 20 69 3.3322045102
3 1 16 1 7.3752667661 69 3.5835189385
3 1 16 2 11.263194792 60 3.8501476017
3 0 16 3 1.3615384421 56 3.8286413965
4 1 12 1 1.1435702634 27 2.5649493575
4 1 12 2 0.7879557095 35 2.1972245773
4 1 12 3 1.0437080519 30 2.7725887222
4 1 12 4 0.2345886959 15 2.5649493575
4 1 12 5 0.7982759122 39 3.2188758249
4 1 12 6 1.216753259 41 3.5263605246
4 1 12 7 0.9160367932 24 3.4339872045
4 1 12 8 0.3173837622 26 3.36729583
4 1 12 9 0.6573286654 45 3.8286413965
4 1 12 10 1.7036323919 41 3.9120230054
5 1 9 1 1.4998131721 22 1.9459101491
5 1 9 2 1.4100322042 25 1.3862943611
5 1 9 3 1.1721396761 12 2.302585093
5 1 9 4 2.9705929199 44 3.295836866
5 1 9 5 1.9368951509 20 2.9957322736
5 1 9 6 2.960302413 37 3.6109179126
5 1 9 7 1.0324953553 17 3.1354942159
5 1 9 8 1.8770488965 46 3.6888794541
5 1 9 9 1.7709175213 33 3.36729583
5 1 9 10 2.6266166365 30 3.4011973817
6 0 11 1 20 75 3.4657359028
7 1 13 1 13.401376401 49 3.1780538303
7 0 13 2 6.5986235989 60 3.4965075615
8 1 10 1 9.7241320156 40 2.4849066498
8 0 10 2 10.275867984 49 3.295836866
9 0 12 1 20 72 3.5263605246
10 1 7 1 0.7858511755 40 2.5649493575
10 1 7 2 0.1775990392 10 1.7917594692
10 1 7 3 0.2177831927 12 1.3862943611
10 1 7 4 0.4371186474 16 2.302585093
10 1 7 5 0.4879911093 16 1.6094379124
10 1 7 6 0.4758633156 14 1.3862943611
10 1 7 7 0.3096340975 7 2.1972245773
10 1 7 8 0.2923481637 7 1.0986122887
10 1 7 9 0.3435437703 22 2.8903717579
10 1 7 10 0.5130830586 7 2.7080502011
11 1 13 1 14.477078769 57 3.0445224377
11 0 13 2 5.5229212312 60 3.7135720667
12 0 17 1 20 90 3.5835189385
13 1 11 1 2.6498135583 23 2.302585093
13 1 11 2 2.2640001973 13 2.302585093
13 1 11 3 7.9025713034 51 3.2188758249
13 1 11 4 4.0005145242 39 3.5553480615
13 0 11 5 3.1831004168 45 3.7135720667
14 1 7 1 7.3750186014 39 1.3862943611
14 1 7 2 10.631107228 42 2.3978952728
14 0 7 3 1.9938741703 29 2.1972245773
15 1 11 1 5.9234201639 54 3.0445224377
15 1 11 2 13.004796081 65 3.5553480615
15 0 11 3 1.0717837555 51 3.4657359028
16 0 13 1 20 78 3.6109179126
17 1 11 1 9.074370784 53 2.7725887222
17 0 11 2 10.925629216 41 3.36729583
18 1 11 1 13.525793846 43 2.5649493575
18 0 11 2 6.4742061539 48 2.9444389792
19 1 12 1 1.0881169768 36 3.0445224377
19 1 12 2 1.1219577829 36 3.1780538303
19 1 12 3 0.7718212321 25 2.6390573296
19 1 12 4 2.1439319904 40 3.0445224377
19 1 12 5 1.3360824974 43 3.4965075615
19 1 12 6 1.903271812 35 3.5835189385
19 1 12 7 1.3105737174 34 3.7376696183
19 1 12 8 2.4471136052 47 3.7841896339
19 1 12 9 3.2578308028 54 3.9702919136
19 1 12 10 0.9484471584 24 3.6635616461
20 1 12 1 16.935815839 69 3.0445224377
20 0 12 2 3.0641841609 33 2.4849066498
21 1 10 1 5.8554756448 26 2.7725887222
21 1 10 2 4.726544498 61 3.6109179126
21 0 10 3 9.4179798572 35 3.36729583
22 1 12 1 1.4217010087 39 2.7725887222
22 1 12 2 2.4216911118 36 2.8903717579
22 1 12 3 1.49164587 33 3.36729583
22 1 12 4 0.8770370605 36 3.0910424534
22 1 12 5 1.2741183998 24 3.1354942159
22 1 12 6 2.1037584172 37 3.5263605246
22 1 12 7 0.5553573942 23 2.6390573296
22 1 12 8 1.0485266202 36 3.3322045102
22 1 12 9 1.5060301196 34 3.36729583
22 1 12 10 1.0956467747 18 3.1780538303
23 1 9 1 3.0944371837 44 2.9957322736
23 1 9 2 1.6618345372 9 2.0794415417
23 1 9 3 2.9130625788 25 2.3978952728
23 1 9 4 5.5163227642 38 2.6390573296
23 1 9 5 4.3524113713 39 3.258096538
23 0 9 6 2.4619315649 32 3.4339872045
24 1 14 1 9.7048843458 73 3.5553480615
24 0 14 2 10.295115654 63 3.9318256327
25 1 12 1 4.0036833453 44 2.7725887222
25 1 12 2 2.8361937581 36 2.9444389792
25 1 12 3 1.3686502905 34 2.8332133441
25 1 12 4 6.2115631698 71 3.6109179126
25 1 12 5 5.579265227 48 4.0604430105
25 0 12 6 0.0006442094 25 3.6109179126
26 0 15 1 20 79 3.8501476017
27 1 12 1 9.0833968925 49 3.1354942159
27 1 12 2 6.2262338392 52 3.5835189385
27 0 12 3 4.6903692683 34 3.1780538303
28 1 13 1 7.2214102879 55 3.1780538303
28 1 13 2 12.54020489 61 3.5835189385
28 0 13 3 0.2383848224 58 3.8918202981
29 1 12 1 4.6118670074 56 2.8903717579
29 1 12 2 5.7354790603 34 1.7917594692
29 0 12 3 9.6526539323 60 3.258096538
30 1 9 1 16.3306989 50 3.1780538303
30 0 9 2 3.6693011 35 2.9957322736
31 1 14 1 1.5522937418 44 1.6094379124
31 1 14 2 4.5260644254 47 3.0445224377
31 1 14 3 6.5725981079 54 3.36729583
31 1 14 4 0.887805283 45 3.36729583
31 1 14 5 4.9191638136 64 3.8712010109
31 0 14 6 1.5420746283 54 4.0430512678
32 1 12 1 1.2855006866 48 2.6390573296
32 1 12 2 1.3392188456 14 2.302585093
32 1 12 3 2.2161169291 33 3.295836866
32 1 12 4 0.841555929 16 2.1972245773
32 1 12 5 0.708384274 38 3.0445224377
32 1 12 6 2.3393629545 24 3.0445224377
32 1 12 7 1.2045053654 38 3.5553480615
32 1 12 8 1.90759742 37 3.36729583
32 1 12 9 2.1382598675 33 3.8286413965
32 1 12 10 2.3576232061 29 3.4657359028
33 0 10 1 20 59 2.8903717579
34 1 9 1 2.7902004846 26 2.3978952728
34 1 9 2 1.1238797244 25 1.0986122887
34 1 9 3 3.5242374875 40 2.7725887222
34 1 9 4 2.6254305256 40 2.7080502011
34 1 9 5 2.8477745814 27 2.3978952728
34 1 9 6 3.0311890983 37 2.8903717579
34 1 9 7 2.7522601884 28 3.295836866
34 0 9 8 1.3050279098 30 3.2188758249
35 1 11 1 4.9267560019 42 2.3978952728
35 1 11 2 13.69573644 59 3.4339872045
35 0 11 3 1.3775075583 40 3.5263605246
36 1 8 1 2.6178619389 15 2.302585093
36 1 8 2 3.2827767491 22 2.302585093
36 1 8 3 2.009028988 14 1.3862943611
36 1 8 4 4.1614282466 25 2.0794415417
36 1 8 5 5.869853611 39 3.2188758249
36 0 8 6 2.0590504664 44 3.4011973817
37 1 15 1 14.390504407 67 3.4339872045
37 0 15 2 5.6094955928 60 3.6635616461
38 1 10 1 9.8550629077 44 2.9444389792
38 1 10 2 9.8083657185 50 3.0910424534
38 0 10 3 0.3365713738 46 3.258096538
39 0 17 1 20 83 3.8066624898
40 1 13 1 9.0469706505 46 3.1780538303
40 0 13 2 10.953029349 66 3.7376696183
41 1 13 1 4.9469158427 45 2.8903717579
41 1 13 2 3.3178158119 60 3.2188758249
41 1 13 3 2.7927874912 40 3.4011973817
41 1 13 4 3.1849202911 45 3.8066624898
41 0 13 5 5.7575605631 76 4.189654742
42 1 18 1 6.9245239295 60 3.4657359028
42 1 18 2 11.241556434 47 3.4965075615
42 0 18 3 1.8339196361 82 3.9702919136
43 1 13 1 16.516646281 66 3.4011973817
43 0 13 2 3.4833537194 52 3.5263605246
44 1 12 1 14.655334994 50 2.0794415417
44 0 12 2 5.3446650062 63 3.6888794541
45 0 17 1 20 86 3.9702919136
46 1 7 1 0.6982712461 22 1.9459101491
46 1 7 2 0.1934757003 6 0.6931471806
46 1 7 3 0.2951048898 11 0
46 1 7 4 0.362310504 2 1.6094379124
46 1 7 5 0.5149615774 1 2.302585093
46 1 7 6 0.5211151875 3 2.302585093
46 1 7 7 0.5021211243 2 2.302585093
46 1 7 8 0.3705193829 7 2.302585093
46 1 7 9 0.3376985812 1 1.3862943611
46 1 7 10 0.2360358907 10 1.6094379124
47 1 16 1 19.427755141 74 3.5835189385
47 0 16 2 0.5722448594 71 4.0430512678
48 0 17 1 20 92 3.7841896339
49 0 18 1 20 84 3.9318256327
50 0 9 1 20 41 2.6390573296
51 1 18 1 0.749543437 56 3.295836866
51 1 18 2 1.2168773087 53 3.4339872045
51 1 18 3 1.7949759822 58 3.8066624898
51 1 18 4 1.7951928796 59 4.276666119
51 1 18 5 1.700249155 64 4.262679877
51 1 18 6 0.3601813147 51 4.1743872699
51 1 18 7 0.6049352178 33 3.7841896339
51 1 18 8 1.2953429776 61 4.0775374439
51 1 18 9 0.9890339554 61 4.1743872699
51 1 18 10 1.8021668639 64 4.262679877
52 1 13 1 10.155096166 53 2.9444389792
52 1 13 2 7.7753283776 61 3.4965075615
52 0 13 3 2.0695754559 71 3.9120230054
53 1 6 1 0.3656874709 27 2.302585093
53 1 6 2 1.0999652678 28 2.0794415417
53 1 6 3 1.1498443162 1 2.6390573296
53 1 6 4 1.4251210208 26 2.3978952728
53 1 6 5 2.4599371188 26 3.0445224377
53 1 6 6 0.733468248 13 2.6390573296
53 1 6 7 1.5824684947 8 3.0445224377
53 1 6 8 3.8370223734 43 3.4011973817
53 1 6 9 1.6434142816 30 3.295836866
53 1 6 10 0.7876457229 14 3.258096538
54 0 15 1 20 70 3.5263605246
55 0 13 1 20 65 3.36729583
56 1 12 1 14.101754191 68 3.0445224377
56 0 12 2 5.8982458087 67 3.9889840466
57 1 13 1 8.345196772 48 0.6931471806
57 1 13 2 4.5265631157 51 2.7080502011
57 0 13 3 7.1282401122 64 3.4011973817
58 1 10 1 15.600883216 48 3.0910424534
58 1 10 2 4.1113722853 31 2.8903717579
58 0 10 3 0.287744499 42 2.8332133441
59 1 13 1 7.9440040454 46 2.8332133441
59 1 13 2 8.982437126 59 3.5835189385
59 0 13 3 3.0735588286 69 3.9120230054
60 0 17 1 20 88 3.4965075615
61 0 14 1 20 70 2.9444389792
62 1 15 1 2.9058629154 37 3.258096538
62 1 15 2 8.0684526898 41 3.2188758249
62 0 15 3 9.0256843948 61 3.5835189385
63 0 14 1 20 68 3.5835189385
64 0 13 1 20 92 3.6635616461
65 1 7 1 1.406837144 8 2.302585093
65 1 7 2 1.2676293166 16 1.9459101491
65 1 7 3 0.538889355 5 2.302585093
65 1 7 4 0.8363605868 16 2.3978952728
65 1 7 5 2.8354298986 30 2.9957322736
65 1 7 6 1.7423978154 12 2.6390573296
65 1 7 7 3.5374286944 34 3.3322045102
65 1 7 8 2.5838335523 15 3.3322045102
65 1 7 9 0.7476350325 12 1.7917594692
65 1 7 10 1.186272178 25 3.1354942159
66 1 16 1 16.343122803 52 3.0445224377
66 0 16 2 3.6568771967 65 3.6375861597
67 1 13 1 2.4099606192 63 2.7725887222
67 1 13 2 5.280058479 45 2.4849066498
67 1 13 3 3.8853916754 54 3.5835189385
67 1 13 4 2.5185630834 33 3.2188758249
67 0 13 5 5.906026143 63 3.9889840466
68 1 9 1 18.195760633 56 2.7725887222
68 0 9 2 1.8042393672 34 2.6390573296
69 1 11 1 7.4964164268 63 3.8286413965
69 1 11 2 11.308277802 53 3.6635616461
69 0 11 3 1.1953057716 57 3.5553480615
70 1 16 1 15.488624707 80 3.295836866
70 0 16 2 4.5113752933 45 3.7135720667
71 1 13 1 3.2089437483 47 2.6390573296
71 1 13 2 2.3304162612 40 2.8903717579
71 1 13 3 3.393344306 50 3.1780538303
71 1 13 4 1.9042285987 58 3.4339872045
71 1 13 5 8.5706596688 66 4.1743872699
71 0 13 6 0.592407417 38 3.8066624898
72 1 12 1 0.9154048548 53 2.5649493575
72 1 12 2 0.5613665122 29 0.6931471806
72 1 12 3 1.6328504732 35 2.7725887222
72 1 12 4 1.8698609504 35 2.7725887222
72 1 12 5 0.4727123233 34 3.258096538
72 1 12 6 1.4701917067 35 3.295836866
72 1 12 7 1.3694821426 39 3.0445224377
72 1 12 8 2.0069155267 46 3.5835189385
72 1 12 9 1.4135908445 46 3.6888794541
72 1 12 10 1.6831131431 23 3.6109179126
73 0 12 1 20 63 3.6375861597
74 0 12 1 20 85 3.5835189385
75 1 9 1 0.5463555146 20 2.302585093
75 1 9 2 0.8124376489 32 0
75 1 9 3 0.6906859695 29 2.3978952728
75 1 9 4 0.5308904173 24 2.8903717579
75 1 9 5 0.4346508375 15 2.5649493575
75 1 9 6 0.4139245029 16 1.0986122887
75 1 9 7 0.889679158 23 3.0445224377
75 1 9 8 1.2310301388 35 3.36729583
75 1 9 9 2.9595257809 33 3.5835189385
75 1 9 10 3.0667780915 41 3.7612001157
76 1 8 1 0.4812668529 10 2.302585093
76 1 8 2 0.3942806422 16 2.302585093
76 1 8 3 0.4367206982 14 2.5649493575
76 1 8 4 0.3741086295 1 2.302585093
76 1 8 5 0.2168065086 22 1.3862943611
76 1 8 6 0.409334904 9 2.6390573296
76 1 8 7 0.4750352023 24 3.4965075615
76 1 8 8 0.7970753685 28 3.4965075615
76 1 8 9 0.6013213419 15 2.9957322736
76 1 8 10 0.7144690485 30 3.6375861597
77 1 11 1 2.4897747814 34 2.8332133441
77 1 11 2 3.0103588886 43 3.2188758249
77 1 11 3 3.1554533203 25 2.9957322736
77 1 11 4 4.1387434586 41 3.2188758249
77 1 11 5 5.2891325849 50 3.8286413965
77 0 11 6 1.9165369661 51 3.8501476017
78 1 8 1 4.7373520188 41 2.9957322736
78 1 8 2 0.7933330236 36 1.9459101491
78 1 8 3 2.9626886269 26 1.7917594692
78 1 8 4 6.5665093662 37 2.8332133441
78 1 8 5 2.3091619439 40 3.0910424534
78 0 8 6 2.6309550206 40 3.4965075615
79 1 11 1 4.8514354998 43 2.8332133441
79 1 11 2 3.1333235134 26 2.4849066498
79 1 11 3 5.266379841 42 3.0445224377
79 1 11 4 4.578441651 47 2.9957322736
79 0 11 5 2.1704194947 44 3.258096538
80 1 13 1 17.490693941 57 2.9444389792
80 0 13 2 2.5093060594 54 3.4965075615
81 1 15 1 1.7521478773 43 1.7917594692
81 1 15 2 1.7385618522 47 3.3322045102
81 1 15 3 2.9180152587 40 3.4339872045
81 1 15 4 1.5409824667 36 3.4011973817
81 1 15 5 2.9999190644 42 3.7841896339
81 1 15 6 2.0314499785 49 3.8918202981
81 1 15 7 2.3050527661 47 3.8712010109
81 1 15 8 4.2800686532 51 4.0604430105
81 0 15 9 0.433802083 26 3.7376696183
82 0 9 1 20 48 3.1354942159
83 1 12 1 1.5953577765 42 2.302585093
83 1 12 2 1.2119014547 39 2.8332133441
83 1 12 3 3.0117136966 47 3.4339872045
83 1 12 4 2.9956128927 42 3.6635616461
83 1 12 5 4.5970441185 38 3.5835189385
83 1 12 6 2.6017363881 46 3.6635616461
83 1 12 7 3.7007545501 44 3.6375861597
83 0 12 8 0.2858791228 39 3.8066624898
84 1 10 1 2.7648575267 33 2.7725887222
84 1 10 2 1.9521486137 35 2.3978952728
84 1 10 3 4.530573523 39 2.4849066498
84 1 10 4 1.7559163519 31 0.6931471806
84 1 10 5 2.5021550036 46 3.4339872045
84 1 10 6 2.7090250409 23 3.258096538
84 1 10 7 2.9435560938 33 3.1780538303
84 0 10 8 0.8417678464 44 3.8712010109
85 1 14 1 8.9430452773 68 3.295836866
85 0 14 2 11.056954723 54 3.4011973817
86 1 8 1 2.0952352667 34 0.6931471806
86 1 8 2 3.2976189619 35 2.4849066498
86 1 8 3 3.9059326384 41 2.302585093
86 1 8 4 2.8459288742 17 2.3978952728
86 1 8 5 6.3708088237 48 3.4657359028
86 0 8 6 1.4844754352 35 3.5835189385
87 0 15 1 20 67 3.4965075615
88 1 11 1 5.9056198358 49 2.8903717579
88 1 11 2 8.7417858444 39 2.4849066498
88 0 11 3 5.3525943198 42 2.8332133441
89 0 13 1 20 70 3.0445224377
90 0 17 1 20 90 3.7841896339
91 1 13 1 2.2470322542 52 2.8903717579
91 1 13 2 1.5656360361 46 3.258096538
91 1 13 3 2.5223373832 47 3.7612001157
91 1 13 4 2.0624744478 37 3.6109179126
91 1 13 5 1.8294250041 41 3.4965075615
91 1 13 6 0.8574360022 40 3.7376696183
91 1 13 7 1.227431173 46 3.9512437186
91 1 13 8 1.5179675391 26 3.6109179126
91 1 13 9 2.3146135253 51 3.8286413965
91 1 13 10 1.4915164307 35 3.7376696183
92 0 12 1 20 86 3.5263605246
93 1 14 1 4.2010132153 38 2.5649493575
93 0 14 2 15.798986785 72 3.4339872045
94 0 13 1 20 66 3.9318256327
95 0 12 1 20 51 2.8903717579
96 1 11 1 9.5122953936 53 2.7080502011
96 1 11 2 6.8875988508 45 3.258096538
96 0 11 3 3.6001057556 48 3.4657359028
97 1 10 1 1.0598622483 47 2.7080502011
97 1 10 2 0.991527639 33 2.7725887222
97 1 10 3 0.9966257462 15 2.302585093
97 1 10 4 1.2119716962 34 3.295836866
97 1 10 5 0.6998590473 26 3.0445224377
97 1 10 6 1.1562350088 30 3.0445224377
97 1 10 7 1.3409627242 19 2.9957322736
97 1 10 8 3.0876458188 44 3.5263605246
97 1 10 9 0.845663316 28 3.4011973817
97 1 10 10 1.1537511605 34 3.3322045102
98 1 9 1 1.5737475702 8 2.302585093
98 1 9 2 2.4057024749 34 2.1972245773
98 1 9 3 4.4160894504 42 3.258096538
98 1 9 4 3.1014497063 33 3.0910424534
98 1 9 5 0.8820722451 10 1.7917594692
98 1 9 6 1.1721615955 34 2.9444389792
98 1 9 7 1.370730855 31 2.9957322736
98 1 9 8 2.6569946404 45 3.5553480615
98 0 9 9 2.4210514623 38 3.7376696183
99 0 16 1 20 78 3.36729583
100 1 10 1 2.5168290804 38 1.3862943611
100 1 10 2 2.2938721332 30 2.7725887222
100 1 10 3 4.1596703242 34 2.8903717579
100 1 10 4 2.275813045 28 2.3978952728
100 1 10 5 3.5801071035 50 3.4011973817
100 1 10 6 5.0533967186 41 3.5263605246
100 0 10 7 0.120311595 56 3.8066624898
;







*************************************************************************
*************************************************************************

PROGRAMS


---------
Chapter 3
---------

/* The following program is found on page 31 of */
   "Survival Analysis Using the SAS System."    */

data myel;
   input dur status treat renal;
   cards;
   8       1        1        1
 180       1        2        0
 632       1        2        0
 852       0        1        0
  52       1        1        1
2240       0        2        0
 220       1        1        0
  63       1        1        1
 195       1        2        0
  76       1        2        0
  70       1        2        0
   8       1        1        0
  13       1        2        1
1990       0        2        0
1976       0        1        0
  18       1        2        1
 700       1        2        0
1296       0        1        0
1460       0        1        0
 210       1        2        0
  63       1        1        1
1328       0        1        0
1296       1        2        0
 365       0        1        0
  23       1        2        1
run;

proc lifetest data=myel;
   time dur*status(0);
run;



/* The following programs are found on page 34 of */
/* "Survival Analysis Using the SAS System."      */

proc lifetest data=myel plots=(s) graphics;
   time dur*status(0);
   symbol1 v=none;
run;




proc lifetest data=myel outsurv=a;
   time dur*status(0);
run;



/* The following program is found on page 35 of  */
/* "Survival Analysis Using the SAS System."     */

proc print data=a;
run;



/* The following program is found on page 36 of  */
/* "Survival Analysis Using the SAS System."     */

proc lifetest data=myel plots=(s) graphics;
   time dur*status(0);
   strata treat;
   symbol1 v=none color=black line=1;
   symbol2 v=none color=black line=2;
run;



/* The following program is found on page 43 of  */
/* "Survival Analysis Using the SAS System."     */

proc lifetest data=recid method=life;
   time week*arrest(0);
run;




/* The following program is found on pages 47-48 of */
/* "Survival Analysis Using the SAS System."        */

data;
   set recid;
   if arrest=0 then week=53;
run;

proc lifetest method=life plots=(s,h) graphics
              intervals=10 20 30 40 50 53;
   time week*arrest(0);
run;




/* The following program is found on pages 48-49 of */
/* "Survival Analysis Using the SAS System."        */

data;
   input time status number;
   cards;
25 1 16
25 0 3
75 1 11
75 0 0
150 1 4
150 0 2
300 1 5
300 0 4
550 1 2
550 0 6
850 1 4
850 0 3
1150 1 1
1150 0 2
1450 1 1
1450 0 3
1700 1 0
1700 0 1
;

proc lifetest method=life intervals=50 100 200 400 700
              1000 1300 1600 plots=(s,h) graphics;
   time time*status(0);
   freq number;
run;




/* The following program is found on page 52 of */
/* "Survival Analysis Using the SAS System."    */

proc lifetest data=recid;
   time week*arrest(0);
   test fin age race wexp mar paro prio;
run;



/* The following program is found on page 55 of */
/* "Survival Analysis Using the SAS System."    */

proc lifetest data=renal;
   time dur*censor(0);
   strata renal;
   test treat;
run;




/* The following program is found on page 58 of */
/* "Survival Analysis Using the SAS System."    */

proc lifetest outsurv=a data=recid;
   time week*arrest(0);
run;

%smooth(data=a,time=week,width=8)



---------
Chapter 4
---------

/* The following program is found on page 64 of */
/* "Survival Analysis Using the SAS System."    */

proc lifereg data=recid;
   model week*arrest(0)=fin age race wexp mar paro prio
         / dist=lnormal;
run;


/* The following program is found on page 76 of */
/* "Survival Analysis Using the SAS System."    */

proc lifereg data=recid;
  model week*arrest(0)=fin age race wexp
        mar paro prio /dist=gamma noshape1 shape1=.811
        noscale scale=.811;
run;




/* The following program is found on page 78 of */
/* "Survival Analysis Using the SAS System."    */

proc lifereg data=recid;
   class educ;
   model week*arrest(0)=fin age race wexp mar paro
         prio educ/dist=weibull covb;
run;



/* The following program is found on page 86 of */
/* "Survival Analysis Using the SAS System."    */

model week*arrest(0)= / dist=weibull;




/* The following program is found on page 88 of */
/* "Survival Analysis Using the SAS System."    */

if educ = 3 then educ = 4;




/* The following program is found on pages 92-93 of */
/* "Survival Analysis Using the SAS System."        */

proc lifetest data=recid outsurv=a;
   time week*arrest(0);
run;

data;
   set a;
   s=survival;
   logit=log((l-s)/s);
   lnorm=probit(l-s);
   lweek=log(week);
run;

proc gplot;
   symbol1 value=none i=join;
   plot logit*lweek lnorm*lweek;
run;




/* The following program is found on page 95 of */
/* "Survival Analysis Using the SAS System."    */

proc lifereg data=recid;
   model week*arrest(0)=fin age race wexp mar paro prio
         / dist=weibull;
   output out=a cdf=f;
run;

data b;
   set a;
   e=-log(l-f);
run;

proc lifetest data=b plots=(ls) notable graphics;
   time e*arrest(0);
   symbol1 v=none;
run;




/* The following program is found on page 98 of */
/* "Survival Analysis Using the SAS System."    */

data;
   set recidlft;

       /* uncensored cases: */
   if arrest=1 and week ne . then do;
      upper=week;
      lower=week;
   end;

      /* left-censored cases: */
   if arrest=1 and week = . then do;
      upper=52;
      lower=.;
   end;

      /* right-censored cases: */
   if arrest=0 then do;
      upper=.;
      lower=52;
   end;
run;

proc lifereg;
   model (lower,upper)=fin age race wexp mar paro prio
         / dist=weibull;
run;




/* The following program is found on pages 99-100 of */
/* "Survival Analysis Using the SAS System."         */

data;
  set recid;

      /* interval censored cases: */
   if arrest=1 then do;
      upper=week;
      lower=week-.9999;
   end;

      /* right-censored cases: */
   if arrest=0 then do;
      upper=.;
      lower=52;
   end;

proc lifereg;
   model (lower, upper)=fin age race wexp mar paro prio
         / dist=weibull;
run;



/* The following program is found on page 101 of */
/* "Survival Analysis Using the SAS System."     */

proc lifereg data=recid;
   model week*arrest(0)=fin age race wexp mar paro prio
         / dist=weibull;
   output out=a p=median std=s;
run;

proc print data=a;
   var week arrest _prob_ median s;
run;




/* The following program is found on page 102 of */
/* "Survival Analysis Using the SAS System."     */

proc lifereg data=recid outest=a;
   model week*arrest(0) = fin age race wexp mar paro prio
         / dist=weibull;
   output out=b xbeta=lp;
run;

%predict(outest=a,out=b,xbeta=lp,time=30)




/* The following program is found on page 103 of */
/* "Survival Analysis Using the SAS System."     */

%lifehaz(outest=a,out=b,xbeta=lp)




/* The following programs are found on page 106 of */
/* "Survival Analysis Using the SAS System."       */

data quarter;
   set recid;
   quarter=ceil(week/13);
   do j=1 to quarter;
      time=13;
      event=0;
        if j=quarter and arrest=1 then do;
                event=1;
                time=week-13*(quarter-1);
        end;
        output;
   end;
run;






proc lifereg data=quarter;
   class j;
   model time*event(0)=fin age race wexp mar paro prio j
         / dist=exponential covb;
run;




/* The following programs are found on page 108 of */
/* "Survival Analysis Using the SAS System."       */

ltime=log(time);






proc genmod data=quarter;
   class j;
   model event=fin age race wexp mar paro prio j j*fin
         / dist=poisson link=log offset=ltime type3;
run;







---------
Chapter 5
---------

/* The following program is found on page 115 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=recid;
   model week*arrest(0)=fin age race wexp mar paro prio;
run;




/* The following program is found on page 119 of */
/* "Survival Analysis Using the SAS System."     */

data stan;
   infile 'c: stan.dat';
   input dob mmddyy9. doa mmddyy9. dot mmddyy9. dls mmddyy9.
         dead surg m1 m2 m3;
   surv1=dls-doa;
   surv2=dls-dot;
   ageaccpt=(doa-dob)/365.25;
   agetrans=(dot-dob)/365.25;
   wait=dot-doa;
   if dot=. then trans=0; else trans=1;
run;


proc phreg data=stan;
   model surv1*dead(0)=trans surg ageaccpt;
run;



/* The following program is found on page 121 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=stan;
   where trans=1;
   model surv2*dead(0)=surg m1 m2 m3 agetrans wait dot;
run;




/* The following program is found on page 130 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=recid;
   model week*arrest(0)=fin age race wexp mar paro prio
         / ties=exact;
run;




/* The following program is found on page 139 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=stan;
   model surv1*dead(0)=plant surg ageaccpt / ties=exact;
   if wait>surv1 or wait=. then plant=0; else plant=1;
run;




/* The following program is found on page 142 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=stan;
   model surv1*dead(0)=plant surg age / ties=exact;
   if wait>surv1 or wait=. then plant=0; else plant=1;
   age=ageaccpt+surv1;
run;




/* The following program is found on page 143 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=stan;
   model surv1*dead(0)=plant surg logage / ties=exact;
   if wait>surv1 or wait=. then plant=0; else plant=1;
   logage=log(ageaccpt+surv1);
run;



/* The following programs are found on page 144 of */
/* "Survival Analysis Using the SAS System."       */

data recid;
   infile 'c:recid.dat';
   input week arrest fin age race wexp mar paro prio emp1-emp52;
run;






proc phreg data=recid;
   model week*arrest(0)=fin age race wexp mar paro prio employed
         / ties=efron;
   array emp(*) emp1-emp52;
   do i=1 to 52;
      if week=i then employed=emp(i);
   end;
run;






proc phreg data=recid;
   model week*arrest(0)=fin age race wexp mar paro prio employed
         / ties=efron;
   array emp(*) emp1-emp52;
   employed=emp(week);
run;




/* The following program is found on page 145 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg;
   where week>1;
   model week*arrest(0)=fin age race wexp mar paro prio employed
         / ties=efron;
   array emp(*) emp1-emp52;
   employed=emp(week-1);
run;




/* The following programs are found on page 146 of */
/* "Survival Analysis Using the SAS System."       */

proc phreg;
   where week>2;
   model week*arrest(0)=fin age race wexp mar paro prio employ1
         employ2 / ties=efron;
   array emp(*) emp1-emp52;
   employ1=emp(week-1);
   employ2=emp(week-2);
run;






data recidcum;
   set recid;
   array emp(*) emp1-emp52;
   array cum(*) cum1-cum52;
   cum1=emp1;
   do i=2 to 52;
      cum(i)=cum(i-1) + emp(i);
   end;
   do i=1 to 52;;
      cum(i)=cum(i)/i;
   end;
run;
proc phreg data=recidcum;
   where week>1;
   model week*arrest(0)=fin age race wexp mar paro prio employ
         / ties=efron;
   array cumemp(*) cum1-cum52;
   employ=cumemp(week-1);
run;




/* The following programs are found on page 148 of */
/* "Survival Analysis Using the SAS System."       */

data blood;
   infile 'blood.dat';
   input deathday status alb1-alb12;
run;

proc phreg;
   model deathday*status(0)=albumin;
   array alb(*) alb1-alb12;
   deathmon=ceil(deathday/30.4);
   albumin=alb(deathmon);
run;






proc phreg data=blood;
   model deathday*status(0)=albumin;
   array alb(*) alb1-alb12;
   deathmon=deathday/30.4;
   j=ceil(deathmon);
   if j=1 then albumin=alb(1);
   else albumin=alb(j)+(alb(j)-alb(j-1))*(deathmon-j+1);
run;





/* The following program is found on page 149 of */
/* "Survival Analysis Using the SAS System."     */

data data=blood;
   set;
   array alb(*) alb1-alb12;
   array meanalb(*) mean1-mean12;
   array predalb(*) pred1-pred12;
   pred1=alb1;
   mean1=alb1;
   do i=2 to 12;
      meanalb(i)=(1/i)*alb(i)+(1-1/i)*meanalb(i-1);
      predalb(i)=.7*alb(i)+.3*meanalb(i-1));
   end;
run;

proc phreg;
   model deathday*status(0)=albumin;
   array pred(*) pred1-pred12;
   deathmon=ceil(deathday/30.4);
   albumin=pred(deathmon);
run;




/* The following program is found on page 152 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=alco;
   model surv*dead(0)=pt;
   time1=0;
   array time(*) time1-time10;
   array p(*) pt1-pt10;
   do j=1 to 10;
   if surv ge time(j) and time(j) ne . then pt=p(j);
   end;
run;




/* The following program is found on page 153 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=stan;
   model surv1*dead(0)=surg ageaccpt plant m1td m2td m3td
         waittd dottd / ties=exact;
   if wait>surv1 or wait=. then plant=0; else plant=1;
   if plant=1 then do;
      m1td=m1;
      m2td=m2;
      m3td=m3;
      waittd=wait;
      dottd=dot;
   end;
   else do;
      m1td=0;
      m2td=0;
      m3td=0;
      waittd=0;
      dottd=0;
   end;
run;





/* The following program is found on page 156 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=recid;
   model week*arrest(0)=fin age race wexp mar paro prio fintime
         / ties=efron;
   fintime=fin*week;
run;




/* The following program is found on page 157 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=recid;
   model week*arrest(0)=fin age race wexp mar paro prio fintime
         / ties=efron;
   fintime=fin*(week>13);
run;




/* The following program is found on page 158 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=myel;
   model dur*stat(0)=treat / ties=exact;
   strata renal;
run;




/* The following programs are found on page 162 of */
/* "Survival Analysis Using the SAS System."       */

data stan2;
   set stan;
   agels=(dls-dob)/365.25;
run;






proc phreg data=stan2;
   model (ageaccpt,agels)*dead(0)=surg ageaccpt / ties=exact;
run;




/* The following programs are found on page 163 of */
/* "Survival Analysis Using the SAS System."       */

ageaccpt=ageaccpt-.0027;






proc phreg data=stan2;
   model agels*dead(0)=surgtd ageaccpt / ties=exact;
   if agels<ageaccpt then surgtd=.;
   else surgtd=surg;
run;






proc phreg data=stan2;
   model agels*dead(0)=surg ageaccpt plant / ties=exact;
   if agels<agetrans or agetrans=. then plant=0;
   else plant=1;
   if agels<ageaccpt then plant=.;
run;




/* The following program is found on page 165 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=recid;
   model week*arrest(0)=fin age prio
         / ties=efron;
   baseline out=a survival=s logsurv=ls loglogs=lls;
run;

proc print data=a;
run;




/* The following program is found on page 167 of */
/* "Survival Analysis Using the SAS System."     */

data b;
   set a;
   ls=-ls;
run;

proc gplot data=b;
   symbol1 value=none interpol=join;
   plot ls*week;
run;




/* The following program is found on page 168 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=recid;
   model week*arrest(0)=age prio / ties=efron;
   strata fin;
   baseline out=a loglogs=lls survival=s;
run;

proc gplot data=a;
   plot lls*week=fin;
   symbol1 interpol=join color=black line=1;
   symbol2 interpol=join color=black line=2;
run;




/* The following programs are found on page 171 of */
/* "Survival Analysis Using the SAS System."       */

proc phreg data=recid;
   model week*arrest(0)=fin finmid age prio / ties=efron;
   mid=(20<week<30);
   finmid=fin*mid;
run;



data covals;
   input fin age prio;
   cards;
0 40 3
run;




/* The following program is found on page 172 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=recid;
   model week*arrest(0)=fin age prio /
         ties=efron;
   baseline out=a covariates=covals survival=s lower=lcl
         upper=ucl / nomean;
run;

proc print data=a;
run;




/* The following program is found on page 174 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=recid;
   model week*arrest(0)=fin age prio / ties=efron;
   output out=c resdev=dev;
run;

proc gplot data=c;
   symbol1 value=dot h=.2;
    plot dev*age;
run;




/* The following program is found on page 176 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=recid;
   model week*arrest(0)=fin age prio /
         ties=efron;
  output out=b ressch=schfin schage schprio;
run;

proc print data=b;
run;




/* The following program is found on page 177 of */
/* "Survival Analysis Using the SAS System."     */

proc gplot data=b;
   plot schfin*week schprio*week schage*week;
   symbol1 value=dot h=.02;
run;




/* The following program is found on page 180 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=myel;
   model dur*status(0)=treat renal;
   id id;
   output out=c ld=ldmyel dfbeta=dtreat drenal;
run;




/* The following program is found on page 182 of */
/* "Survival Analysis Using the SAS System."     */

data recid2;
   set recid;
   ed3=(educ=3);
   ed4=(educ=4);
   ed5=(educ=5);
   ed6=(educ=6);
run;

proc phreg data=recid2;
   model week*arrest(0)=fin age prio ed3-ed6 / ties=efron;
   No_Educ: test ed3,ed4,ed5,ed6;
   Ed3_Ed6: test ed3=ed6;
   Ed4_Ed6: test ed4=ed6;
run;




---------
Chapter 6
---------

/* The following program is found on page 191 of */
/* "Survival Analysis Using the SAS System."     */

proc lifetest data=leaders notable outsurv=a;
   time years*lost(0,2,3);
run;

proc lifetest data=leaders notable outsurv=b;
   time years*lost(0,1,3);
run;

proc lifetest data=leaders notable outsurv=c;
   time years*lost(0,1,2);
run;

data combined;
   set a b c;
   retain outcome 0;
   if years=0 and survival=1 then outcome=outcome+1;
   lls=log(-log(survival));
run;

proc gplot data=combined;
   where _censor_=0;
   symbol1 interpol=join color=black v=none line=1;
   symbol2 interpol=join color=black v=none line=2;
   symbol3 interpol=join color=black v=none line=8;
   plot lls*years=outcome;
run;




/* The following program is found on page 192 of */
/* "Survival Analysis Using the SAS System."     */

%smooth(data=combined,time=years,width=4)




/* The following program is found on page 193 of */
/* "Survival Analysis Using the SAS System."     */

proc catmod data=leaders;
   where lost ne 0;
   direct years;
   model lost=years / noprofile;
run;




/* The following program is found on page 195 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=leaders;
   model years*lost(0)=manner start military age conflict
         loginc growth pop land literacy / ties=efron;
   strata region;
run;

proc phreg data=leaders;
   model years*lost(0,1,2)=manner start military age conflict
         loginc growth pop land literacy / ties=efron;
   strata region;
run;

proc phreg data=leaders;
   model years*lost(0,1,3)=manner start military age conflict
         loginc growth pop land literacy / ties=efron;
   strata region;
run;

proc phreg data=leaders;
   model years*lost(0,2,3)=manner start military age conflict
         loginc growth pop land literacy / ties=efron;
   strata region;
run;





/* The following program is found on page 201 of */
/* "Survival Analysis Using the SAS System."     */

data leaders2;
   set leaders;
   lower=years;
   upper=years;
   if years=0 then do;
      lower=.;
      upper=1;
   end;
   if lost in (0,1,2) then upper=.;
run;

proc lifereg data=leaders2;
   model (lower,upper)= / d=exponential;
run;




/* The following program is found on page 205 of */
/* "Survival Analysis Using the SAS System."     */

data leaders3;
   set leaders;
   lyears=log(years+.5);
run;

proc probit data=leaders3;
   where lost=1 or lost=3;
   class lost region;
   model lost=lyears manner age start military conflict loginc
         literacy region / d=logistic;
run;




/* The following program is found on page 207 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=leaders;
   model years*lost(0,2)=manner age start military conflict
      loginc literacy / ties=efron;
   strata region;
run;


---------
Chapter 7
---------

/* The following program is found on page 213 of */
/* "Survival Analysis Using the SAS System."     */

data jobyrs;
   set jobdur;
   do year=1 to dur;
      if year=dur and event=1 then quit=1;
      else quit=2;
      output;
   end;
run;




/* The following program is found on page 214 of */
/* "Survival Analysis Using the SAS System."     */

proc probit data=jobyrs;
   class year quit;
   model quit=ed prestige salary year / d=logistic;
run;




/* The following program is found on page 217 of */
/* "Survival Analysis Using the SAS System."     */

data jobyrs2;
   quit=2-quit;
   n=1;
run;

proc genmod data=jobyrs2;
   class year;
   model quit/n=ed prestige salary year / d=binomial
         link=cloglog type3;
run;




/* The following program is found on page 219 of */
/* "Survival Analysis Using the SAS System."     */

model quit/n=ed prestige salary year salary*year
      / d=binomial link=cloglog type3;




/* The following program is found on pages 220-221 of */
/* "Survival Analysis Using the SAS System."          */

data rankyrs;
   infile 'c:rank.dat';
   input dur event undgrad phdmed phdprest art1-art10
         cit1-cit10 prest1 prest2 jobtime;
   array arts(*) art1-art10;
   array cits(*) cit1-cit10;
   if jobtime=. then jobtime=11;
   do year=1 to dur;
      if year=dur and event=1 then promo=1;
         else promo=0;
      if year ge jobtime then prestige=prest2;
         else prestige=prest1;
      articles=arts(year);
      citation=cits(year);
      year2=year*year;
      output;
   end;
run;




/* The following program is found on page 221 of */
/* "Survival Analysis Using the SAS System."     */

proc logistic descending data=rankyrs;
   model promo=undgrad phdmed phdprest articles citation
         prestige year year2;
run;




/* The following program is found on page 226 of */
/* "Survival Analysis Using the SAS System."     */

if year=22 then year=21;




/* The following programs are found on page 221 of */
/* "Survival Analysis Using the SAS System."       */

data jobyrs2;
   set jobdur;
   do year=1 to dur;
      if year=dur and event=1 then outcome=1;
      else if year=dur and event=2 then outcome=2;
      else outcome=3;
      output;
   end;
run;






proc catmod data=jobyrs2;
   direct ed prestige salary year;
   model outcome=ed prestige salary year / noprofile noiter;
run;




/* The following program is found on page 229 of */
/* "Survival Analysis Using the SAS System."     */

proc logistic data=jobyrs2;
   where outcome ne 2;
   model outcome=ed prestige salary year;
run;

proc logistic data=jobyrs2;
   where outcome ne 1;
   model outcome=ed prestige salary year;
run;




/* The following program is found on page 238 of */
/* "Survival Analysis Using the SAS System."     */

proc sort data=jobmult;
   by j;
run;

proc phreg data=jobmult;
   model duration*event(0)=prestige logsal ed;
   by j;
run;




/* The following program is found on page 242 of */
/* "Survival Analysis Using the SAS System."     */

%wlw(data=jobmult,dv=duration*event(0),cv=prestige logsal
    ed,evcnt=j,id=id,max=9,ties=efron)




/* The following program is found on page 244 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=jobmult nosummary;
   model duration*event(0)=prestige logsal;
   strata id;
run;




/* The following program is found on page 247 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=strtstop;
   model (start,stop)*event(0)=prestige logsal ed;
run;




/* The following program is found on page 250 of */
/* "Survival Analysis Using the SAS System."     */

proc phreg data=leaders;
   model years*lost(0)=manner age start military conflict
         loginc literacy / ties=efron;
   strata region;
run;




/* The following program is found on page 251 of */
/* "Survival Analysis Using the SAS System."     */

data leaders4;
   set leaders;
   if lost=2 then years=24;
run;

proc phreg data=leaders4;
   model years*lost(0,2)=manner age start military conflict                                loginc literacy / ties=efron;
   strata region;
run;

*************************************************************************
*************************************************************************

MACROS
_________________________________________________________________________


------------
SMOOTH Macro
------------

%macro smooth (data=_last_, time=, width=, survival=survival);

/*********************************************************************
MACRO SMOOTH produces graphs of smoothed hazard functions using output
from either PROC LIFETEST or PROC PHREG. With PROC LIFETEST, it uses the
data set produced by the OUTSURV option in the PROC statement. With PROC
PHREG, it uses the data set produced by the BASELINE statement. SMOOTH
employs a kernel smoothing method described by H. Ramlau-Hansen (1983),
"Smoothing Counting Process Intensities by Means of Kernel Functions,"
The Annals of Statistics 11, 453-466. If there is more than one survival
curve in the input data set, SMOOTH will produce multiple smoothed
hazard curves on the same axes.

There are four parameters:

DATA     is the name of the data set containing survivor function
         estimates. The default is the most recently created data set.

TIME     is name of the variable containing event times.

SURVIVAL is the name of a variable containing survivor function
         estimates (the default is SURVIVAL, which is the automatic name in
         PROC LIFETEST).

WIDTH    is bandwidth of smoothing function. The default is 1/5 of the range
         of event times.

Example of usage:

%smooth(data=my.data,time=duration,width=8,survival=s)

Author:  Paul D. Allison, University of Pennsylvania
         allison@ssc.upenn.edu
*************************************************************************/

data _inset_;
 set &data end=final;
 retain _grp_ _censor_ 0;
 t=&time;
 survival=&survival;
 if t=0 and survival=1 then _grp_=_grp_+1;
 keep _grp_ t survival;
 if final and _grp_ > 1 then call symput('nset','yes');
   else if final then call symput('nset','no');
 if _censor_ = 1 then delete;
 if survival in (0,1) then delete;
run;

proc iml;
use _inset_;
read all var {t _grp_};
%if &width ne %then %let w2=&width;
  %else %let w2=(max(t)-min(t))/5;
w=&w2;
z=char(w,8,2);
call symput('width',z);
numset=max(_grp_);
create _plt_ var{ lambda s group};
setin _inset_ ;
do m=1 to numset;
  read all var {t survival _grp_} where (_grp_=m);
  n=nrow(survival);
  lo=t[1] + w;
  hi=t[n] - w;
  npt=50;
  inc=(hi-lo)/npt;
  s=lo+(1:npt)`*inc;
  group=j(npt,1,m);
  slag=1//survival[1:n-1];
  h=1-survival/slag;
  x = (j(npt,1,1)*t` - s*j(1,n,1))/w;
  k=.75*(1-x#x)#(abs(x)<=1);
  lambda=k*h/w;
  append;
end;
quit;

%if &nset = yes %then %let c==group;
  %else %let c=;

proc gplot data=_plt_;
  plot lambda*s &c / vaxis=axis1 vzero haxis=axis2;
  axis1 label=(angle=90 f=titalic 'Hazard Function' ) minor=none ;
  axis2 label=(f=titalic "Time    (bandwidth=&width)") minor=none;
  symbol1 i=join color=black line=1;
  symbol2 i=join color=red line=2;
  symbol3 i=join color=green line=3;
  symbol4 i=join color=blue line=4;
run;
quit;

%mend smooth;




-------------
LIFEHAZ Macro
-------------

%macro lifehaz(outest=,out=,obsno=0,xbeta=lp);

/********************************************************************
Macro LIFEHAZ plots the hazard function for a model fitted by
PROC LIFEREG. In the LIFEREG procedure, you must specify OUTEST=name1
in the PROC statement.  You must also use the OUTPUT statement with
OUT=name2 and XBETA=name3. By default, the hazard is plotted for the
mean value of XBETA (the linear predictor).  If you want a plot for a
specific observation, you must specify the observation number
(OBSNO) when you invoke the macro.  The macro is invoked as follows:

   %lifehaz(outest=name1,out=name2,xbeta=name3,obsno=1);

Author: Paul D. Allison, U. of Pennsylvania, allison@ssc.upenn.edu.

********************************************************************/


data;
  set &outest;
  call symput('time',_NAME_);
run;
proc means data=&out noprint;
  var &time &xbeta;
  output out=_c_ min(&time)=min max(&time)=max mean(&xbeta)=mean;
run;
data;
  set &outest;
  call symput('model',_dist_);
  s=_scale_;
  d=_shape1_;
  _y_=&obsno;
  set _c_ (keep=min max mean);
  if _y_=0 then m=mean;
  else do;
    set &out (keep=&xbeta) point=_y_;
    m=&xbeta;
  end;
  inc=(max-min)/300;
  g=1/s;
  alph=exp(-m*g);
if _dist_='LNORMAL' then do;
  do t=min to max by inc;
  z=(log(t)-m)/s;
  f=exp(-z*z/2)/(t*s*sqrt(2*3.14159));
  Surv=1-probnorm(z);
  h=f/Surv;
  output;
  end;
end;
else if _dist_='GAMMA' then do;
  k=1/(d*d);
  do t=min to max by inc;
  u=(t*exp(-m))**(1/s);
  f=abs(d)*(k*u**d)**k*exp(-k*u**d)/(s*gamma(k)*t);
  Surv=1-probgam(k*u**d,k);
  if d lt 0 then Surv=1-Surv;
  h=f/Surv;
  output;
  end;
end;
else if _dist_='WEIBULL' or _dist_='EXPONENT' then do;
  do t=min to max by inc;
  h=g*alph*t**(g-1);
  output;
  end;
end;
else if _dist_='LLOGISTC' then do;
  do t=min to max by inc;
  h=g*alph*t**(g-1)/(1+alph*t**g);
  output;
  end;
end;
else put 'ERROR:DISTRIBUTION NOT FITTED BY LIFEREG';
run;
proc gplot;
  plot h*t / haxis=axis2 vaxis=axis1 vzero;
  symbol1 i=join v=none c=black;
  axis1 label=(f=titalic angle=90 'Hazard');
  axis2 label=(f=titalic justify=c 'time' f=titalic justify=c "&model");
run; quit;
%mend lifehaz;




-------------
PREDICT Macro
-------------

%macro predict (outest=, out=_last_,xbeta=,time=);

/********************************************************************
MACRO PREDICT produces predicted survival probabilities for specified
survival times, based on models fitted by PROC LIFEREG. When fitting the
model with PROC LIFEREG, you must request the OUTEST data set in the
PROC statement.  You must also request an OUTPUT data set with the
XBETA= keyword.

PREDICT has four parameters:

OUTEST    is the name of the data set produced with the OUTEST option.

OUT       is the name of the data set produced by the OUTPUT statement.
          The default is the last created data set.

XBETA     is the name of the variable specified with the XBETA= keyword.

TIME      is the specified survival time that is to be evaluated.

Example of usage:

To get 5-year survival probabilities for every individual in the sample
(assuming that actual survival times are measured in years);

%predict(outest=a, out=b, xbeta=lp, time=5).

Author:  Paul D. Allison, Univ. of Pennsylvania
         allison@ssc.upenn.edu
*********************************************************************/


data _pred_;
_p_=1;
set &outest (keep=_dist_ _scale_ _shape1_ ) point=_p_;
set &out;
lp=&xbeta;
t=&time;
gamma=1/_scale_;
alpha=exp(-lp*gamma);
prob=0;
if _dist_='EXPONENT' or _dist_='WEIBULL' then prob=exp(-alpha*t**gamma);
if _dist_='LNORMAL' then prob=1-probnorm((log(t)-lp)/_scale_);
if _dist_='LLOGISTC' then prob=1/(1+alpha*t**gamma);
if _dist_='GAMMA' then do;
  d=_shape1_;
  k=1/(d*d);
  u=(t*exp(-lp))**gamma;
  prob=1-probgam(k*u**d,k);
  if d lt 0 then prob=1-prob;
  end;
drop lp gamma alpha _dist_ _scale_ _shape1_ d k u;
run;
proc print data=_pred_;
run;
%mend predict;









---------
WLW Macro
---------

%macro wlw(dv=,cv=,evcnt=,id=id,max=,data=_last_,ties=efron);

/***********************************************************************
MACRO WLW uses the method of Wei, Lin, and Weissfeld (Journal
of the American Statistical Association, 1989) to produce
tests and partial likelihood estimates for multivariate survival
data, e.g., repeated events.

The macro has the following parameters:

DV    is the two-part dependent variable, specified in the usual way
      for PROC PHREG.

CV    is a list of covariates (the maximum number is 20).

EVCNT is the name of a variable that contains the number of the event
      in the individual's sequence.

ID    is the name of a variable containing a unique ID for each
      individual (either character or numeric).

MAX   is the maximum number of events among all individuals. If you don't
      wish to analyze the higher order events (because of small
      subsample sizes), just enter a smaller number for MAX.

DATA  is the name of data set to be analyzed. The default is the last
      created data set.

TIES  is the method for handling ties (BRESLOW, EFRON, EXACT or DISCRETE).
      The default is EFRON.

Example of usage:

%wlw(dv=duration*censor(0), cv=nit hemo age sex, evcnt=number,
                id=idnum, data=_last_, ties=exact)

Author:  Paul D. Allison, University of Pennsylvania
         allison@ssc.upenn.edu

Adapted from IML program written by Ying So, SAS Institute.
*************************************************************************/

/*Preliminary operations on parameter specifications*/
%do i = 1 %to 20;
%let var&i=%scan(&cv,&i);
%if &&var&i = %then %goto out;
%if %length(&&var&i) > 6 %then %let vv&i=%substr(&&var&i,1,6);
%else %let vv&i=&&var&i;
%end;
%out: %let i=%eval(&i-1);
%let tot=%eval(&i*&max);
%do j=1 %to &i;
%let vdef&j=arr&j(_i_) = &&var&j*(evcnt=_i_);
%let cvd&j= &&vv&j..1-&&vv&j..&max;
%let ar&j=array arr&j(*) &&vv&j..1-&&vv&j..&max;
%end;

/*Create data set with covariate by time interactions*/
data expand;
ncv=&i;
set &data;
evcnt=&evcnt;
%do j=1 %to &i;
&&ar&j;
%end;
do _i_ = 1 to &max;
  %do j=1 %to &i;
    &&vdef&j;
  %end;
end;
run;

/*Do PHREG model for all events*/
proc phreg data=expand outest=_a_ noprint;
model &dv=
%do j=1 %to &i;
    &&cvd&j
  %end;
/ties=&ties;
output out=_out1_ dfbeta=dt1-dt&tot/order=data;
id &id;
strata &evcnt;
run;

/*Sum the DFBETA statistics*/
proc sort data=_out1_;
by &id; run;
proc means data=_out1_ noprint;
by &id;
var dt1-dt&tot;
output out=_out2_(drop=&id _type_ _freq_) sum=dt1-dt&tot;

/*Calculate the robust covariance matrix, perform tests*/
proc iml;
names={&cv};
nvar=ncol(names);
use _a_;
read all var _num_ into b;
b= b`;
use _out2_;
read all into x;

do i=1 to nvar;
stop=i*&max;
start=stop-&max+1;
bi= b[start:stop];
xi=x[,start:stop];
v= xi` * xi;
iv=inv(v);
se=sqrt(vecdiag(v));
reset noname;
cname= {"Estimate", " Std Error"};
cname2={"Event"};
indx= (1:&max)`;
tmpprt=  bi || se;
print / "Results For" (names[i]);
print indx[colname=cname2] tmpprt[colname=cname format=10.5];
print "Estimated Joint Covariance Matrix",, v;

/* H0: All coefficients equal to 0 */
chisq= bi` * iv * bi;
df= nrow(bi);
p= 1-probchi(chisq,df);
print ,,"Testing H0: no treatment effects for" (names[i]), ,
"Wald Chi-Square = " chisq, "DF = " df,
"p-value = "p[format=5.4],;

/* H0: All coefficients equal to each other */
c=j(df-1,df,0);
do k=1 to df-1;
c[k,k]=1;
c[k,k+1]=-1;
end;
chisq= bi`*c`*inv(c*v*c`)*c * bi;
df= df-1;
p= 1-probchi(chisq,df);
print ,,"Testing H0:Equal Coefficients for" (names[i]), ,
"Wald Chi-Square = " chisq, "DF = " df,
"p-value = "p[format=5.4],;

/* Assume coefficients equal. Estimate the common value */
nparm=nrow(bi);
e= j(nparm,1,1);
h= inv(e` * iv * e) * iv * e;
b1= h` * bi;
se= sqrt(h` * v * h);
zscore= b1 / se;
p= 1- probchi( zscore * zscore, 1);
print ,,"Estimation of the Common Parameter for" (names[i]),,
"optimal weights = "h,
"Estimate = " b1,
"Standard Error = " se,
"z-score =" zscore,
"2-sided p-value = " p[format=5.4];
end;
quit;
run;
%mend wlw;