Example 10 for PROC GENMOD
/****************************************************************/
/* S A S S A M P L E L I B R A R Y */
/* */
/* NAME: GENMEX10 */
/* TITLE: Example 10 for PROC GENMOD */
/* PRODUCT: STAT */
/* SYSTEM: ALL */
/* KEYS: generalized linear models, Bayesian analysis */
/* PROCS: GENMOD */
/* DATA: */
/* */
/* SUPPORT: sasgjj */
/* REF: PROC GENMOD, EXAMPLE 10 */
/* MISC: */
/****************************************************************/
data Liver;
input X1-X6 Y;
datalines;
19.1358 50.0110 51.000 0 0 1 3
23.5970 18.4959 3.429 0 0 1 9
20.0474 56.7699 3.429 1 1 0 6
28.0277 59.7836 4.000 0 0 1 6
28.6851 74.1589 5.714 1 0 1 1
18.8092 31.0630 2.286 0 1 1 61
28.7201 52.9178 37.286 1 0 1 6
21.3669 61.6603 54.143 0 1 1 6
23.7332 42.2904 0.571 1 0 1 21
20.4783 22.1260 19.000 1 0 1 6
22.8625 25.2164 1.714 0 1 1 6
22.0932 66.7562 2.571 0 0 1 1
24.3141 66.8000 26.714 1 1 0 2
21.4619 78.9863 9.714 0 0 1 6
23.8087 58.3260 2.000 0 1 1 6
19.3698 48.4904 2.000 1 1 1 6
23.4568 70.9890 1.429 0 0 1 6
24.4418 70.7425 5.714 1 0 1 6
22.9130 49.7041 13.143 1 0 1 6
22.5306 64.0438 4.143 1 1 1 6
32.7449 62.2082 0.143 1 1 0 3
20.0617 22.7671 0.143 1 1 1 6
15.9597 48.8137 1.571 1 0 1 6
31.4398 64.5918 63.143 0 0 1 2
22.9854 79.5205 2.714 1 0 1 1
19.2653 37.8685 4.857 1 1 1 1
19.5313 65.0630 0.857 0 0 1 6
24.1415 39.9452 4.429 1 0 1 6
17.1225 13.9342 0.429 1 0 1 6
21.4692 64.9699 4.714 1 1 1 6
25.3515 52.8027 0.857 0 0 1 6
30.1194 65.2438 6.000 1 0 0 6
29.1749 47.0301 4.286 1 1 0 6
21.7784 71.5123 2.571 1 0 1 6
17.3010 57.8575 16.714 1 1 1 6
17.0068 68.0356 69.143 1 0 1 6
20.0000 48.4027 23.714 1 0 1 6
19.2653 62.5014 2.000 1 1 0 6
25.3815 58.1671 2.143 1 1 1 6
25.9151 53.2027 113.000 1 1 1 6
22.2656 59.8904 0.857 0 0 1 6
22.4600 65.7288 5.286 1 0 0 1
18.0092 24.2274 2.286 1 0 1 6
19.4708 28.3644 0.571 1 0 1 6
20.7612 68.9342 2.714 1 0 0 2
32.0313 59.9781 5.429 0 0 1 6
19.8413 45.4740 1.143 0 0 1 6
24.4898 43.5315 4.286 1 0 1 6
21.2585 49.6274 4.714 0 0 0 6
20.0155 52.1397 5.429 1 1 1 6
19.5682 41.3233 6.571 1 1 1 1
23.6614 74.7616 6.429 1 1 1 3
20.5693 78.1671 1.857 1 1 1 6
18.7652 17.7534 104.000 1 0 1 6
21.7738 32.7616 3.571 1 0 1 6
30.8532 62.6932 3.571 1 0 1 2
23.1481 44.1178 4.571 1 0 1 2
29.7576 60.1342 0.429 1 0 1 6
21.5619 41.9096 2.429 0 0 1 6
24.3046 62.8603 3.429 0 0 1 2
20.7248 66.9918 1.429 0 0 1 6
36.3880 55.3178 1.429 1 0 0 2
21.9076 49.8466 64.143 0 1 1 3
18.3058 72.7233 0.571 1 1 1 2
26.5118 75.7562 2.143 1 0 0 2
23.4236 49.1178 4.429 1 0 1 6
24.7245 61.0521 5.000 1 0 0 1
32.2421 65.8795 0.000 0 0 0 6
23.3556 71.2712 2.857 1 0 1 3
22.7732 68.7014 3.857 0 0 0 1
19.4870 63.6192 4.143 1 0 0 1
24.5390 56.3890 5.143 0 1 1 6
26.8977 60.3507 3.000 1 1 0 6
25.2595 72.9863 5.429 0 0 1 1
22.1297 77.5808 1.286 1 0 1 6
9.6849 49.6274 0.286 0 0 1 6
17.0068 12.6466 7.143 1 0 1 1
18.4240 59.8055 0.857 1 0 1 6
19.1406 68.1781 6.857 1 1 1 4
18.5078 70.5890 2.143 0 0 1 1
19.5965 66.7315 1.143 1 0 1 1
24.4418 60.2137 4.714 1 0 0 0
30.1194 61.8740 0.143 1 1 1 6
25.3444 38.3507 4.000 0 0 1 6
21.4844 68.7726 3.143 1 0 0 1
20.1995 66.9041 5.571 1 0 1 4
25.2994 62.8685 12.714 1 0 0 6
23.6013 70.3808 4.286 1 0 1 6
27.1706 62.3397 2.429 1 0 1 6
20.9024 62.9425 7.857 0 0 0 6
20.4491 73.7890 8.000 0 0 1 1
22.1510 55.4822 1.286 0 0 1 6
22.5710 75.0274 7.571 1 0 0 6
27.9904 76.4082 1.429 1 0 0 3
29.0688 54.9479 4.143 1 0 0 1
20.9184 60.2521 2.571 0 1 0 1
18.1940 37.1808 8.143 1 0 0 2
21.4536 24.8822 1.714 0 1 0 9
14.0445 61.3288 6.571 1 0 0 6
16.7311 60.3288 2.143 1 0 0 6
24.6094 42.9918 2.571 1 0 0 6
25.0829 54.4329 16.286 1 0 0 9
21.5510 58.6658 6.857 0 0 0 6
24.2215 75.7836 3.429 0 1 0 2
30.4498 69.8795 4.429 1 0 0 2
20.6790 39.7315 2.143 1 0 1 0
59.2554 41.1342 5.571 1 0 0 3
22.7244 60.2575 41.571 1 0 0 6
20.7008 75.3671 3.429 0 0 1 3
24.6094 47.3644 8.714 0 0 0 1
21.8300 74.4027 5.286 0 0 0 6
20.8980 66.1178 34.429 0 0 0 6
31.9602 69.6247 4.000 1 0 0 6
29.4107 45.4521 4.571 1 0 0 6
22.9421 65.4027 1.143 1 0 1 21
24.8163 67.1096 3.429 1 0 0 6
19.8178 65.9014 1.286 1 1 0 6
18.7783 61.0904 2.571 1 0 0 1
26.0617 55.4384 3.571 1 0 0 1
21.6333 61.5288 3.571 0 0 0 6
32.5260 71.4904 5.714 1 0 0 9
25.4028 68.2329 48.714 1 0 0 6
20.5693 29.2575 3.571 1 0 0 6
19.2570 33.1233 0.714 1 0 0 6
20.8980 40.2822 4.857 1 0 0 1
17.0562 30.2247 2.143 1 1 0 6
25.9924 66.5151 2.857 1 0 1 6
31.0735 73.0493 8.714 1 0 0 2
20.9840 48.2027 4.857 1 0 0 2
21.4536 69.1808 2.571 0 0 0 1
26.2346 60.3425 2.571 1 0 1 1
24.1633 60.8329 11.000 1 0 1 1
26.8519 58.6877 3.429 1 0 1 2
17.0993 48.8384 3.000 0 0 0 9
19.1327 65.3425 2.571 1 0 0 1
17.3010 51.4493 4.429 1 0 0 6
;
proc genmod data=Liver;
model Y = X1-X6 / dist=Poisson link=log;
bayes seed=1 coeffprior=normal;
run;
data NormalPrior;
input _type_ $ Intercept X1-X6;
datalines;
Var 1e6 0.0005 1e6 1e6 1e6 1e6 1e6
Mean 0.0 0.1385 0.0 0.0 0.0 0.0 0.0
;
proc genmod data=Liver;
model Y = X1-X6 / dist=Poisson link=log;
bayes seed=1 plots=none coeffprior=normal(input=NormalPrior);
run;
