/*------------------------------------------------------------------- */ /* Logistic Regression Using the SAS System: Theory and Application */ /* */ /* by Paul D. Allison */ /* Copyright(c) 1999 by SAS Institute Inc., Cary, NC, USA */ /* SAS Publications order # 55770 */ /* ISBN 1-58025-352-0 */ /*-------------------------------------------------------------------*/ /* */ /* This material is provided "as is" by SAS Institute Inc. There */ /* are no warranties, expressed or implied, as to merchantability or */ /* fitness for a particular purpose regarding the materials or code */ /* contained herein. The Institute is not responsible for errors */ /* in this material as it now exists or will exist, nor does the */ /* Institute provide technical support for it. */ /* */ /*-------------------------------------------------------------------*/ /* Questions or problem reports concerning this material may be */ /* addressed to the author: */ /* */ /* SAS Institute Inc. */ /* Books by Users */ /* Attn: Paul D. Allison */ /* SAS Campus Drive */ /* Cary, NC 27513 */ /* */ /* */ /* If you prefer, you can send email to: saspress@sas.com */ /* Use this for subject field: */ /* Comments for Paul D. Allison */ /* */ /*-------------------------------------------------------------------*/ /* This file contains programs and data sets from the book, "Logistic Regression Using the SAS System: Theory and Application" by Paul D. Allison, Ph.D. The file lists, in order, -- data sets used in the book -- macro used in the book -- programs used in the book ************************************************************************* ************************************************************************* DATA SETS USED IN THIS BOOK ---------------- PENALTY Data Set ---------------- Data described in Chapter 2 of P.D. Allison, "Logistic Regression Using the SAS System: Theory and Application." */ data penalty; input death blackd whitvic serious culp serious2; datalines; 0 1 0 7.1 2 3.4 1 0 1 11.5 5 4.66666666 0 0 0 6 2 3 0 0 1 8.4 4 3.2 1 1 0 12.2 5 4.2 0 0 0 7.7 1 3.2 1 1 0 3.66666666 2 2.83333333 1 0 1 12.8 5 4.8 0 1 0 7 1 3.2 0 1 0 7.875 5 2.75 0 1 1 3.7 1 2.4 0 1 1 7.3 1 3.4 0 0 1 9.2 1 3.2 0 1 0 8.6 1 3.8 1 1 0 8 5 3.8 0 1 0 3.58333333 1 2.83333333 0 0 1 10.7 2 4 1 0 1 7.2 5 3 0 1 0 4.8 1 2.2 0 1 0 1.6 1 1.8 1 0 1 6.9 2 3 0 0 1 7.4 3 3.8 0 0 1 6.7 1 3.2 0 1 1 6.8 1 2.6 1 1 0 9.8 1 4.2 0 0 1 9.4 1 3.4 0 0 1 1.4 1 1.4 0 1 0 8.1 1 3.2 0 1 0 1.6 1 1 0 1 0 2.25 1 1 0 0 0 10.9 2 4.4 0 0 0 9.3 2 3.8 1 0 0 6 5 2.5 1 1 1 9.8 2 4 0 0 1 4.6 2 2.6 1 1 1 8.4 5 3.6 0 0 0 8.16666666 1 3.83333333 0 1 1 4.6 1 2.4 0 0 1 5.3 1 2.4 1 1 1 7.8 4 3.8 0 1 1 6.5 1 2.8 1 1 0 6.8 3 3.4 1 1 1 11 5 3.8 1 0 1 11.7 3 3.8 0 1 0 8.8 1 4 0 1 1 6.2 1 2.6 1 0 1 4 4 2.4 0 0 1 10.6 2 5 1 0 0 13.6 5 4.6 0 0 1 5.1 1 2.8 1 0 1 10.9 5 3.6 1 1 1 5.8 2 2.8 0 0 1 4.7 1 3 0 0 1 4.8 1 2.4 0 0 1 4.2 4 2 1 0 1 13.5 4 4.8 0 0 1 3.6 1 1.8 0 0 1 2.6 1 2.6 1 1 0 11.6666666 5 4.66666666 0 1 0 5.1 1 2.2 0 0 0 6.6 1 3 0 0 1 6.4 2 3 0 0 1 8.8 2 3.8 1 0 1 9.7 5 4 1 1 0 6.66666666 2 3.33333333 0 0 1 11.2 1 4 0 0 1 4.5 2 2.4 0 1 0 5.16666666 1 3.16666666 0 0 0 11.9 4 4.4 1 1 0 2 5 1.4 0 1 1 10.0833333 1 4.33333333 1 0 1 5.2 4 3 1 1 0 8.1 4 3.4 0 1 0 5.2 1 3 0 0 1 4.7 1 2.4 0 0 1 7.3 1 3.6 0 1 0 10.4 2 3.8 1 1 0 7.58333333 5 3.83333333 1 1 0 9.9 5 3.6 0 0 1 9.2 1 3.8 0 0 1 10.3 1 4.2 0 0 1 7.4 1 3 0 0 0 8 1 3.2 0 0 1 9.25 1 3.75 0 1 1 9.2 1 3.2 1 0 1 7.58333333 3 3.66666666 0 0 1 11.9 1 4 1 1 0 7.5 4 3 0 1 0 3.6 1 2.2 1 0 1 10 4 3.6 0 0 1 1.875 1 1 0 1 0 10 2 4 0 1 1 8.83333333 1 4.16666666 0 1 0 5.8 1 2.4 0 1 1 7.5 2 3 0 1 0 3 1 1.5 0 1 0 1.8 1 1.4 0 1 0 5.75 1 2.5 1 1 0 8.6 4 4.2 0 0 1 12.25 1 4.25 0 1 1 9.3 1 4 0 0 0 2.7 1 2.2 1 0 1 8.9 4 4 0 0 1 8.9 2 3.8 1 0 1 8.3 3 3.6 0 0 1 11.5 5 4.5 1 1 0 11.2 3 4.6 0 0 1 10 3 3.8 1 0 1 13.8 5 4.4 0 0 1 6.25 1 2.25 0 0 0 13.7 5 5 1 0 1 12.8 5 4.8 0 1 0 8.41666666 1 3.83333333 0 1 1 7.6 1 3.2 0 0 1 13.7 5 5 1 0 1 9.75 4 3.75 0 0 1 6.2 1 2.4 0 1 1 11.9 1 4.4 0 0 1 2.3 1 2.4 0 1 1 5.7 1 2.4 0 0 0 9.5 2 3.6 1 0 0 2.2 2 1.2 1 1 0 12 5 4.2 1 1 1 12 1 4.4 0 0 0 4.16666666 1 3.33333333 0 1 1 9.4 2 4 0 1 0 9.25 2 4.16666666 1 1 1 7.1 1 3.4 0 1 0 11.25 1 4 1 1 1 6 3 2.6 0 0 1 3.6 2 2 0 1 0 5.3 1 2.8 0 1 1 13.6666666 3 4.66666666 0 1 1 4.9 1 2.2 0 0 0 12 2 4.6 0 1 0 11 3 4.6 0 1 1 8.9 1 3.6 1 1 1 13 1 4.4 1 1 0 11.6 1 4.4 1 0 1 13.4 3 4.4 0 1 0 10.5 3 4 1 1 1 13.7 5 4.8 0 0 1 5.3 1 2.2 1 0 1 5.7 5 3 0 0 1 10.6 2 4 1 1 1 3.9 3 2.4 1 1 1 9.3 5 4.4 ; /* ---------------- WALLET Data Set ---------------- Data described in Chapter 5 of P.D. Allison, "Logistic Regression Using the SAS System: Theory and Application." */ data wallet; input wallet male business punish explain; datalines; 2 0 0 2 0 2 0 0 2 1 3 0 0 1 1 3 0 0 2 0 1 1 0 1 1 3 0 0 1 1 3 0 0 1 1 3 1 0 1 1 3 1 0 1 1 3 0 0 2 1 2 0 1 1 1 3 1 1 1 1 3 1 0 1 1 3 1 0 1 1 3 0 0 1 1 3 0 0 1 0 3 0 0 2 1 2 0 0 3 0 1 1 1 3 0 2 0 0 1 1 2 1 0 2 0 3 0 0 1 1 3 1 0 1 1 3 1 1 1 0 3 1 0 1 1 2 0 0 1 0 2 1 0 3 0 1 1 0 2 0 3 1 0 2 0 3 1 0 1 1 3 0 0 1 1 3 1 0 2 1 1 1 0 1 1 3 0 0 2 0 3 1 0 1 0 3 1 1 2 1 3 0 0 2 0 3 0 0 1 1 3 1 0 1 1 3 0 0 1 1 3 0 0 1 1 3 0 0 1 1 3 0 0 2 0 3 1 1 1 1 3 1 0 1 1 3 0 0 1 1 3 0 0 1 1 3 0 0 1 0 3 0 1 3 0 3 1 0 2 0 2 0 0 2 1 3 0 0 1 1 3 1 0 1 1 3 1 0 1 1 3 1 0 1 0 3 1 1 1 0 3 1 0 1 0 2 1 1 3 1 3 0 0 1 1 3 0 0 3 1 3 0 0 1 1 3 0 0 1 0 3 0 0 1 1 1 0 1 1 1 3 0 0 1 0 3 1 0 1 1 1 1 0 1 0 3 1 0 3 1 2 1 0 3 1 1 1 1 2 1 1 1 0 2 1 3 0 0 1 1 3 0 0 3 0 2 1 0 1 1 2 0 0 1 1 2 1 0 1 1 3 0 0 1 0 3 1 1 1 1 3 1 0 1 1 3 0 0 1 1 3 0 1 1 1 3 0 0 1 1 3 0 0 1 1 3 0 0 2 1 2 1 1 1 0 3 1 0 1 1 3 0 0 1 1 2 1 1 1 1 3 0 0 1 1 3 1 1 1 1 3 0 0 1 1 3 0 0 1 1 3 0 0 1 1 3 0 1 1 1 3 0 0 2 1 1 1 1 1 1 1 1 0 2 0 2 1 0 1 1 1 1 1 1 1 2 1 0 1 1 1 1 1 3 0 2 1 1 1 1 1 1 1 3 1 3 0 0 3 1 3 0 0 1 1 2 0 0 1 1 3 0 0 1 1 1 0 1 3 0 3 0 0 1 1 2 0 0 1 0 3 0 0 1 1 3 0 0 1 1 2 1 0 1 1 3 1 0 1 1 3 0 0 1 1 1 1 0 3 0 2 1 0 1 1 2 0 1 1 1 1 0 0 3 0 1 0 1 2 0 3 0 0 1 1 3 0 0 1 1 3 0 0 1 1 3 1 1 1 1 3 0 0 1 0 3 0 0 1 1 3 1 0 1 1 3 1 1 1 1 3 1 0 1 1 2 1 1 1 1 2 0 0 1 0 3 0 0 1 1 2 1 1 2 0 3 1 0 1 0 2 1 0 1 0 3 0 0 2 1 3 1 1 1 1 1 0 0 3 0 3 0 0 1 1 3 1 1 1 1 3 0 0 1 0 3 0 1 1 0 2 0 0 1 1 3 1 0 1 1 2 1 0 1 0 3 0 0 1 0 2 1 0 1 1 3 1 0 1 1 3 1 0 2 0 3 1 1 2 1 3 1 0 1 1 2 1 0 1 0 3 0 0 1 1 3 1 0 1 1 2 1 1 1 0 3 0 0 1 1 3 1 0 1 1 2 1 0 1 0 3 0 1 2 1 2 1 1 2 1 3 0 0 1 1 1 1 0 1 1 3 1 1 3 1 2 1 0 1 1 1 0 0 1 0 2 1 0 3 0 3 0 0 1 1 2 1 1 1 1 3 0 0 1 1 2 0 0 2 0 2 1 0 1 1 1 1 1 2 0 2 1 0 2 0 2 0 0 1 1 1 0 1 3 0 2 1 0 1 1 2 1 0 1 1 3 1 0 1 1 3 0 0 1 1 2 1 0 1 1 1 1 0 2 0 2 0 1 2 1 3 0 0 2 0 2 1 1 1 1 3 0 1 2 1 1 0 0 3 0 2 1 1 1 0 3 0 0 3 1 2 1 0 2 1 3 0 0 1 1 3 1 0 3 1 3 0 0 1 1 3 1 1 1 1 3 1 0 1 1 2 1 0 1 1 ; /* ---------------- TRAVEL Data Set ---------------- Data described in Chapter 7 of P.D. Allison, "Logistic Regression Using the SAS System: Theory and Application." */ data travel; input id mode choice ttme cost time hinc psize; datalines; 1 1 0 69 59 100 35 1 1 2 0 34 31 372 35 1 1 3 0 35 25 417 35 1 1 4 1 0 10 180 35 1 2 1 0 64 58 68 30 2 2 2 0 44 31 354 30 2 2 3 0 53 25 399 30 2 2 4 1 0 11 255 30 2 3 1 0 69 115 125 40 1 3 2 0 34 98 892 40 1 3 3 0 35 53 882 40 1 3 4 1 0 23 720 40 1 4 1 0 64 49 68 70 3 4 2 0 44 26 354 70 3 4 3 0 53 21 399 70 3 4 4 1 0 5 180 70 3 5 1 0 64 60 144 45 2 5 2 0 44 32 404 45 2 5 3 0 53 26 449 45 2 5 4 1 0 8 600 45 2 6 1 0 69 59 100 20 1 6 2 1 40 20 345 20 1 6 3 0 35 13 417 20 1 6 4 0 0 12 284 20 1 7 1 1 45 148 115 45 1 7 2 0 34 111 945 45 1 7 3 0 35 66 935 45 1 7 4 0 0 36 821 45 1 8 1 0 69 121 152 12 1 8 2 0 34 52 889 12 1 8 3 0 35 50 879 12 1 8 4 1 0 50 780 12 1 9 1 0 69 59 100 40 1 9 2 0 34 31 372 40 1 9 3 0 35 25 417 40 1 9 4 1 0 17 210 40 1 10 1 0 69 58 68 70 2 10 2 0 34 31 357 70 2 10 3 0 35 25 402 70 2 10 4 1 0 7 210 70 2 11 1 0 64 58 68 15 2 11 2 0 44 16 357 15 2 11 3 0 53 13 402 15 2 11 4 1 0 4 210 15 2 12 1 0 64 62 108 35 2 12 2 0 44 34 370 35 2 12 3 0 53 28 415 35 2 12 4 1 0 6 250 35 2 13 1 0 64 45 114 50 4 13 2 0 44 24 378 50 4 13 3 0 53 19 423 50 4 13 4 1 0 5 240 50 4 14 1 0 64 58 94 40 1 14 2 0 44 31 360 40 1 14 3 0 53 25 405 40 1 14 4 1 0 15 285 40 1 15 1 0 64 83 169 26 4 15 2 0 44 70 948 26 4 15 3 0 53 47 938 26 4 15 4 1 0 17 1200 26 4 16 1 0 69 60 127 26 1 16 2 1 20 19 325 26 1 16 3 0 35 25 435 26 1 16 4 0 0 14 350 26 1 17 1 0 69 61 74 26 1 17 2 1 15 38 255 26 1 17 3 0 35 26 389 26 1 17 4 0 0 13 315 26 1 18 1 0 69 67 86 6 1 18 2 1 20 21 300 6 1 18 3 0 35 19 399 6 1 18 4 0 0 17 327 6 1 19 1 0 69 59 148 20 1 19 2 1 45 18 305 20 1 19 3 0 35 14 456 20 1 19 4 0 0 16 427 20 1 20 1 0 64 58 93 72 2 20 2 1 10 28 305 72 2 20 3 0 53 25 346 72 2 20 4 0 0 9 316 72 2 21 1 0 69 61 73 6 1 21 2 1 20 21 305 6 1 21 3 0 35 15 395 6 1 21 4 0 0 13 314 6 1 22 1 0 64 62 235 10 2 22 2 1 45 45 465 10 2 22 3 0 53 17 623 10 2 22 4 0 0 13 559 10 2 23 1 1 90 142 105 50 1 23 2 0 34 71 596 50 1 23 3 0 35 32 590 50 1 23 4 0 0 33 577 50 1 24 1 1 50 120 110 50 1 24 2 0 34 70 596 50 1 24 3 0 35 31 590 50 1 24 4 0 0 33 577 50 1 25 1 1 15 85 65 18 2 25 2 0 34 15 361 18 2 25 3 0 35 12 406 18 2 25 4 0 0 9 296 18 2 26 1 1 30 85 140 60 1 26 2 0 44 90 928 60 1 26 3 0 53 45 918 60 1 26 4 0 0 86 902 60 1 27 1 1 80 75 110 45 1 27 2 0 34 70 638 45 1 27 3 0 35 31 632 45 1 27 4 0 0 39 581 45 1 28 1 1 45 85 140 18 2 28 2 0 44 39 664 18 2 28 3 0 53 35 658 18 2 28 4 0 0 19 592 18 2 29 1 0 64 74 179 8 2 29 2 1 60 43 320 8 2 29 3 0 53 21 345 8 2 29 4 0 0 9 321 8 2 30 1 0 69 59 100 6 1 30 2 1 2 11 285 6 1 30 3 0 35 13 417 6 1 30 4 0 0 13 284 6 1 31 1 0 69 59 101 20 1 31 2 1 5 17 300 20 1 31 3 0 35 25 420 20 1 31 4 0 0 13 297 20 1 32 1 0 69 64 90 45 1 32 2 1 15 32 325 45 1 32 3 0 35 29 405 45 1 32 4 0 0 18 327 45 1 33 1 0 64 59 73 70 2 33 2 1 45 29 290 70 2 33 3 0 53 26 395 70 2 33 4 0 0 9 314 70 2 34 1 0 69 62 66 4 1 34 2 1 10 31 295 4 1 34 3 0 35 19 397 4 1 34 4 0 0 17 307 4 1 35 1 0 69 60 132 40 1 35 2 1 15 15 330 40 1 35 3 0 35 26 373 40 1 35 4 0 0 12 309 40 1 36 1 0 69 60 117 35 1 36 2 1 10 23 325 35 1 36 3 0 35 25 425 35 1 36 4 0 0 17 307 35 1 37 1 0 64 62 184 40 2 37 2 1 45 24 360 40 2 37 3 0 53 28 464 40 2 37 4 0 0 11 427 40 2 38 1 0 64 50 67 4 3 38 2 1 30 31 265 4 3 38 3 0 53 14 393 4 3 38 4 0 0 6 308 4 3 39 1 0 64 48 154 15 4 39 2 1 55 25 360 15 4 39 3 0 53 14 462 15 4 39 4 0 0 4 351 15 4 40 1 1 30 147 100 26 1 40 2 0 34 96 678 26 1 40 3 0 35 57 672 26 1 40 4 0 0 28 629 26 1 41 1 1 75 125 110 26 1 41 2 0 34 70 596 26 1 41 3 0 35 31 590 26 1 41 4 0 0 24 577 26 1 42 1 1 40 152 95 70 1 42 2 0 34 73 600 70 1 42 3 0 35 34 594 70 1 42 4 0 0 24 587 70 1 43 1 1 30 116 180 70 1 43 2 0 34 71 657 70 1 43 3 0 35 32 651 70 1 43 4 0 0 29 629 70 1 44 1 1 40 100 105 45 2 44 2 0 44 70 622 45 2 44 3 0 53 31 616 45 2 44 4 0 0 17 577 45 2 45 1 1 45 105 115 8 2 45 2 0 44 35 622 8 2 45 3 0 53 31 616 8 2 45 4 0 0 12 577 8 2 46 1 1 20 106 190 70 1 46 2 0 34 72 659 70 1 46 3 0 35 33 653 70 1 46 4 0 0 44 592 70 1 47 1 1 60 90 100 26 2 47 2 0 44 69 596 26 2 47 3 0 53 30 590 26 2 47 4 0 0 13 577 26 2 48 1 1 40 48 115 50 1 48 2 0 34 31 365 50 1 48 3 0 35 25 410 50 1 48 4 0 0 16 308 50 1 49 1 1 50 69 85 10 3 49 2 0 44 16 344 10 3 49 3 0 53 13 389 10 3 49 4 0 0 4 315 10 3 50 1 1 75 99 135 30 1 50 2 0 34 96 678 30 1 50 3 0 35 57 672 30 1 50 4 0 0 29 629 30 1 51 1 1 90 64 155 60 2 51 2 0 44 74 678 60 2 51 3 0 53 35 672 60 2 51 4 0 0 20 629 60 2 52 1 1 85 105 85 30 4 52 2 0 44 56 665 30 4 52 3 0 53 35 659 30 4 52 4 0 0 8 587 30 4 53 1 0 69 60 123 30 1 53 2 1 15 24 365 30 1 53 3 0 35 25 430 30 1 53 4 0 0 13 332 30 1 54 1 0 64 58 90 50 2 54 2 1 30 22 340 50 2 54 3 0 53 25 417 50 2 54 4 0 0 9 334 50 2 55 1 0 64 45 73 6 4 55 2 1 15 22 290 6 4 55 3 0 53 13 395 6 4 55 4 0 0 5 314 6 4 56 1 0 69 108 170 30 1 56 2 1 30 31 875 30 1 56 3 0 35 44 887 30 1 56 4 0 0 50 884 30 1 57 1 0 69 110 249 12 1 57 2 1 45 22 890 12 1 57 3 0 35 47 955 12 1 57 4 0 0 38 990 12 1 58 1 0 64 115 138 36 2 58 2 1 10 44 830 36 2 58 3 0 53 50 869 36 2 58 4 0 0 18 862 36 2 59 1 0 69 117 147 30 1 59 2 1 40 59 790 30 1 59 3 0 35 48 885 30 1 59 4 0 0 38 883 30 1 60 1 0 64 88 119 35 3 60 2 1 50 78 775 35 3 60 3 0 53 43 840 35 3 60 4 0 0 16 855 35 3 61 1 0 69 105 196 6 1 61 2 1 40 43 895 6 1 61 3 0 35 44 919 6 1 61 4 0 0 50 935 6 1 62 1 0 64 120 333 6 1 62 2 1 25 28 870 6 1 62 3 0 53 52 890 6 1 62 4 0 0 38 921 6 1 63 1 0 64 103 146 8 2 63 2 1 25 36 875 8 2 63 3 0 53 43 943 8 2 63 4 0 0 19 887 8 2 64 1 0 69 103 138 6 1 64 2 1 5 22 800 6 1 64 3 0 35 43 821 6 1 64 4 0 0 36 846 6 1 65 1 0 64 116 164 12 2 65 2 1 75 89 685 12 2 65 3 0 53 47 875 12 2 65 4 0 0 19 874 12 2 66 1 0 69 103 129 30 1 66 2 0 34 88 925 30 1 66 3 1 10 30 790 30 1 66 4 0 0 50 887 30 1 67 1 0 64 109 230 35 2 67 2 0 44 101 1104 35 2 67 3 0 53 56 1094 35 2 67 4 1 0 26 960 35 2 68 1 0 69 108 177 35 1 68 2 0 34 92 907 35 1 68 3 1 45 39 850 35 1 68 4 0 0 52 865 35 1 69 1 0 64 92 161 60 3 69 2 1 40 73 792 60 3 69 3 0 53 46 920 60 3 69 4 0 0 16 887 60 3 70 1 0 64 119 161 60 2 70 2 1 45 75 765 60 2 70 3 0 53 51 869 60 2 70 4 0 0 19 898 60 2 71 1 0 64 109 190 12 2 71 2 1 40 24 399 12 2 71 3 0 53 46 951 12 2 71 4 0 0 27 897 12 2 72 1 0 69 111 108 10 1 72 2 1 30 30 760 10 1 72 3 0 35 50 867 10 1 72 4 0 0 47 844 10 1 73 1 0 69 104 246 10 1 73 2 1 25 23 830 10 1 73 3 0 35 45 1068 10 1 73 4 0 0 41 978 10 1 74 1 0 69 104 200 15 1 74 2 1 75 23 835 15 1 74 3 0 35 43 846 15 1 74 4 0 0 40 927 15 1 75 1 0 64 124 160 10 2 75 2 1 30 82 850 10 2 75 3 0 53 54 893 10 2 75 4 0 0 19 886 10 2 76 1 0 64 103 145 8 1 76 2 1 50 73 840 8 1 76 3 0 53 43 892 8 1 76 4 0 0 50 894 8 1 77 1 0 69 103 125 30 1 77 2 1 30 80 800 30 1 77 3 0 35 42 844 30 1 77 4 0 0 38 861 30 1 78 1 0 64 113 163 20 2 78 2 0 44 51 948 20 2 78 3 0 53 49 938 20 2 78 4 1 0 26 720 20 2 79 1 0 64 76 147 70 5 79 2 0 44 63 918 70 5 79 3 0 53 44 908 70 5 79 4 1 0 10 1440 70 5 80 1 0 69 108 163 20 1 80 2 0 34 89 905 20 1 80 3 1 30 43 785 20 1 80 4 0 0 35 879 20 1 81 1 0 69 127 193 60 1 81 2 0 34 109 888 60 1 81 3 1 60 52 1025 60 1 81 4 0 0 50 892 60 1 82 1 0 64 44 100 70 4 82 2 0 44 25 351 70 4 82 3 0 53 20 361 70 4 82 4 1 0 5 180 70 4 83 1 0 69 59 98 8 1 83 2 1 1 11 320 8 1 83 3 0 35 13 413 8 1 83 4 0 0 17 332 8 1 84 1 0 69 59 114 30 1 84 2 1 25 60 337 30 1 84 3 0 35 25 423 30 1 84 4 0 0 8 335 30 1 85 1 1 25 65 140 70 2 85 2 0 44 69 596 70 2 85 3 0 53 30 590 70 2 85 4 0 0 16 577 70 2 86 1 0 69 60 67 60 1 86 2 1 10 37 285 60 1 86 3 0 35 28 400 60 1 86 4 0 0 14 320 60 1 87 1 0 64 59 118 20 2 87 2 0 44 17 349 20 2 87 3 0 53 14 359 20 2 87 4 1 0 5 240 20 2 88 1 0 69 61 72 15 1 88 2 1 10 18 305 15 1 88 3 0 35 27 396 15 1 88 4 0 0 12 332 15 1 89 1 0 64 59 118 30 2 89 2 0 44 32 349 30 2 89 3 0 53 26 359 30 2 89 4 1 0 6 265 30 2 90 1 0 64 60 74 26 2 90 2 1 20 40 262 26 2 90 3 0 53 26 389 26 2 90 4 0 0 10 315 26 2 91 1 0 64 44 93 35 4 91 2 1 20 30 291 35 4 91 3 0 53 19 346 35 4 91 4 0 0 4 316 35 4 92 1 0 69 58 124 12 1 92 2 1 10 30 340 12 1 92 3 0 35 25 427 12 1 92 4 0 0 14 364 12 1 93 1 0 64 84 108 70 2 93 2 0 44 70 596 70 2 93 3 0 53 31 590 70 2 93 4 1 0 15 360 70 2 94 1 1 30 145 90 50 1 94 2 0 44 31 343 50 1 94 3 0 53 25 388 50 1 94 4 0 0 13 296 50 1 95 1 1 45 121 100 40 2 95 2 0 44 92 926 40 2 95 3 0 53 47 916 40 2 95 4 0 0 20 885 40 2 96 1 1 30 84 180 70 1 96 2 0 34 72 707 70 1 96 3 0 35 33 701 70 1 96 4 0 0 26 626 70 1 97 1 0 69 61 146 10 1 97 2 0 34 17 409 10 1 97 3 1 5 31 300 10 1 97 4 0 0 13 350 10 1 98 1 1 45 180 160 26 1 98 2 0 34 89 985 26 1 98 3 0 35 44 975 26 1 98 4 0 0 39 896 26 1 99 1 0 64 94 231 50 3 99 2 0 44 79 949 50 3 99 3 1 40 32 1110 50 3 99 4 0 0 13 942 50 3 100 1 0 64 92 203 70 3 100 2 0 44 77 961 70 3 100 3 0 53 46 951 70 3 100 4 1 0 17 780 70 3 101 1 0 69 59 111 30 1 101 2 0 34 31 376 30 1 101 3 1 15 25 360 30 1 101 4 0 0 23 351 30 1 102 1 0 64 75 153 50 5 102 2 0 44 64 900 50 5 102 3 0 53 45 890 50 5 102 4 1 0 13 720 50 5 103 1 0 69 58 99 20 1 103 2 0 34 16 366 20 1 103 3 0 35 13 411 20 1 103 4 1 0 13 300 20 1 104 1 0 64 110 153 32 2 104 2 0 44 91 874 32 2 104 3 0 53 46 864 32 2 104 4 1 0 21 960 32 2 105 1 0 64 108 187 27 2 105 2 0 44 90 932 27 2 105 3 0 53 45 922 27 2 105 4 1 0 20 1440 27 2 106 1 0 69 104 179 30 1 106 2 0 34 89 978 30 1 106 3 1 30 28 795 30 1 106 4 0 0 40 904 30 1 107 1 0 69 108 180 35 1 107 2 0 34 89 901 35 1 107 3 0 35 44 891 35 1 107 4 1 0 34 720 35 1 108 1 0 64 78 146 40 4 108 2 0 44 66 903 40 4 108 3 0 53 43 893 40 4 108 4 1 0 11 870 40 4 109 1 0 64 60 144 60 2 109 2 0 44 32 404 60 2 109 3 0 53 26 449 60 2 109 4 1 0 8 270 60 2 110 1 0 64 78 175 40 4 110 2 0 44 67 932 40 4 110 3 0 53 44 922 40 4 110 4 1 0 12 720 40 4 111 1 0 69 67 108 70 1 111 2 0 34 38 370 70 1 111 3 0 35 32 415 70 1 111 4 1 0 12 240 70 1 112 1 0 64 108 200 70 2 112 2 0 44 90 944 70 2 112 3 0 53 45 934 70 2 112 4 1 0 19 720 70 2 113 1 1 60 108 80 30 2 113 2 0 44 32 344 30 2 113 3 0 53 26 389 30 2 113 4 0 0 7 315 30 2 114 1 1 30 58 90 35 2 114 2 0 44 32 506 35 2 114 3 0 53 26 551 35 2 114 4 0 0 8 402 35 2 115 1 1 55 69 115 60 1 115 2 0 34 43 392 60 1 115 3 0 35 37 437 60 1 115 4 0 0 13 268 60 1 116 1 1 40 66 105 45 1 116 2 0 34 31 372 45 1 116 3 0 35 25 417 45 1 116 4 0 0 18 327 45 1 117 1 0 69 57 67 45 1 117 2 0 34 31 355 45 1 117 3 1 40 18 245 45 1 117 4 0 0 13 320 45 1 118 1 0 69 129 185 6 1 118 2 0 34 67 933 6 1 118 3 1 20 54 820 6 1 118 4 0 0 38 894 6 1 119 1 1 90 151 95 36 1 119 2 0 34 96 895 36 1 119 3 0 35 51 885 36 1 119 4 0 0 35 844 36 1 120 1 1 10 70 85 20 1 120 2 0 34 34 351 20 1 120 3 0 35 28 396 20 1 120 4 0 0 22 307 20 1 121 1 1 25 75 100 20 2 121 2 0 44 15 348 20 2 121 3 0 53 12 393 20 2 121 4 0 0 7 290 20 2 122 1 1 99 110 260 26 1 122 2 0 34 92 934 26 1 122 3 0 35 47 924 26 1 122 4 0 0 45 816 26 1 123 1 1 30 94 195 29 1 123 2 0 34 89 943 29 1 123 3 0 35 44 933 29 1 123 4 0 0 58 912 29 1 124 1 1 35 95 155 8 2 124 2 0 44 45 930 8 2 124 3 0 53 43 920 8 2 124 4 0 0 23 860 8 2 125 1 0 69 104 178 32 1 125 2 0 34 89 992 32 1 125 3 1 15 38 675 32 1 125 4 0 0 39 900 32 1 126 1 0 64 103 170 45 2 126 2 0 44 88 889 45 2 126 3 1 30 35 770 45 2 126 4 0 0 18 905 45 2 127 1 0 64 86 167 45 3 127 2 0 44 75 972 45 3 127 3 0 53 44 962 45 3 127 4 1 0 13 870 45 3 128 1 0 64 108 139 26 2 128 2 0 44 90 862 26 2 128 3 1 30 36 780 26 2 128 4 0 0 18 875 26 2 129 1 0 69 59 106 60 1 129 2 0 34 31 372 60 1 129 3 0 35 25 417 60 1 129 4 1 0 13 300 60 1 130 1 0 64 58 124 10 2 130 2 1 10 35 380 10 2 130 3 0 53 13 427 10 2 130 4 0 0 8 364 10 2 131 1 0 64 107 153 45 2 131 2 0 44 89 880 45 2 131 3 0 53 44 870 45 2 131 4 1 0 2 660 45 2 132 1 0 64 86 143 60 3 132 2 0 44 74 880 60 3 132 3 0 53 43 870 60 3 132 4 1 0 16 660 60 3 133 1 0 69 108 196 60 1 133 2 0 34 91 967 60 1 133 3 1 15 35 935 60 1 133 4 0 0 38 903 60 1 134 1 0 69 103 149 8 1 134 2 0 34 45 892 8 1 134 3 1 25 25 730 8 1 134 4 0 0 37 882 8 1 135 1 0 64 103 160 60 2 135 2 0 44 89 987 60 2 135 3 0 53 44 977 60 2 135 4 1 0 34 660 60 2 136 1 0 64 114 161 12 2 136 2 0 44 60 1031 12 2 136 3 0 53 58 1021 12 2 136 4 1 0 19 720 12 2 137 1 0 69 107 150 45 1 137 2 0 34 91 914 45 1 137 3 0 35 46 904 45 1 137 4 1 0 36 750 45 1 138 1 0 69 118 137 50 1 138 2 0 34 96 904 50 1 138 3 1 5 65 850 50 1 138 4 0 0 64 859 50 1 139 1 0 69 102 101 26 1 139 2 0 34 87 870 26 1 139 3 1 45 35 800 26 1 139 4 0 0 35 825 26 1 140 1 0 64 85 101 35 3 140 2 0 44 73 870 35 3 140 3 0 53 42 860 35 3 140 4 1 0 12 600 35 3 141 1 0 69 107 158 12 1 141 2 1 30 61 780 12 1 141 3 0 35 45 901 12 1 141 4 0 0 54 853 12 1 142 1 0 69 113 244 15 1 142 2 1 30 67 845 15 1 142 3 0 35 49 893 15 1 142 4 0 0 47 868 15 1 143 1 0 64 84 215 12 4 143 2 1 99 37 885 12 4 143 3 0 53 46 966 12 4 143 4 0 0 10 921 12 4 144 1 0 64 94 163 35 3 144 2 1 25 68 755 35 3 144 3 0 53 47 895 35 3 144 4 0 0 16 879 35 3 145 1 0 69 112 161 26 1 145 2 1 15 21 797 26 1 145 3 0 35 45 876 26 1 145 4 0 0 47 852 26 1 146 1 0 69 103 166 6 1 146 2 1 45 20 820 6 1 146 3 0 35 43 836 6 1 146 4 0 0 35 886 6 1 147 1 0 69 107 152 4 1 147 2 1 30 33 755 4 1 147 3 0 35 44 882 4 1 147 4 0 0 48 845 4 1 148 1 0 64 103 164 40 2 148 2 1 10 41 730 40 2 148 3 0 53 43 925 40 2 148 4 0 0 19 898 40 2 149 1 0 64 143 166 40 1 149 2 1 10 83 825 40 1 149 3 0 53 70 896 40 1 149 4 0 0 50 911 40 1 150 1 1 45 94 270 60 1 150 2 0 34 91 916 60 1 150 3 0 35 46 906 60 1 150 4 0 0 49 872 60 1 151 1 1 45 138 115 4 1 151 2 0 34 60 880 4 1 151 3 0 35 58 870 4 1 151 4 0 0 47 888 4 1 152 1 1 60 102 250 50 1 152 2 0 34 112 997 50 1 152 3 0 35 67 952 50 1 152 4 0 0 43 971 50 1 153 1 1 60 151 255 60 2 153 2 0 44 91 941 60 2 153 3 0 53 46 931 60 2 153 4 0 0 21 959 60 2 154 1 1 60 111 205 70 1 154 2 0 34 97 888 70 1 154 3 0 35 52 878 70 1 154 4 0 0 49 855 70 1 155 1 1 60 70 95 40 2 155 2 0 44 31 360 40 2 155 3 0 53 25 405 40 2 155 4 0 0 7 335 40 2 156 1 1 45 74 70 35 3 156 2 0 44 26 361 35 3 156 3 0 53 21 406 35 3 156 4 0 0 4 315 35 3 157 1 1 75 165 180 60 2 157 2 0 44 98 967 60 2 157 3 0 53 53 922 60 2 157 4 0 0 26 947 60 2 158 1 1 30 93 175 60 1 158 2 0 34 96 1030 60 1 158 3 0 35 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30 1 169 4 1 0 30 440 30 1 170 1 0 64 71 145 40 3 170 2 0 44 59 658 40 3 170 3 0 53 32 652 40 3 170 4 1 0 10 590 40 3 171 1 0 64 82 159 50 2 171 2 0 44 71 765 50 2 171 3 0 53 32 759 50 2 171 4 1 0 13 490 50 2 172 1 0 69 61 73 35 1 172 2 0 34 33 350 35 1 172 3 1 50 26 227 35 1 172 4 0 0 14 314 35 1 173 1 0 69 60 133 34 1 173 2 0 34 31 397 34 1 173 3 1 15 21 240 34 1 173 4 0 0 14 351 34 1 174 1 0 64 81 129 8 2 174 2 0 44 35 677 8 2 174 3 1 15 31 565 8 2 174 4 0 0 12 588 8 2 175 1 0 69 59 117 30 1 175 2 0 34 32 397 30 1 175 3 0 35 26 442 30 1 175 4 1 0 17 180 30 1 176 1 0 69 111 276 32 1 176 2 0 34 93 1047 32 1 176 3 1 30 35 860 32 1 176 4 0 0 42 1008 32 1 177 1 0 69 59 88 26 1 177 2 0 34 30 361 26 1 177 3 1 15 21 295 26 1 177 4 0 0 13 299 26 1 178 1 0 69 59 114 42 1 178 2 0 34 31 389 42 1 178 3 1 15 21 243 42 1 178 4 0 0 13 334 42 1 179 1 1 90 55 115 50 1 179 2 0 44 72 602 50 1 179 3 0 53 33 596 50 1 179 4 0 0 24 589 50 1 180 1 1 15 87 110 70 2 180 2 0 44 31 348 70 2 180 3 0 53 25 393 70 2 180 4 0 0 7 320 70 2 181 1 0 69 62 76 30 1 181 2 0 34 39 377 30 1 181 3 0 35 33 422 30 1 181 4 1 0 12 300 30 1 182 1 0 69 59 121 26 1 182 2 0 34 31 386 26 1 182 3 0 35 25 431 26 1 182 4 1 0 14 270 26 1 183 1 0 64 51 90 26 3 183 2 1 20 61 350 26 3 183 3 0 53 22 405 26 3 183 4 0 0 6 327 26 3 184 1 0 64 64 215 18 2 184 2 1 50 41 420 18 2 184 3 0 53 15 385 18 2 184 4 0 0 9 321 18 2 185 1 0 64 58 74 35 2 185 2 1 30 21 295 35 2 185 3 0 53 24 389 35 2 185 4 0 0 7 315 35 2 186 1 0 64 71 119 50 3 186 2 0 44 58 617 50 3 186 3 1 15 35 615 50 3 186 4 0 0 11 586 50 3 187 1 1 15 50 75 4 1 187 2 0 34 15 361 4 1 187 3 0 35 12 406 4 1 187 4 0 0 13 315 4 1 188 1 1 10 61 80 30 4 188 2 0 44 24 350 30 4 188 3 0 53 19 395 30 4 188 4 0 0 4 314 30 4 189 1 0 69 59 100 45 1 189 2 0 34 31 372 45 1 189 3 0 35 25 417 45 1 189 4 1 0 13 210 45 1 190 1 0 69 58 73 60 1 190 2 0 34 31 324 60 1 190 3 0 35 25 334 60 1 190 4 1 0 18 240 60 1 191 1 0 69 62 184 4 1 191 2 0 34 19 454 4 1 191 3 0 35 16 464 4 1 191 4 1 0 18 225 4 1 192 1 1 30 93 85 30 1 192 2 0 34 33 365 30 1 192 3 0 35 27 410 30 1 192 4 0 0 13 308 30 1 193 1 1 20 76 95 60 1 193 2 0 34 33 344 60 1 193 3 0 35 27 389 60 1 193 4 0 0 13 315 60 1 194 1 0 64 100 190 4 2 194 2 0 44 49 678 4 2 194 3 1 30 48 430 4 2 194 4 0 0 14 629 4 2 195 1 0 64 48 63 18 3 195 2 1 10 21 255 18 3 195 3 0 53 13 397 18 3 195 4 0 0 4 324 18 3 196 1 0 64 58 93 15 2 196 2 1 10 30 315 15 2 196 3 0 53 13 346 15 2 196 4 0 0 6 316 15 2 197 1 0 69 59 94 26 1 197 2 0 34 30 361 26 1 197 3 0 35 24 406 26 1 197 4 1 0 10 270 26 1 198 1 1 30 111 105 40 1 198 2 0 34 71 596 40 1 198 3 0 35 32 590 40 1 198 4 0 0 27 577 40 1 199 1 1 5 64 80 70 2 199 2 0 44 30 348 70 2 199 3 0 53 24 393 70 2 199 4 0 0 7 291 70 2 200 1 1 5 60 85 45 4 200 2 0 44 24 379 45 4 200 3 0 53 19 424 45 4 200 4 0 0 3 337 45 4 201 1 0 64 97 188 26 3 201 2 0 44 76 825 26 3 201 3 1 16 38 810 26 3 201 4 0 0 15 803 26 3 202 1 0 69 91 117 35 1 202 2 0 34 77 630 35 1 202 3 0 35 38 624 35 1 202 4 1 0 29 540 35 1 203 1 0 69 59 114 4 1 203 2 0 34 16 378 4 1 203 3 1 5 14 370 4 1 203 4 0 0 17 335 4 1 204 1 0 69 60 66 20 1 204 2 0 34 34 352 20 1 204 3 1 10 37 250 20 1 204 4 0 0 13 307 20 1 205 1 0 69 107 144 45 1 205 2 0 34 89 879 45 1 205 3 1 30 35 775 45 1 205 4 0 0 37 868 45 1 206 1 0 69 81 124 40 1 206 2 0 34 69 605 40 1 206 3 0 35 30 599 40 1 206 4 1 0 30 720 40 1 207 1 1 45 126 135 40 1 207 2 0 34 70 596 40 1 207 3 0 35 31 590 40 1 207 4 0 0 32 577 40 1 208 1 0 69 59 86 2 1 208 2 0 34 15 360 2 1 208 3 1 50 29 265 2 1 208 4 0 0 13 300 2 1 209 1 0 69 81 124 20 1 209 2 0 34 35 605 20 1 209 3 0 35 31 599 20 1 209 4 1 0 27 510 20 1 210 1 0 64 66 140 70 4 210 2 0 44 54 670 70 4 210 3 0 53 33 664 70 4 210 4 1 0 12 540 70 4 ; /* ----------------- JUDGERNK Data Set ----------------- Data described in Chapter 7 of P.D. Allison, "Logistic Regression Using the SAS System: Theory and Application." */ data judgernk; input judgid rank blackd whitvic death culp case; datalines; 11 1 1 1 0 3 4163 11 2 0 1 1 3 2172 11 3 1 1 0 1 1880 11 4 1 0 1 5 2015 11 5 0 0 0 1 1060 11 6 1 1 0 1 2375 11 7 1 0 1 2 1720 11 8 1 0 1 5 1598 11 9 1 0 1 2 197 11 10 0 1 1 5 119 11 11 1 0 0 1 3035 11 12 1 0 0 2 4142 11 13 0 0 0 1 4128 11 14 1 0 0 1 1791 11 15 1 0 0 1 463 12 1 0 1 1 5 119 12 2 1 0 0 2 4142 12 3 1 0 1 5 1598 12 4 0 0 0 1 1060 12 5 1 0 1 2 1720 12 6 1 1 0 1 1880 12 7 1 1 0 3 4163 12 8 1 0 0 1 3035 12 9 1 0 1 5 2015 12 10 0 0 0 1 4128 12 11 1 1 0 1 2375 12 12 1 0 0 1 1791 12 13 0 1 1 3 2172 12 14 1 0 1 2 197 12 15 1 0 0 1 463 13 1 1 1 0 3 4163 13 2 0 1 1 5 119 13 3 1 1 0 1 1880 13 4 0 1 1 3 2172 13 5 1 0 0 2 4142 13 6 1 1 0 1 2375 13 7 1 0 1 5 1598 13 8 1 0 1 5 2015 13 9 1 0 1 2 1720 13 10 1 0 0 1 1791 13 11 0 0 0 1 1060 13 12 1 0 0 1 3035 13 13 0 0 0 1 4128 13 14 1 0 1 2 197 13 15 1 0 0 1 463 14 2 0 1 1 5 119 14 2 1 0 1 5 1598 14 2 1 1 0 3 4163 14 4 1 1 0 1 1880 14 5.5 1 0 0 1 3035 14 5.5 1 0 0 2 4142 14 7.5 1 0 0 1 463 14 7.5 1 0 1 5 2015 14 9 0 0 0 1 1060 14 10 0 0 0 1 4128 14 11 0 1 1 3 2172 14 12 1 0 1 2 197 14 13 1 1 0 1 2375 14 14 1 0 0 1 1791 14 15 1 0 1 2 1720 15 1 1 0 0 1 3035 15 2 1 1 0 3 4163 15 3 1 0 1 5 1598 15 4 0 0 0 1 1060 15 5 1 1 0 1 2375 15 6 1 0 0 1 1791 15 7 0 1 1 5 119 15 8 1 0 1 2 1720 15 9 1 0 1 5 2015 15 10 0 0 0 1 4128 15 11 1 0 0 1 463 15 12 1 0 0 2 4142 15 13 1 1 0 1 1880 15 14 0 1 1 3 2172 15 15 1 0 1 2 197 16 1 1 1 0 3 4163 16 2 1 1 0 1 2375 16 3 1 0 1 5 1598 16 4 1 0 0 2 4142 16 5 0 1 1 5 119 16 6.5 1 1 0 1 1880 16 6.5 0 1 1 3 2172 16 8 1 0 0 1 3035 16 9 1 0 0 1 1791 16 10 1 0 1 2 197 16 11 1 0 0 1 463 16 12 1 0 1 2 1720 16 13 1 0 1 5 2015 16 14 0 0 0 1 1060 16 15 0 0 0 1 4128 21 1 0 1 1 4 3049 21 2 0 1 0 1 2715 21 3 1 0 0 1 4150 21 4 1 0 0 3 4179 21 5 1 0 0 5 231 21 6 0 1 0 5 2826 21 7 0 1 0 1 3003 21 8 1 0 1 4 2228 21 9 0 0 1 5 728 21 10 0 1 0 1 2091 21 11 1 0 0 1 2647 21 12 0 1 0 1 2270 21 13 1 0 0 1 716 21 14 1 0 0 1 2463 22 1 0 1 0 5 2826 22 2 0 1 1 4 3049 22 3 0 1 0 1 2715 22 4 1 0 0 5 231 22 5 1 0 0 3 4179 22 6 1 0 0 1 4150 22 7 0 1 0 1 3003 22 8 1 0 0 1 2647 22 9 0 1 0 1 2091 22 10 1 0 1 4 2228 22 11 1 0 0 1 2463 22 12 0 0 1 5 728 22 13 1 0 0 1 716 22 14 0 1 0 1 2270 23 1 1 0 0 1 4150 23 2 0 1 0 1 2715 23 3 0 1 0 1 2091 23 4 0 1 0 5 2826 23 5 1 0 1 4 2228 23 6 0 0 1 5 728 23 7 1 0 0 3 4179 23 8 0 1 1 4 3049 23 9 0 1 0 1 3003 23 10 1 0 0 1 2647 23 11 1 0 0 1 716 23 12 1 0 0 1 2463 23 13.5 1 0 0 5 231 23 13.5 0 1 0 1 2270 26 1 0 1 0 1 2091 26 2 1 0 0 3 4179 26 3 0 1 0 5 2826 26 4 0 1 0 1 2715 26 5 1 0 0 1 4150 26 6 1 0 0 5 231 26 7 1 0 1 4 2228 26 8 1 0 0 1 2647 26 9 0 0 1 5 728 26 10 0 1 1 4 3049 26 11 1 0 0 1 2463 26 12 0 1 0 1 3003 26 13 0 1 0 1 2270 26 14 1 0 0 1 716 31 1.5 0 1 0 2 506 31 1.5 0 1 1 4 1529 31 3 1 1 1 5 1158 31 4 0 1 1 5 3002 31 5 0 1 0 1 1780 31 6 0 1 1 5 1453 31 7 1 1 1 2 868 31 8 0 1 0 1 1079 31 9 1 1 0 1 1133 31 10 1 0 0 1 4158 31 11 0 1 1 2 595 31 12 1 0 0 1 1918 31 13 0 1 0 1 4063 31 14 1 1 1 2 1459 31 15 1 0 0 1 2627 32 2.5 0 1 1 5 1453 32 2.5 0 1 1 4 1529 32 2.5 0 1 0 1 1780 32 2.5 0 1 1 5 3002 32 6 0 1 0 2 506 32 6 0 1 1 2 595 32 6 1 1 1 5 1158 32 8 1 1 0 1 1133 32 11 1 1 1 2 868 32 11 0 1 0 1 1079 32 11 1 1 1 2 1459 32 11 1 0 0 1 2627 32 11 1 0 0 1 4158 32 14.5 1 0 0 1 1918 32 14.5 0 1 0 1 4063 33 1 0 1 1 5 3002 33 2 0 1 1 4 1529 33 3 0 1 0 1 1780 33 4 1 1 1 2 1459 33 5 0 1 1 5 1453 33 6 1 0 0 1 1918 33 7 1 1 1 2 868 33 8 1 1 1 5 1158 33 9 1 1 0 1 1133 33 10 1 0 0 1 4158 33 11 0 1 1 2 595 33 12 0 1 0 2 506 33 13 0 1 0 1 4063 33 14 0 1 0 1 1079 33 15 1 0 0 1 2627 34 1.5 0 1 1 4 1529 34 1.5 0 1 1 5 3002 34 3 0 1 0 2 506 34 5 1 1 1 2 868 34 5 1 1 1 5 1158 34 5 0 1 1 5 1453 34 7.5 0 1 0 1 1079 34 7.5 0 1 0 1 1780 34 9.5 0 1 1 2 595 34 9.5 1 0 0 1 1918 34 11.5 1 1 0 1 1133 34 11.5 1 0 0 1 4158 34 13 1 1 1 2 1459 34 14 0 1 0 1 4063 34 15 1 0 0 1 2627 35 1 1 1 1 2 868 35 2 0 1 1 5 3002 35 3 1 1 1 5 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1 4 2241 104 1 0 1 0 5 3048 104 2 1 0 1 5 160 104 3 0 0 0 1 1638 104 4 0 1 1 4 2241 104 5 0 1 0 1 1489 104 6 0 1 0 2 4153 104 7 1 0 0 2 1974 104 8 0 1 0 1 365 104 9 0 1 0 2 4207 104 10 1 0 0 1 694 104 11 0 1 0 2 1658 104 12 0 1 0 3 3001 104 13 1 1 0 2 2403 104 14 0 1 0 1 1946 104 15 0 1 0 1 2044 105 1 0 1 1 4 2241 105 2 0 1 0 1 365 105 3 0 1 0 5 3048 105 4 0 1 0 2 4207 105 5 0 0 0 1 1638 105 6 1 0 1 5 160 105 7 1 0 0 1 694 105 8 0 1 0 3 3001 105 9 1 0 0 2 1974 105 10 1 1 0 2 2403 105 11 0 1 0 2 1658 105 12 0 1 0 1 1946 105 13 0 1 0 1 2044 105 14 0 1 0 1 1489 105 15 0 1 0 2 4153 106 1 1 0 1 5 160 106 2 0 1 0 5 3048 106 3.5 1 1 0 2 2403 106 3.5 0 1 0 2 4207 106 5 0 1 0 2 1658 106 6 0 1 0 1 2044 106 7 0 1 0 3 3001 106 8 0 1 1 4 2241 106 9 1 0 0 1 694 106 10 1 0 0 2 1974 106 11 0 0 0 1 1638 106 12 0 1 0 1 1946 106 13 0 1 0 1 365 106 14 0 1 0 1 1489 106 15 0 1 0 2 4153 ; /* ---------------- PTSD Data Set ---------------- Data described in Chapter 8 of P.D. Allison, "Logistic Regression Using the SAS System: Theory and Application." */ data ptsd; input subjid ptsd control problems sevent cohes time; datalines; 15 0 3.2222222222 5.625 1 8 1 15 0 3.1666666667 5.375 0 8 2 15 0 3.2777777778 3.75 1 8 3 18 1 2.5555555556 9.25 0 8 1 18 0 3.4444444444 4.375 0 8 2 18 0 3.3333333333 2.375 0 8 3 19 1 2.7222222222 7.75 1 7 1 19 1 2.7777777778 7.75 1 7 2 19 0 2.7777777778 7.5 1 7 3 23 0 3.3888888889 7.75 0 8 1 23 1 3.2777777778 7.25 1 8 2 23 0 3.3333333333 6.25 0 8 3 24 0 3.1666666667 6.875 0 9 1 24 0 3.8888888889 6.875 0 9 2 24 0 3.9444444444 4.375 0 9 3 29 1 3.2777777778 6.125 1 8 1 29 0 3.3333333333 5.875 0 8 2 29 0 3.9444444444 2.125 1 8 3 30 0 3.3333333333 5.5 0 9 1 30 0 3.6666666667 4.375 0 9 2 30 0 3.3888888889 3.75 0 9 3 31 0 2.8888888889 6 1 8 1 31 1 3.1111111111 7.125 2 8 2 31 0 3.2222222222 5.875 1 8 3 32 0 3.3333333333 5.5 1 8 1 32 0 3.6111111111 4.25 0 8 2 32 0 3.9444444444 3.375 0 8 3 33 0 3.6666666667 4.5 0 9 1 33 0 3.6111111111 2.875 1 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7 1 2 2 523 0 3.3333333333 5.25 0 2 3 529 1 2.5555555556 7.75 2 4 1 529 1 2.7222222222 7.375 0 4 2 529 1 3.3888888889 7.75 1 4 3 531 0 3.8888888889 4.125 0 7 1 531 0 4 3.25 1 7 2 531 0 3.7777777778 2.25 1 7 3 532 0 3.7777777778 5.875 0 9 1 532 0 4 5.375 0 9 2 532 0 4 3.125 0 9 3 536 1 2.4444444444 6.875 0 6 1 536 0 2.5555555556 5.875 0 6 2 536 1 3.5555555556 7.25 0 6 3 538 0 3.6111111111 6.5 0 8 1 538 0 3.1111111111 4.375 0 8 2 538 0 3.3888888889 4.125 0 8 3 539 0 2.3888888889 7.875 1 7 1 539 0 2.8888888889 6.75 0 7 2 539 0 3.0555555556 6.5 2 7 3 545 1 3.3333333333 7.5 0 9 1 545 1 4 5.125 0 9 2 545 1 2.8333333333 6.125 1 9 3 551 0 2.9444444444 6.125 0 9 1 551 0 3.2222222222 7.125 0 9 2 551 0 3.3888888889 2.625 0 9 3 554 0 2.7777777778 9.75 1 7 1 554 1 3.6666666667 8.75 0 7 2 554 1 3.2222222222 9.25 2 7 3 557 1 2.4444444444 7.75 0 9 1 557 1 3.0555555556 7.75 0 9 2 557 0 2.7222222222 6.375 2 9 3 558 1 3.3888888889 7.75 2 8 1 558 0 3.6111111111 7.25 1 8 2 558 0 3.6111111111 2.625 0 8 3 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----------------- Data described in Chapter 8 of P.D. Allison, "Logistic Regression Using the SAS System: Theory and Application." */ data postdoc; input pdoc age mar doc und ag arts cits docid; datalines; 0 29 1 362 7 0 1 2 1402 1 32 1 210 6 0 1 4 1250 1 26 1 359 6 0 0 1 1399 0 25 1 181 3 0 0 1 1221 1 30 1 429 7 0 0 1 1469 1 28 1 359 6 0 1 0 1399 1 30 1 210 4 0 0 0 1250 1 40 1 347 4 0 0 0 1387 0 30 1 210 5 0 1 2 1250 1 28 1 359 7 0 5 32 1399 0 29 1 447 4 0 0 0 1487 1 28 1 276 5 0 1 0 1316 0 41 1 261 3 0 0 0 1301 1 27 1 226 7 0 0 1 1266 1 35 1 359 6 0 0 1 1399 1 30 0 341 5 0 7 16 1381 0 28 0 226 1 0 1 1 1266 1 28 1 429 4 0 3 3 1469 0 27 0 359 3 0 0 0 1399 1 27 0 205 4 0 0 0 1245 1 27 0 276 5 0 0 0 1316 0 37 1 347 7 0 1 2 1387 1 26 1 210 7 0 1 4 1250 0 34 1 236 5 0 0 1 1276 0 35 0 359 5 0 0 1 1399 1 31 0 341 7 0 3 7 1381 1 27 0 214 6 0 0 0 1254 1 37 1 250 5 0 2 2 1290 1 26 1 261 7 0 2 7 1301 0 27 1 181 5 0 0 1 1221 1 27 1 226 4 0 0 0 1266 1 27 1 362 6 0 0 1 1402 1 30 1 347 4 0 1 2 1387 0 30 1 359 9 0 0 1 1399 0 25 0 181 3 0 1 5 1221 1 29 1 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1336 0 32 1 239 5 1 3 4 1279 0 33 1 239 8 1 1 1 1279 0 28 1 296 6 1 2 15 1336 0 28 1 200 3 1 2 0 1240 1 30 1 340 4 1 1 1 1380 0 29 1 286 4 1 10 23 1326 1 36 0 286 5 1 0 1 1326 1 26 1 296 4 1 0 0 1336 1 26 0 296 5 1 0 1 1336 0 32 1 296 4 1 1 5 1336 0 31 1 296 4 1 2 0 1336 0 31 1 296 4 1 0 0 1336 0 35 1 296 5 1 0 0 1336 1 34 1 436 7 1 0 1 1476 0 30 1 436 7 1 0 1 1476 1 28 1 214 4 1 0 0 1254 0 32 1 436 8 1 0 1 1476 0 26 1 436 5 1 1 6 1476 0 28 1 0 7 1 0 0 1040 0 26 1 436 2 1 3 22 1476 0 27 1 436 4 1 2 1 1476 0 29 1 436 2 1 0 0 1476 0 26 1 436 5 1 1 0 1476 1 28 0 436 7 1 0 0 1476 1 26 0 436 4 1 0 0 1476 0 36 1 436 7 1 0 0 1476 0 26 1 436 5 1 0 1 1476 1 35 0 436 9 1 0 0 1476 1 26 1 436 7 1 0 1 1476 0 34 1 436 5 1 0 2 1476 1 28 1 392 5 1 1 1 1432 1 30 1 436 5 1 0 2 1476 0 29 1 436 4 1 0 2 1476 0 29 1 436 4 1 0 1 1476 0 32 1 214 4 1 0 1 1254 0 32 1 130 3 1 3 6 1170 0 34 1 237 5 1 0 0 1277 0 28 1 436 4 1 0 0 1476 1 27 0 436 4 1 0 1 1476 1 26 1 436 5 1 2 7 1476 0 40 1 180 8 1 7 3 1220 0 27 1 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1357 0 32 1 217 5 1 1 7 1257 0 34 1 160 3 1 0 1 1200 1 31 1 333 5 1 0 1 1373 1 27 1 340 5 1 0 0 1380 1 27 1 333 5 1 0 1 1373 0 30 1 333 3 1 0 0 1373 0 34 1 174 3 1 0 1 1214 0 43 1 217 3 1 1 6 1257 0 28 1 217 3 1 0 4 1257 0 40 1 217 3 1 2 3 1257 0 28 1 317 4 1 0 0 1357 0 31 1 186 4 1 0 1 1226 0 38 1 174 7 1 0 0 1214 0 32 1 0 3 1 0 1 1040 1 28 1 249 4 1 0 0 1289 1 29 0 333 4 1 0 2 1373 1 34 1 340 4 1 0 1 1380 1 25 0 333 7 1 0 0 1373 0 27 1 333 3 1 0 0 1373 1 29 0 317 5 1 0 0 1357 0 29 1 340 4 1 4 9 1380 1 27 0 340 5 1 2 40 1380 0 29 1 217 6 1 0 0 1257 ; /* ----------------- CASECONT Data Set ----------------- Data described in Chapter 8 of P.D. Allison, "Logistic Regression Using the SAS System: Theory and Application." */ data casecont; input pubhouse staybaby black kids doubleup age days casenum; datalines; 0 1 1 0 1 17.5 8 1994662001 0 0 1 1 1 18.3 8 1994662001 0 1 0 2 1 20.9 10 0189633001 0 0 0 1 0 32.9 10 0189633001 0 1 0 1 0 29.5 10 4435941001 0 0 1 2 1 31.8 10 4435941001 0 1 1 5 0 39.3 11 4257996002 0 0 0 1 0 34.9 11 4257996002 0 1 1 3 0 19.6 12 1761045001 0 0 0 1 1 20 12 1761045001 0 1 0 0 0 33.5 13 1572302001 0 0 1 1 1 21.9 13 1572302001 0 1 0 1 0 28.6 20 4293147001 0 0 1 1 1 20.2 20 4293147001 0 1 0 2 1 21.9 20 2903906001 0 0 1 1 0 35.7 20 2903906001 0 1 0 1 1 32.2 24 4124206001 0 0 1 1 0 22.3 24 4124206001 0 1 1 1 1 21.7 24 7916104001 0 0 1 1 1 20.8 24 7916104001 0 1 1 1 0 34.5 25 3927579001 0 0 1 0 0 31.4 25 3927579001 0 1 0 2 0 21.9 27 0730299001 0 0 1 5 0 27.2 27 0730299001 0 1 1 1 0 24.5 29 3746460001 0 0 0 3 0 26.4 29 3746460001 0 1 1 0 0 21.4 30 0580478001 0 0 0 1 1 20 30 0580478001 0 1 1 0 1 33.3 32 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413 0647639001 1 1 1 2 1 26.1 414 7837362001 0 0 0 2 0 39.5 414 7837362001 0 1 1 2 0 32.1 415 3832514001 1 0 0 2 0 25.7 415 3832514001 1 1 1 1 1 33.3 415 4015297001 1 0 1 1 0 30 415 4015297001 1 1 1 2 0 25.7 416 4531703001 1 0 1 2 0 36.1 416 4531703001 1 1 1 1 1 24.2 417 7621081001 1 0 1 2 1 27.8 417 7621081001 1 1 1 3 0 28.2 417 7907586001 0 0 1 2 1 22.1 417 7907586001 0 1 1 2 0 23.7 417 0382941001 1 0 1 2 0 32.8 417 0382941001 1 1 1 2 1 26.7 418 4387773002 1 0 0 5 0 35.3 418 4387773002 1 1 1 2 0 27.4 418 1312054001 1 0 1 2 1 38 418 1312054001 1 1 1 1 1 27.8 419 4248235001 1 0 1 3 0 38 419 4248235001 1 1 1 5 0 20.9 422 1116617001 1 0 1 0 1 23.7 422 1116617001 1 1 1 3 1 23 422 0692461001 1 0 1 1 0 34.3 422 0692461001 1 1 1 1 1 33.5 425 4076831001 1 0 0 1 1 22.2 425 4076831001 1 1 1 2 0 27.3 426 7546909001 0 0 1 2 0 20.2 426 7546909001 1 1 0 2 0 30.3 426 4664021001 1 0 1 2 0 23.3 426 4664021001 1 1 1 2 0 35.4 427 3640131001 1 0 1 1 0 35.7 427 3640131001 0 1 1 3 0 26.6 427 0138250001 1 0 1 1 0 23.6 427 0138250001 0 1 0 2 1 21.6 430 1262949001 0 0 1 1 1 27.1 430 1262949001 1 1 1 1 0 28.6 431 7975624001 1 0 0 1 1 20.3 431 7975624001 1 1 0 2 0 21.7 432 0601330001 1 0 0 3 0 30 432 0601330001 0 1 1 1 0 29.1 432 3935660001 0 0 0 1 0 27 432 3935660001 0 1 1 1 1 35.9 432 7856943001 1 0 1 2 1 36.2 432 7856943001 0 1 1 1 0 23.1 433 4613354001 1 0 1 2 1 23.3 433 4613354001 1 1 1 2 1 19.1 433 1154625001 1 0 1 2 0 30 433 1154625001 1 1 0 1 0 26.2 434 7509830001 1 0 1 1 0 21.6 434 7509830001 1 1 1 2 0 22.2 434 0669816001 1 0 0 4 0 28.9 434 0669816001 1 1 1 2 1 21.8 435 0904608001 1 0 1 1 0 28.1 435 0904608001 1 1 1 2 1 25.8 436 4528732001 1 0 1 2 1 25.3 436 4528732001 0 1 1 1 0 29.1 438 0480556001 0 0 1 4 0 27.9 438 0480556001 1 1 1 2 1 20.6 438 0257970001 1 0 1 4 1 24.2 438 0257970001 1 1 1 1 0 28.8 439 4192451001 0 0 0 3 0 31.4 439 4192451001 1 1 0 4 0 25.9 442 4653337001 0 0 0 1 0 24.6 442 4653337001 0 1 1 4 1 26 443 4536424001 1 0 0 1 1 23 443 4536424001 1 1 1 3 0 21.9 448 4637555001 0 0 0 3 0 33.4 448 4637555001 1 1 0 2 0 35.1 449 7495216001 1 0 0 4 0 26.4 449 7495216001 1 1 1 1 1 23.3 450 7357348001 0 0 1 1 1 29.2 450 7357348001 0 1 1 1 0 29.6 450 0033011001 1 0 1 1 1 26.5 450 0033011001 1 1 1 7 1 29.5 452 4157413001 0 0 1 3 1 25.3 452 4157413001 1 1 1 1 1 24.5 452 4257696001 1 0 1 2 0 33.6 452 4257696001 0 1 1 2 1 27.1 453 0448792001 0 0 1 1 1 23.1 453 0448792001 1 1 0 2 0 27.3 454 0543752001 1 0 1 2 1 36.7 454 0543752001 1 1 1 5 1 23.9 455 4364170001 1 0 0 1 0 30.9 455 4364170001 1 1 1 2 1 34.2 456 3919340002 0 0 0 1 0 36.1 456 3919340002 1 1 1 2 0 29.8 459 4576675001 1 0 1 1 0 30.9 460 4576675001 1 1 1 2 0 21.8 460 7304344001 1 0 0 3 0 34.3 460 7304344001 1 1 1 1 1 29.3 461 4468490001 1 0 0 0 0 36.4 461 4468490001 1 1 1 1 1 21.8 462 1214284001 1 0 0 2 0 35.8 462 1214284001 1 1 1 4 1 27.2 463 4445018001 0 0 1 1 1 27.5 463 4445018001 1 1 1 2 0 18.7 464 0768129001 1 0 1 2 1 30.3 464 0768129001 1 1 1 5 0 34.2 465 3745478001 0 0 1 3 0 28 465 3745478001 1 1 0 6 0 37.9 467 0309073001 1 0 0 2 0 18.4 467 0309073001 0 1 1 3 1 21.6 468 0402952001 1 0 1 4 0 22.6 468 0402952001 1 1 1 1 1 32 469 4024885001 1 0 1 1 0 24.2 469 4024885001 0 1 1 3 0 20.6 470 1298413001 1 0 1 5 0 34.5 470 1298413001 1 1 1 3 0 26.8 471 4369139001 1 0 1 1 1 33.3 471 4369139001 0 1 0 2 0 21.7 471 1165135001 1 0 1 1 0 28.4 471 1165135001 1 1 0 4 0 35.6 473 4545881001 1 0 1 2 0 34.3 473 4545881001 0 1 1 2 1 20.5 473 2222443001 0 0 1 1 1 25.1 474 2222443001 1 1 1 4 1 19.2 479 0622801001 1 0 0 2 0 39.5 479 0622801001 1 1 0 2 1 21.5 480 0009762001 0 0 1 3 1 37.7 480 0009762001 1 1 1 2 1 19.5 481 0481810001 1 0 1 5 0 35.6 482 0481810001 0 1 1 2 1 18.8 484 0366566001 1 0 0 3 0 23.7 484 0366566001 1 1 0 5 1 24.3 484 1105867001 1 0 1 1 0 34.6 485 1105867001 1 1 1 4 0 23.2 484 4671542001 1 0 0 2 1 32.4 486 4671542001 1 1 1 6 1 34.4 486 0261797001 1 0 0 1 0 32 486 0261797001 1 1 1 2 1 20.1 489 0767189001 1 0 1 3 0 24.2 489 0767189001 1 1 1 3 1 22.9 491 0621351001 1 0 1 3 1 23.3 491 0621351001 1 1 1 2 1 20.3 492 0347518001 1 0 1 0 0 30.8 492 0347518001 1 1 1 2 1 20.3 493 0627715001 1 0 0 2 0 38.5 493 0627715001 1 1 1 3 1 29.1 495 4501418001 1 0 1 1 0 36.2 495 4501418001 0 1 0 3 0 30.9 495 0849042001 0 0 0 1 1 25 495 0849042001 1 1 0 6 0 38.7 497 4585773001 0 0 1 2 1 23.2 497 4585773001 0 1 1 1 0 28.9 500 0554818001 1 0 1 1 1 31.1 500 0554818001 1 1 0 2 0 24.5 501 0006034001 1 0 1 0 1 36.3 502 0006034001 1 1 0 2 1 21 501 7326438001 1 0 1 1 0 29.9 502 7326438001 1 1 1 2 1 20.6 501 1038707001 1 0 1 2 1 25.9 503 1038707001 0 1 0 2 1 19.5 505 2005924001 1 0 1 3 1 34.4 505 2005924001 1 1 0 2 1 22.2 509 0025548001 1 0 0 2 0 31.6 509 0025548001 1 1 1 3 1 29 509 4587777001 1 0 1 2 1 24.5 509 4587777001 1 1 1 1 0 27.8 514 4423650001 0 0 0 1 0 34 514 4423650001 1 1 1 2 0 26.5 514 7657661001 0 0 0 2 1 36.2 514 7657661001 1 1 1 2 0 31.6 517 7527898001 1 0 1 2 0 33.7 517 7527898001 1 1 1 5 1 18.8 518 1390592001 0 0 1 5 0 31.8 518 1390592001 1 1 1 3 0 25.5 518 0595713001 1 0 0 3 0 34.9 518 0595713001 1 1 1 3 0 32.6 519 7986099001 1 0 0 4 0 26.4 519 7986099001 1 1 1 1 1 30.4 522 4047295001 0 0 0 2 0 23.6 522 4047295001 1 1 1 1 1 29.7 523 0593304001 1 0 0 3 0 20.5 523 0593304001 1 1 0 3 0 31.1 527 4611523001 1 0 0 4 1 28.7 527 4611523001 1 1 0 2 1 23.8 528 2761409001 1 0 1 3 0 21.3 529 2761409001 1 1 0 4 0 27.5 529 1571893001 0 0 1 4 0 29 529 1571893001 0 1 1 4 1 22.9 530 4654829001 1 0 1 1 1 21.1 531 4654829001 0 1 1 1 0 34 531 3965621001 1 0 0 3 0 28.9 532 3965621001 0 1 1 3 0 29.9 539 4608525001 1 0 1 2 1 24.2 540 4608525001 1 1 1 1 1 30.6 541 7942021001 0 0 1 1 1 35 541 7942021001 1 1 1 4 1 24 541 4616216001 1 0 0 2 0 36.4 541 4616216001 1 1 1 1 1 20.8 542 0366237001 1 0 0 2 0 36.2 542 0366237001 0 1 1 1 1 25 545 0654636001 1 0 0 3 0 18.5 545 0654636001 1 1 1 7 0 25.5 546 0255298001 1 0 1 3 0 32.1 546 0255298001 0 1 0 4 0 22.4 553 0031085001 0 0 1 2 0 25.6 553 0031085001 1 1 1 2 0 26.4 555 4521316001 0 0 1 1 0 38.4 555 4521316001 0 1 1 2 0 22.9 555 3511878001 1 0 0 2 1 27.6 556 3511878001 0 1 0 4 0 29.2 555 0349788001 1 0 1 1 0 33.7 557 0349788001 1 1 1 1 1 37.5 557 4018161001 1 0 1 2 0 21.1 557 4018161001 0 1 1 3 0 21.2 560 0703201001 1 0 1 3 1 23.9 562 0703201001 1 1 0 3 0 28 568 7822472001 1 0 1 1 1 29.5 568 7822472001 0 1 0 2 1 20.6 572 0457692001 1 0 1 2 0 26.3 574 0457692001 1 1 1 1 1 32.9 572 7499375001 1 0 1 3 0 39.5 575 7499375001 1 1 1 2 0 19.3 572 3205137001 1 0 0 3 0 39 576 3205137001 1 1 0 2 1 31.1 582 0533835001 1 0 0 1 1 37.3 582 0533835001 1 1 1 2 0 21.2 587 0284348001 1 0 1 2 0 28.4 587 0284348001 1 1 1 4 1 34.4 588 2603487001 1 0 1 1 0 30.6 589 2603487001 1 1 1 2 0 34.8 590 4211815001 1 0 0 1 1 26.5 590 4211815001 1 1 1 3 0 26.1 590 4362058001 1 0 1 3 0 28.1 590 4362058001 0 1 1 5 1 24.7 593 0799286001 1 0 0 0 0 16.7 593 0799286001 1 1 1 2 0 28.5 593 4395990001 0 0 1 1 0 26.2 594 4395990001 1 1 1 4 0 34.8 594 4095631001 1 0 0 3 0 31.3 597 4095631001 0 1 1 1 1 22.4 595 7589734001 1 0 0 3 0 31.9 597 7589734001 1 1 0 1 0 24 600 4269724001 1 0 1 1 0 24 600 4269724001 1 1 1 1 0 28.5 606 4250372001 1 0 1 2 0 21.9 611 4250372001 1 1 0 3 0 26.9 606 7508049001 1 0 1 3 0 29 612 7508049001 1 1 1 3 0 23.9 610 0511471001 1 0 0 0 0 39.7 613 0511471001 1 1 0 1 1 26.3 616 4423159001 1 0 1 3 0 35.9 617 4423159001 1 1 0 3 0 20.6 618 7999289001 0 0 1 2 0 23.2 619 7999289001 1 1 0 1 1 33.2 619 3853904001 0 0 1 2 0 36 620 3853904001 1 1 0 3 0 22.2 631 4538389001 1 0 1 1 0 23.9 631 4538389001 0 1 1 2 0 23.5 634 0960675001 1 0 0 2 0 35.1 637 0960675001 1 1 0 5 0 17.6 634 2134923001 1 0 0 4 0 32.4 637 2134923001 1 1 1 1 1 34.8 640 4239421001 1 0 1 2 1 20.7 648 4239421001 0 1 1 2 0 39.2 646 3720111001 1 0 1 2 0 30.4 651 3720111001 1 1 1 1 1 30.7 661 4262298001 1 0 0 3 0 23.6 663 4262298001 0 1 1 5 0 30.5 661 4342868001 1 0 1 0 0 32.4 665 4342868001 1 1 0 6 0 25 663 1846667001 0 0 1 1 0 31 665 1846667001 1 1 0 1 0 21.9 665 0724795001 1 0 0 2 1 36.1 666 0724795001 0 1 1 1 1 22.9 666 0616697001 1 0 1 2 0 35.9 670 0616697001 1 1 1 5 0 28.7 670 4679253001 1 0 0 3 0 34.4 672 4679253001 1 1 1 4 0 28.4 671 7532705003 0 0 1 2 0 22.6 674 7532705003 1 1 0 1 1 31.4 673 0249980001 1 0 1 3 1 34.2 676 0249980001 1 1 0 3 0 30 686 4250105001 1 0 1 2 0 31.2 686 4250105001 0 1 1 5 0 38.8 686 3398318001 1 0 1 1 1 28.1 688 3398318001 1 1 1 3 1 25.5 687 0217890001 1 0 1 2 1 27.6 690 0217890001 0 1 1 1 0 30.8 701 4673520001 1 0 0 1 0 39.2 701 4673520001 1 1 0 2 0 24.2 705 1380868001 1 0 0 6 0 39.1 707 1380868001 1 1 1 2 0 38.4 716 3756940001 1 0 1 6 0 37.5 718 3756940001 1 1 1 1 1 31.1 716 4522443001 1 0 1 1 0 25 726 4522443001 1 1 1 2 0 23.9 722 4609235001 1 0 0 3 0 30.7 727 4609235001 1 1 0 1 0 33.2 742 4233045001 1 0 0 1 0 30.4 742 4233045001 1 1 0 1 0 37.6 746 3733192001 1 0 1 4 0 36.6 751 3733192001 1 1 0 3 0 24.3 751 4528136001 1 0 1 2 0 35.9 758 4528136001 1 1 0 3 0 23.2 759 0174247001 0 0 1 1 0 28.7 777 0174247001 1 1 1 2 0 28.3 760 4437624001 1 0 1 1 0 22.8 785 4437624001 1 1 1 1 0 24.2 763 4670354001 1 0 0 3 0 36.8 786 4670354001 1 1 1 7 0 32.7 767 2607241001 1 0 1 2 0 36.5 787 2607241001 1 1 1 8 0 31 769 4456719001 1 0 1 4 1 31.7 795 4456719001 0 1 1 1 0 29.9 771 0329727001 1 0 1 7 0 36.7 795 0329727001 0 1 0 4 1 18.3 771 2846679001 0 0 1 6 0 33.8 799 2846679001 1 1 1 4 0 28.4 773 4505893001 0 0 1 2 0 39.5 803 4505893001 0 1 1 2 0 39.9 796 0032567001 1 0 1 2 0 34.7 823 0032567001 1 1 0 6 0 20.4 820 4017093001 0 0 1 1 0 28.5 826 4017093001 1 1 1 3 1 25.9 821 7794857001 1 0 0 3 0 29.7 849 7794857001 1 1 1 2 0 31.2 824 0543777001 0 0 1 2 0 33.1 863 0543777001 1 1 1 3 0 33.4 845 3898075001 1 0 1 3 0 33.4 864 3898075001 1 1 0 1 0 38.4 852 3727115001 1 0 0 0 0 32.7 869 3727115001 1 1 1 1 0 33 871 3962052001 0 0 0 0 0 37.5 882 3962052001 1 1 1 3 0 28.2 872 7311680001 1 0 1 2 0 39.6 887 7311680001 1 1 0 1 0 28.2 882 4342798001 1 0 1 3 0 30.3 898 4342798001 1 1 1 8 0 38.5 884 3521667001 0 0 1 1 0 18.6 901 3521667001 1 1 0 4 0 39.8 936 3834402001 1 0 0 1 0 34.1 943 3834402001 0 1 1 3 0 34.8 1044 3715671001 1 0 0 3 0 35 1146 3715671001 0 1 1 2 0 35.4 1085 0009614001 1 0 1 4 0 18.9 1294 0009614001 1 1 1 10 0 21.3 1422 2600041001 0 0 1 5 0 38.6 1459 2600041001 1 1 1 8 0 25 1780 0370229001 1 0 1 2 0 32.4 1785 0370229001 ; /* ----------------- PROGNOSI Data Set ----------------- Data described in Chapter 9 of P.D. Allison, "Logistic Regression Using the SAS System: Theory and Application." */ data prognosi; input lengthpx ptage ptsex ezcompt mdlikept surgeon claims minutes; datalines; 12 20 0 5 4 1 2 7 0 24 0 4 4 1 7 6 1 26 0 3 3 1 2 20 0 57 0 5 4 1 2 15 24 38 1 5 3 1 4 5 4 33 1 5 4 1 0 5 3 58 0 5 5 1 2 15 3 51 0 5 5 1 3 5 15 51 1 5 3 1 6 6 2 26 1 3 3 1 2 20 2 50 0 5 4 1 0 10 24 54 1 5 5 1 0 . 0 28 0 4 4 1 3 10 8 54 1 2 3 1 3 17 6 71 1 5 4 1 0 15 20 49 1 4 4 1 0 7 14 58 1 5 5 1 0 30 9 53 0 4 3 1 3 10 0 71 1 4 4 1 4 20 4 18 0 4 3 1 0 20 2 32 1 5 3 1 8 . 11 19 0 5 5 1 4 15 0 72 0 5 4 1 3 30 21 35 1 5 5 1 0 15 1 43 1 3 3 1 4 5 0 67 0 5 5 0 0 5 2 82 1 5 5 0 0 15 0 70 0 4 4 0 0 15 4 75 1 3 4 0 2 10 0 87 1 2 3 0 0 15 0 74 1 5 5 0 2 20 0 83 0 4 4 0 0 14 0 47 1 5 5 0 3 12 0 81 0 4 5 0 2 15 0 42 1 2 2 0 0 30 2 50 0 4 4 0 0 10 1 60 1 5 5 0 0 10 0 42 1 5 4 0 2 8 2 76 1 5 3 0 0 20 10 54 0 5 4 0 0 15 0 48 1 4 3 0 4 25 0 61 0 5 4 0 0 20 0 53 0 4 3 0 0 25 4 72 1 5 5 0 2 20 0 52 0 4 3 0 3 10 1 75 1 2 3 0 0 12 0 51 0 5 5 0 0 . 0 62 0 3 3 0 3 20 9 68 1 3 3 0 2 15 1 48 0 5 4 1 5 5 6 59 1 5 4 1 5 12 1 44 1 5 4 1 3 20 0 26 1 4 4 1 0 20 0 32 1 5 4 1 0 15 5 53 0 5 4 1 3 10 0 70 1 5 5 1 3 12 2 53 1 5 5 1 0 8 6 44 1 5 4 1 11 8 17 50 1 5 5 1 0 15 5 63 0 5 4 1 5 5 2 74 1 5 5 1 0 10 0 26 1 5 5 1 3 15 7 41 1 5 4 1 3 5 12 35 0 5 4 1 3 25 8 51 0 3 1 1 0 10 20 72 1 5 5 1 4 18 3 56 0 4 4 1 0 15 0 84 1 5 5 1 0 10 0 58 0 5 2 1 0 15 0 32 0 4 3 1 0 10 9 65 1 5 5 1 0 15 5 63 0 2 3 1 6 15 0 42 0 5 5 1 0 3 7 32 0 5 4 1 3 5 3 38 1 4 4 1 2 15 4 57 1 4 4 1 4 15 6 57 1 5 4 1 0 10 1 52 0 3 2 1 6 15 0 30 0 5 3 1 0 10 0 25 0 4 4 1 4 15 7 25 0 4 4 1 5 20 3 67 1 3 3 1 5 10 8 41 0 3 2 1 2 18 2 40 1 5 4 1 0 15 0 41 0 5 5 1 3 20 9 39 0 3 3 1 0 10 0 38 1 3 2 1 2 15 0 46 0 5 4 1 0 15 7 62 0 5 5 1 0 20 2 76 1 5 4 1 3 10 1 44 0 3 3 0 2 10 0 34 0 5 5 0 3 45 2 61 0 4 4 0 4 . 0 60 0 5 5 0 0 12 4 44 1 5 5 0 2 45 0 42 1 5 5 0 3 15 4 78 0 4 5 0 2 15 0 86 1 3 4 0 0 30 0 38 0 4 3 0 4 10 0 64 1 5 4 0 2 6 9 73 1 2 4 0 3 12 0 22 0 4 4 0 2 5 4 47 0 4 4 0 5 13 0 29 0 4 3 0 2 25 0 87 0 2 4 0 0 15 0 81 0 4 5 0 3 20 6 78 0 4 4 0 0 10 0 71 0 3 3 0 2 5 0 49 0 2 3 0 2 20 0 60 0 4 4 0 3 12 1 69 0 5 5 0 0 17 2 73 1 5 5 0 0 15 0 58 0 4 5 0 0 22 0 44 1 5 4 0 0 15 0 55 1 4 3 0 0 30 1 71 0 4 3 0 0 20 6 22 1 5 4 0 0 15 0 40 0 5 4 0 3 15 1 84 0 2 5 0 0 20 0 75 0 4 4 0 2 10 2 53 1 3 3 0 2 15 2 68 0 4 4 0 3 10 2 49 1 5 3 0 0 15 2 73 0 5 4 0 0 10 0 56 0 4 2 0 0 15 ; /*------------ ROBUST Macro ------------*/ /********************************************************************* MACRO ROBUST produces robust estimates of the covariance matrix for the coefficients from PROC LOGISTIC or PROC PHREG when the data are clustered. One common application is to longitidunal data with each individual treated as a cluster. IML is required. The macro uses the method of Halbert White (1982) "Maximum likelihood estimation of misspecified models," Econometrica 50: 1-25. Author: Paul D. Allison, University of Pennsylvania allison@ssc.upenn.edu Adapted from an IML program written by Terry Therneau, Mayo Clinic. For PROC LOGISTIC, you must specify the OUTEST=name1 and COVOUT options on the PROC statement. You must also use the OUTPUT statement with OUT=name2 and DFBETAS=namelist. The namelist should have one name for each term in the model, including the intercept. There must also be a variable in the data set containing a unique value (either character or numeric) for each cluster. The macro is invoked after running the LOGISTIC procedure. For PROC PHREG, you must specify OUTEST=name1 on the PROC statement. (COVOUT is unncessary). You must also use the OUTPUT statement with OUT=name2 and DFBETA=namelist. The namelist should have one name for each variable in the model. There must also be a variable in the data set containing a unique value (either character or numeric) for each cluster. This variable must be added to the OUTPUT data set by using the ID statement. The macro is invoked after running the PHREG procedure. The macro has the following parameters: OUTEST Name of data set used in the OUTEST= option. OUT Name of data set used in the OUT= option. ID Name of variable containing a unique value for each cluster DF List of names used in the DFBETAS or DFBETA option. Examples of usage: proc logistic outest=a covout; model y = x z w; output out=b dfbetas=dint dx dz dw; run; %robust(outest=a, out=b, id=subjid, df=dint dx dz dw) proc phreg outest=a; model y*d(0) = x z w; id subjid; output out=b dfbeta= dx dz dw; run; %robust(outest=a, out=b, id=subjid, df=dx dz dw) BE CAREFUL: On the OUTPUT statement, it's DFBETAS in LOGISTIC but DFBETA in PHREG. (The former is standardized, the latter is not). Also PHREG does NOT have an intercept. ************************************************************** **************************************************************/ %macro robust(outest=a, out=_last_, id=id, df=); proc sort data=&out; by &id; run; proc means data=&out noprint; by &id; var &df; output out=_out1_(keep=&df) sum=&df; run; data _out1_; set; array d (*) &df; if d(1)=. then delete; run; data _reduce_; set &outest; array abc(*) _character_; length name $8; call vname(abc(1),name); if name ne '_LINK_' and _type_ eq 'COV' then delete; drop _lnlike_; run; proc iml; use _reduce_ where (_type_='COV'); read all into cov; use _reduce_ where (_type_='PARMS'); read all into b[colname=vname]; if ncol(cov)=0 then se=1; else se=sqrt(diag(cov)); use _out1_; read all into x; x=x*se; v=x`*x; se=sqrt(vecdiag(v)); wald=(b`/se)##2; p=1-probchi(wald,1); chi=wald||p; c={"Chi Square" "p-value"}; reset noname fuzz=.000001; print, "Robust Variance Matrix",, v[colname=vname rowname=vname]; print, "Standard Errors",, se[rowname=vname]; print, "Wald Statistics",, chi[rowname=vname colname=c]; quit; run; %mend robust; /************************************************************************* PROGRAMS ************************************************************************/ /* The following program is found on page 6 of */ /* "Logistic Regression Using the SAS System." */ PROC REG DATA=my.penalty; MODEL death=blackd whitvic serious; RUN; /* The following program is found on page 18 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DATA=my.penalty DESCENDING; MODEL death=blackd whitvic serious; RUN; /* The following program is found on page 21 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.penalty; MODEL death=blackd whitvic serious / DIST=BINOMIAL; RUN; /* The following program is found on page 24 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.penalty; CLASS culp; MODEL death = blackd whitvic culp / D=B; RUN; /* The following program is found on page 25 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.penalty; MODEL death = blackd whitvic culp blackd*whitvic / D=B; RUN; /* The following program is found on page 32 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DATA=my.penalty DES; MODEL death = blackd whitvic culp / CLPARM=BOTH; RUN; /* The following program is found on page 33 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.penalty; MODEL death = blackd whitvic culp / D=B WALDCI LRCI; RUN; /* The following program is found on page 40 of */ /* "Logistic Regression Using the SAS System." */ DATA compsep; INPUT x y; DATALINES; 1 0 2 0 3 0 4 1 5 1 6 1 ; PROC LOGISTIC DES; MODEL y = x; RUN; PROC GENMOD DATA=compsep; MODEL y = x / D=B; RUN; /* The following program is found on page 41 of */ /* "Logistic Regression Using the SAS System." */ DATA quasisep; INPUT x y; DATALINES; 1 0 2 0 3 0 4 0 4 1 5 1 6 1 ; PROC LOGISTIC DES; MODEL y = x; PROC GENMOD; MODEL y = x /D=B; RUN; /* The following program is found on page 43 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.penalty; WHERE blackd=0; CLASS culp; MODEL death = culp serious / D=B TYPE3; RUN; /* The following program is found on page 45 of */ /* "Logistic Regression Using the SAS System." */ DATA; SET my.penalty; IF culp=1 THEN culp=2; PROC GENMOD; WHERE blackd=0; CLASS culp; MODEL death=culp serious /D=B; RUN; /* The following program is found on page 46 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.penalty; WHERE blackd=0 AND culp > 1; CLASS culp; MODEL death=culp serious /D=B; RUN; /* The following program is found on page 47 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.penalty; WHERE blackd=0; CLASS culp; MODEL death=culp serious /D=B; CONTRAST 'culp1 v. culp5' CULP 1 0 0 0 -1; RUN; /* The following program is found on page 49 of */ /* "Logistic Regression Using the SAS System." */ PROC REG DATA=my.penalty; MODEL death = blackd whitvic serious1 serious2 / TOL VIF; RUN; /* The following program is found on page 50 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DES DATA=my.penalty; MODEL death = blackd whitvic serious1 serious2; OUTPUT OUT=a PRED=phat; DATA b; SET a; w = phat*(1-phat); PROC REG DATA=b; WEIGHT w; MODEL death = blackd whitvic serious1 serious2 / TOL VIF; RUN; /* The following program is found on page 52 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DES DATA=my.penalty; MODEL death = blackd whitvic culp / AGGREGATE SCALE=NONE; RUN; /* The following program is found on page 53 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.penalty; CLASS culp; MODEL death = blackd whitvic culp blackd*whitvic blackd*culp whitvic*culp blackd*whitvic*culp / D=B; RUN; /* The following program is found on page 54 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DES DATA=my.penalty; MODEL death = blackd whitvic culp / LACKFIT; RUN; /* The following program is found on page 60 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.penalty; MODEL death = culp blackd whitvic / D=B OBSTATS RESIDUALS; MAKE 'OBSTATS' OUT=a; RUN; /* The following program is found on page 63 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DES DATA=my.penalty; MODEL death = culp blackd whitvic; OUTPUT OUT=a(KEEP= death pred up lo chi dev) P=pred U=up L=lo RESCHI=chi RESDEV=dev; /* The following program is found on page 65 of */ /* "Logistic Regression Using the SAS System." */ PROC GPLOT DATA=b; PLOT dev*pred / VAXIS=AXIS1 HAXIS=AXIS1; SYMBOL V=DOT HEIGHT=.35; AXIS1 MINOR=NONE WIDTH=2 MAJOR=(WIDTH=2); RUN; /* The following program is found on page 71 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DES DATA=my.penalty; MODEL death = culp blackd whitvic / LINK=PROBIT; RUN; /* The following program is found on page 83 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.penalty; MODEL death = blackd / D=B; RUN; /* The following program is found on pages 83-84 of */ /* "Logistic Regression Using the SAS System." */ DATA tab4_1a; INPUT f blackd death; DATALINES; 22 0 1 28 1 1 52 0 0 45 1 0 ; PROC GENMOD DATA=tab4_1a; FREQ f; MODEL death = blackd / D=B; RUN; /* The following program is found on page 84 of */ /* "Logistic Regression Using the SAS System." */ DATA tab4_1b; INPUT death total blackd; DATALINES; 22 74 0 28 73 1 ; PROC GENMOD DATA=tab4_1b; MODEL death/total = blackd / D=B; RUN; /* The following program is found on page 85 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DATA=tab4_1b; MODEL death/total = blackd / AGGREGATE SCALE=N; RUN; /* The following program is found on page 86 of */ /* "Logistic Regression Using the SAS System." */ PROC FREQ DATA=tab4_1a; WEIGHT f; TABLES blackd*death / CHISQ CMH; RUN; /* The following program is found on page 88 of */ /* "Logistic Regression Using the SAS System." */ DATA interco; INPUT white male yes no; total=yes+no; DATALINES; 1 1 43 134 1 0 26 149 0 1 29 23 0 0 22 36 ; PROC GENMOD DATA=interco; MODEL yes/total=white male / D=B; RUN; /* The following program is found on page 89 of */ /* "Logistic Regression Using the SAS System." */ DATA; CHI=1-PROBCHI(.0583,1); PUT CHI; RUN; /* The following program is found on page 90 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=interco; MODEL yes/total=white male white*male/ D=B; RUN; /* The following program is found on page 92 of */ /* "Logistic Regression Using the SAS System." */ DATA working; INPUT france manual famanual total working; DATALINES; 1 1 1 107 85 1 1 0 65 44 1 0 1 66 24 1 0 0 171 17 0 1 1 87 24 0 1 0 65 22 0 0 1 85 1 0 0 0 148 6 ; PROC GENMOD DATA=working; MODEL working/total = france manual famanual / D=B; RUN; /* The following program is found on page 93 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=working; MODEL working/total = france manual famanual france*manual france*famanual manual*famanual / D=B; RUN; /* The following program is found on page 97-98 of */ /* "Logistic Regression Using the SAS System." */ DATA wisc; INPUT iq parent ses total coll; DATALINES; 1 1 1 353 4 1 1 2 234 2 1 1 3 174 8 1 1 4 52 4 1 2 1 77 13 1 2 2 111 27 1 2 3 138 47 1 2 4 96 39 2 1 1 216 9 2 1 2 208 7 2 1 3 126 6 2 1 4 52 5 2 2 1 105 33 2 2 2 159 64 2 2 3 184 74 2 2 4 213 123 3 1 1 138 12 3 1 2 127 12 3 1 3 109 17 3 1 4 50 9 3 2 1 92 38 3 2 2 185 93 3 2 3 248 148 3 2 4 289 224 4 1 1 77 10 4 1 2 96 17 4 1 3 48 6 4 1 4 25 8 4 2 1 92 49 4 2 2 178 119 4 2 3 271 198 4 2 4 468 414 ; PROC GENMOD DATA=wisc; CLASS iq ses; MODEL coll/total=iq ses parent / D=B TYPE3; RUN; /* The following program is found on page 99 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=wisc; CLASS iq ses; MODEL coll/total=iq|ses|parent @2/ D=B TYPE3; RUN; /* The following program is found on page 104-105 of */ /* "Logistic Regression Using the SAS System." */ DATA my.nihdoc; INPUT nih docs pdoc; DATALINES; .5 8 1 .5 9 3 .835 16 1 .998 13 6 1.027 8 2 2.036 9 2 2.106 29 10 2.329 5 2 2.523 7 5 2.524 8 4 2.874 7 4 3.898 7 5 4.118 10 4 4.130 5 1 4.145 6 3 4.242 7 2 4.280 9 4 4.524 6 1 4.858 5 2 4.893 7 2 4.944 5 4 5.279 5 1 5.548 6 3 5.974 5 4 6.733 6 5 7 12 5 9.115 6 2 9.684 5 3 12.154 8 5 13.059 5 3 13.111 10 8 13.197 7 4 13.433 86 33 13.749 12 7 14.367 29 21 14.698 19 5 15.440 10 6 17.417 10 8 18.635 14 9 21.524 18 16 ; PROC GENMOD DATA=my.nihdoc; MODEL pdoc/docs=nih / D=B; RUN; /* The following program is found on page 107 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DATA=my.nihdoc; MODEL pdoc/docs=nih / D=B AGGREGATE SCALE=WILLIAMS; RUN; /* The following program is found on page 110 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.nihdoc; MODEL pdoc/docs=nih docs/ D=B; RUN; /* The following program is found on page 115 of */ /* "Logistic Regression Using the SAS System." */ PROC CATMOD DATA=my.wallet; DIRECT male business punish explain; MODEL wallet = male business punish explain / NOITER; RUN; /* The following program is found on page 120 of */ /* "Logistic Regression Using the SAS System." */ MODEL wallet = _response_ male business punish explain / NOITER; /* The following program is found on page 120 of */ /* "Logistic Regression Using the SAS System." */ CONTRAST 'all' @1 male 1 @2 male -1, @1 business 1 @2 business -1, @1 punish 1 @2 punish -1, @1 explain 1 @2 explain -1; /* The following program is found on page 121 of */ /* "Logistic Regression Using the SAS System." */ MODEL wallet = male business punish explain male*business male*punish male*explain business*punish business*explain punish*explain / NOITER; /* The following program is found on page 122 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DATA=my.wallet; WHERE wallet NE 2; MODEL wallet=male business punish explain; RUN; PROC LOGISTIC DATA=my.wallet; WHERE wallet NE 1; MODEL wallet=male business punish explain; RUN; PROC LOGISTIC DATA=my.wallet; WHERE wallet NE 3; MODEL wallet=male business punish explain; RUN; /* The following program is found on page 124 of */ /* "Logistic Regression Using the SAS System." */ DATA my.afterlif; INPUT white female belief freq; DATALINES; 1 1 1 371 1 1 2 49 1 1 3 74 1 0 1 250 1 0 2 45 1 0 3 71 0 1 1 64 0 1 2 9 0 1 3 15 0 0 1 25 0 0 2 5 0 0 3 13 ; PROC CATMOD DATA=my.afterlif; WEIGHT freq; DIRECT white female; MODEL belief=white female / NOITER PRED; RUN; /* The following program is found on page 126 of */ /* "Logistic Regression Using the SAS System." */ PROC CATMOD DATA=my.afterlif; WEIGHT freq; DIRECT white female; POPULATION white female; MODEL belief= / NOITER PRED; RUN; /* The following program is found on page 134 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DATA=my.wallet; MODEL wallet = male business punish explain; RUN; /* The following program is found on page 136 of */ /* "Logistic Regression Using the SAS System." */ DATA a; SET my.wallet; IF wallet=1 THEN wallet=2; RUN; PROC LOGISTIC DATA=a; MODEL wallet = male business punish explain; RUN; /* The following program is found on page 137 of */ /* "Logistic Regression Using the SAS System." */ DATA a; SET my.wallet; IF wallet=3 THEN wallet=2; RUN; PROC LOGISTIC DATA=a; MODEL wallet = male business punish explain; RUN; /* The following program is found on page 143 of */ /* "Logistic Regression Using the SAS System." */ DATA happy; INPUT year married happy count; y84 = year EQ 2; y94 = year EQ 3; DATALINES; 1 1 1 473 1 1 2 493 1 1 3 93 1 0 1 84 1 0 2 231 1 0 3 99 2 1 1 332 2 1 2 387 2 1 3 62 2 0 1 150 2 0 2 347 2 0 3 117 3 1 1 571 3 1 2 793 3 1 3 112 3 0 1 257 3 0 2 889 3 0 3 234 ; /* The following program is found on page 144 of */ /* "Logistic Regression Using the SAS System." */ PROC LOGISTIC DATA=happy; FREQ count; MODEL happy = married y84 y94 / AGGREGATE SCALE=N; TEST y84, y94; RUN; /* The following program is found on page 147 of */ /* "Logistic Regression Using the SAS System." */ DATA a; SET happy; lesshap=happy GE 2; nottoo=happy EQ 3; RUN; PROC LOGISTIC DATA=a; FREQ count; MODEL lesshap=married y84 y94; RUN; PROC LOGISTIC DATA=a; FREQ count; MODEL nottoo=married y84 y94; RUN; /* The following program is found on page 149 of */ /* "Logistic Regression Using the SAS System." */ PROC CATMOD DATA=happy; WEIGHT count; DIRECT married y84 y94; RESPONSE ALOGIT; MODEL happy = _RESPONSE_ married y84 y94 / WLS; RUN; /* The following program is found on page 153-154 of */ /* "Logistic Regression Using the SAS System." */ DATA my.afqt; INPUT white old faed ed count; DATALINES; 1 0 1 1 39 1 0 1 2 29 1 0 1 3 8 1 0 2 1 4 1 0 2 2 8 1 0 2 3 1 1 0 3 1 11 1 0 3 2 9 1 0 3 3 6 1 0 4 1 48 1 0 4 2 17 1 0 4 3 8 1 1 1 1 231 1 1 1 2 115 1 1 1 3 51 1 1 2 1 17 1 1 2 2 21 1 1 2 3 13 1 1 3 1 18 1 1 3 2 28 1 1 3 3 45 1 1 4 1 197 1 1 4 2 111 1 1 4 3 35 0 0 1 1 19 0 0 1 2 40 0 0 1 3 19 0 0 2 1 5 0 0 2 2 17 0 0 2 3 7 0 0 3 1 2 0 0 3 2 14 0 0 3 3 3 0 0 4 1 49 0 0 4 2 79 0 0 4 3 24 0 1 1 1 110 0 1 1 2 133 0 1 1 3 103 0 1 2 1 18 0 1 2 2 38 0 1 2 3 25 0 1 3 1 11 0 1 3 2 25 0 1 3 3 18 0 1 4 1 178 0 1 4 2 206 0 1 4 3 81 DATA first; SET my.afqt; stage=1; advance = ed GE 2; RUN; DATA second; SET my.afqt; stage=2; IF ed=1 THEN DELETE; advance = ed EQ 3; RUN; DATA concat; SET first second; RUN; /* The following program is found on page 155 of */ /* "Logistic Regression Using the SAS System." */ DATA combined; SET my.afqt; stage=1; advance = ed GE 2; OUTPUT; stage=2; IF ed=1 THEN DELETE; advance = ed EQ 3; OUTPUT; RUN; PROC GENMOD DATA=combined; FREQ count; CLASS faed; MODEL advance=stage white old faed / D=B TYPE3; RUN; /* The following program is found on page 156 of */ /* "Logistic Regression Using the SAS System." */ MODEL advance=stage white old faed stage*white stage*old stage*faed / D=B TYPE3; /* The following program is found on page 157 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=first; FREQ count; CLASS faed; MODEL advance= white old faed / D=B TYPE3; RUN; PROC GENMOD DATA=second; FREQ count; CLASS faed; MODEL advance= white old faed / D=B TYPE3; RUN; /* The following program is found on page 162 of */ /* "Logistic Regression Using the SAS System." */ DATA my.chocs; INPUT id choose dark soft nuts @@; DATALINES; 1 0 0 0 0 1 0 0 0 1 1 0 0 1 0 1 0 0 1 1 1 1 1 0 0 1 0 1 0 1 1 0 1 1 0 1 0 1 1 1 2 0 0 0 0 2 0 0 0 1 2 0 0 1 0 2 0 0 1 1 2 0 1 0 0 2 1 1 0 1 2 0 1 1 0 2 0 1 1 1 3 0 0 0 0 3 0 0 0 1 3 0 0 1 0 3 0 0 1 1 3 0 1 0 0 3 0 1 0 1 3 1 1 1 0 3 0 1 1 1 4 0 0 0 0 4 0 0 0 1 4 0 0 1 0 4 0 0 1 1 4 1 1 0 0 4 0 1 0 1 4 0 1 1 0 4 0 1 1 1 5 0 0 0 0 5 1 0 0 1 5 0 0 1 0 5 0 0 1 1 5 0 1 0 0 5 0 1 0 1 5 0 1 1 0 5 0 1 1 1 6 0 0 0 0 6 0 0 0 1 6 0 0 1 0 6 0 0 1 1 6 0 1 0 0 6 1 1 0 1 6 0 1 1 0 6 0 1 1 1 7 0 0 0 0 7 1 0 0 1 7 0 0 1 0 7 0 0 1 1 7 0 1 0 0 7 0 1 0 1 7 0 1 1 0 7 0 1 1 1 8 0 0 0 0 8 0 0 0 1 8 0 0 1 0 8 0 0 1 1 8 0 1 0 0 8 1 1 0 1 8 0 1 1 0 8 0 1 1 1 9 0 0 0 0 9 0 0 0 1 9 0 0 1 0 9 0 0 1 1 9 0 1 0 0 9 1 1 0 1 9 0 1 1 0 9 0 1 1 1 10 0 0 0 0 10 0 0 0 1 10 0 0 1 0 10 0 0 1 1 10 0 1 0 0 10 1 1 0 1 10 0 1 1 0 10 0 1 1 1 ; /* The following program is found on page 163 of */ /* "Logistic Regression Using the SAS System." */ DATA chocs; SET my.chocs; choose=2-choose; RUN; PROC PHREG DATA=chocs NOSUMMARY; MODEL choose=dark soft nuts / TIES=DISCRETE; STRATA id; RUN; /* The following program is found on page 169 of */ /* "Logistic Regression Using the SAS System." */ DATA travel; SET my.travel; choice = 2-choice; air = mode EQ 1; train = mode EQ 2; bus = mode EQ 3; airhinc = air*hinc; airpsize = air*psize; trahinc = train*hinc; trapsize = train*psize; bushinc = bus*hinc; buspsize = bus*psize; RUN; /* The following program is found on page 170 of */ /* "Logistic Regression Using the SAS System." */ PROC PHREG DATA=travel NOSUMMARY; MODEL choice = ttme time cost / TIES=DISCRETE; STRATA id; RUN; /* The following program is found on page 171 of */ /* "Logistic Regression Using the SAS System." */ MODEL choice = air bus train airhinc bushinc trahinc airpsize buspsize trapsize/ TIES=DISCRETE; /* The following program is found on page 172 of */ /* "Logistic Regression Using the SAS System." */ PROC CATMOD DATA=travel; WHERE choice=1; DIRECT hinc psize; MODEL mode=hinc psize / NOITER NOPROFILE; RUN; /* The following program is found on page 175 of */ /* "Logistic Regression Using the SAS System." */ PROC PHREG DATA=travel NOSUMMARY; MODEL choice*choice(2) = ttme time cost; STRATA id; RUN; /* The following program is found on page 176 of */ /* "Logistic Regression Using the SAS System." */ PROC PHREG DATA=my.judgernk NOSUMMARY; MODEL rank=blackd whitvic death / TIES=DISCRETE; STRATA judgid; RUN; /* The following program is found on page 182 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.ptsd; CLASS time; MODEL ptsd = control problems sevent cohes time / D=B; RUN; /* The following program is found on page 184 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.ptsd; CLASS subjid time; MODEL ptsd = control problems sevent cohes time / D=B; REPEATED SUBJECT=subjid / WITHIN=time TYPE=UN CORRW; RUN; /* The following program is found on page 190 of */ /* "Logistic Regression Using the SAS System." */ DATA ptsd; SET my.ptsd; ptsd=2-ptsd; t1 = time EQ 1; t2 = time EQ 2; RUN; PROC PHREG DATA=ptsd NOSUMMARY; MODEL ptsd = control problems sevent cohes t1 t2 / TIES=DISCRETE; STRATA subjid; RUN; /* The following program is found on page 194 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.postdoc; CLASS docid; MODEL pdoc = age mar doc ag und arts cits / D=B; REPEATED SUBJECT=docid / TYPE=EXCH; RUN; /* The following program is found on page 196 of */ /* "Logistic Regression Using the SAS System." */ DATA postdoc; SET my.postdoc; pdoc=2-pdoc; RUN; PROC PHREG DATA=postdoc NOSUMMARY; MODEL pdocd = age mar ag und arts cits / TIES=DISCRETE; STRATA docid; RUN; /* The following program is found on page 200 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.casecont; CLASS casenum; MODEL pubhouse=staybaby black kids doubleup age days / D=B; REPEATED SUBJECT=casenum / TYPE=UN CORRW; RUN; /* The following program is found on page 202 of */ /* "Logistic Regression Using the SAS System." */ DATA b; SET my.casecont; pubhouse=1-pubhouse; RUN; PROC PHREG DATA=b NOSUMMARY; MODEL pubhouse= staybaby black kids doubleup age / TIES=DISCRETE; STRATA casenum; RUN; /* The following program is found on page 205 of */ /* "Logistic Regression Using the SAS System." */ DATA c; SET my.casecont; staybaby=1-staybaby; RUN; PROC PHREG DATA=c NOSUMMARY; MODEL staybaby=black kids doubleup age; STRATA casenum; RUN; /* The following program is found on page 207 of */ /* "Logistic Regression Using the SAS System." */ DATA ptsd; SET my.ptsd; n=1; RUN; %GLIMMIX(DATA=ptsd, STMTS=%STR( CLASS subjid time; MODEL ptsd/n = control problems sevent cohes time / SOLUTION; RANDOM subjid; )) /* The following program is found on page 209 of */ /* "Logistic Regression Using the SAS System." */ DATA postdoc; SET my.postdoc; n=1; RUN; %GLIMMIX(DATA=postdoc,STMTS=%STR( CLASS docid; MODEL pdoc/n=age mar doc ag und arts cits / SOLUTION; RANDOM docid; )) /* The following program is found on page 211 of */ /* "Logistic Regression Using the SAS System." */ %GLIMMIX(DATA=postdoc,STMTS=%STR( CLASS docid; MODEL pdoc/n=age mar doc ag und arts cits/SOLUTION; RANDOM docid docid*ag; )) /* The following program is found on page 214 of */ /* "Logistic Regression Using the SAS System." */ PROC MEANS DATA=my.ptsd NWAY NOPRINT; CLASS subjid; VAR control problems sevent; OUTPUT OUT=means MEAN=mcontrol mproblem msevent; PROC SORT DATA=my.ptsd; BY subjid; PROC SORT DATA=a; BY subjid; DATA combine; MERGE my.ptsd means; BY subjid; dcontrol=control-mcontrol; dproblem=problems-mproblem; dsevent=sevent-msevent; RUN; /* The following program is found on page 215 of */ /* "Logistic Regression Using the SAS System." */ %GLIMMIX(DATA=combine, STMTS=%STR( CLASS subjid; MODEL ptsd/n = dcontrol dproblem dsevent mcontrol mproblem msevent cohes t2 t3 / SOLUTION; RANDOM subjid; )) /* The following program is found on page 216 of */ /* "Logistic Regression Using the SAS System." */ CONTRAST 'spec test' dcontrol 1 mcontrol -1, dproblem 1 mproblem -1, dsevent 1 msevent -1; /* The following program is found on page 220-221 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.postdoc; MODEL arts = age mar doc ag und / DIST=POISSON; PROC GENMOD DATA=my.postdoc; MODEL cits = age mar doc ag und / D=P; RUN; /* The following program is found on page 223 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=my.postdoc; MODEL arts = age mar doc ag und / D=P PSCALE; PROC GENMOD DATA=my.postdoc; MODEL cits = age mar doc ag und / D=P PSCALE; RUN; /* The following program is found on page 225 of */ /* "Logistic Regression Using the SAS System." */ DATA postdoc; SET my.postdoc; lcits=log(cits+.5); RUN; PROC GENMOD DATA=postdoc; MODEL lcits = age mar doc ag und; RUN; /* The following program is found on page 226 of */ /* "Logistic Regression Using the SAS System." */ %HILBENB(DSIN=my.postdoc,YVAR=arts,XVARS=age mar doc ag und) %HILBENB(DSIN=my.postdoc,YVAR=cits,XVARS=age mar doc ag und) /* The following program is found on page 229-230 of */ /* "Logistic Regression Using the SAS System." */ DATA prog2; SET my.prognosi; lmin=LOG(minutes); RUN; PROC GENMOD DATA=prog2; MODEL lengthpx=ptage ptsex ezcompt mdlikept surgeon claims / OFFSET=lmin D=P; RUN; /* The following program is found on page 236 of */ /* "Logistic Regression Using the SAS System." */ DATA penalty; INPUT n death black; DATALINES; 28 1 1 22 1 0 45 0 1 52 0 0 ; PROC GENMOD DATA=penalty; MODEL n = death black death*black / DIST=POISSON; RUN; /* The following program is found on page 238 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=penalty; WEIGHT n; MODEL death=black / D=BINOMIAL LINK=LOGIT; RUN; /* The following program is found on page 238 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=penalty; WEIGHT n; MODEL black=death / D=BINOMIAL LINK=LOGIT; RUN; /* The following program is found on page 240 of */ /* "Logistic Regression Using the SAS System." */ DATA wisctab; SET wisc; college=1; freq=coll; OUTPUT; college=0; freq=total-coll; OUTPUT; DROP total coll; PROC PRINT; RUN; /* The following program is found on page 242 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=wisctab; CLASS iq ses; MODEL freq=iq|ses|parent college iq*college ses*college parent*college / D=P TYPE3; RUN; /* The following program is found on page 247 of */ /* "Logistic Regression Using the SAS System." */ DATA happy; INPUT year married happy count; happyq=happy; DATALINES; 1 1 1 473 1 1 2 493 1 1 3 93 1 0 1 84 1 0 2 231 1 0 3 99 2 1 1 332 2 1 2 387 2 1 3 62 2 0 1 150 2 0 2 347 2 0 3 117 3 1 1 571 3 1 2 793 3 1 3 112 3 0 1 257 3 0 2 889 3 0 3 234 ; PROC GENMOD DATA=happy; CLASS year happy; MODEL count=year|married happy year*happyq married*happyq / D=P TYPE3; RUN; /* The following program is found on page 250 of */ /* "Logistic Regression Using the SAS System." */ MODEL count=year|married happy year*happyq married*happyq married*year*happyq / D=P TYPE3; /* The following program is found on page 250 of */ /* "Logistic Regression Using the SAS System." */ MODEL count=year|married happy year*happy married*happy / D=P TYPE3; /* The following program is found on page 251-252 of */ /* "Logistic Regression Using the SAS System." */ DATA happy2; SET happy; yearq=year; pretty=happy eq 2; RUN; PROC GENMOD DATA=happy2; CLASS year happy; MODEL count=year|married happy yearq*pretty married*happyq / D=P TYPE3; RUN; /* The following program is found on page 253-254 of */ /* "Logistic Regression Using the SAS System." */ DATA mobility; INPUT n dad son; DATALINES; 50 1 1 45 1 2 8 1 3 18 1 4 8 1 5 28 2 1 174 2 2 84 2 3 154 2 4 55 2 5 11 3 1 78 3 2 110 3 3 223 3 4 96 3 5 14 4 1 150 4 2 185 4 3 714 4 4 447 4 5 0 5 1 42 5 2 72 5 3 320 5 4 411 5 5 ; PROC GENMOD DATA=mobility; CLASS dad son; MODEL n = dad son /D=P; RUN; /* The following program is found on page 255 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=mobility; WHERE dad NE son; CLASS dad son; MODEL n = dad son /D=P; RUN; /* The following program is found on page 255 of */ /* "Logistic Regression Using the SAS System." */ DATA b; SET mobility; up=son GT dad; PROC GENMOD DATA=b; WHERE dad NE son; CLASS dad son; MODEL n = dad son son*up dad*up/D=P; RUN; /* The following program is found on page 256 of */ /* "Logistic Regression Using the SAS System." */ DATA c; SET mobility; band=ABS(dad-son); PROC GENMOD DATA=c; WHERE dad NE son; CLASS dad son band; MODEL n = dad son band /D=P; RUN; /* The following program is found on page 257 of */ /* "Logistic Regression Using the SAS System." */ DATA d; SET mobility; sonq=son; dadq=dad; PROC GENMOD DATA=d; WHERE dad NE son; CLASS dad son; MODEL n = dad son sonq*dadq /D=P OBSTATS; RUN; /* The following program is found on page 262 of */ /* "Logistic Regression Using the SAS System." */ DATA zero; INPUT x y z f; DATALINES; 1 1 1 20 1 0 1 5 1 1 0 5 1 0 0 5 0 1 1 4 0 0 1 11 0 1 0 0 0 0 0 0 ; PROC GENMOD DATA=zero; FREQ f; MODEL y = x z / D=B; RUN; /* The following program is found on page 263 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=zero; MODEL f=x z y x*z y*z y*x / D=P OBSTATS; RUN; /* The following program is found on page 265 of */ /* "Logistic Regression Using the SAS System." */ PROC GENMOD DATA=zero; WHERE f NE 0; MODEL f=x z y x*z y*z y*x / D=P; RUN;