Categorical Data Analysis: Chapter 12
options nodate nonumber ps=200 ls=80;
data melanoma;
input type $ site $ count;
datalines;
Hutchinson's Head&Neck 22
Hutchinson's Trunk 2
Hutchinson's Extremities 10
Superficial Head&Neck 16
Superficial Trunk 54
Superficial Extremities 115
Nodular Head&Neck 19
Nodular Trunk 33
Nodular Extremities 73
Indeterminate Head&Neck 11
Indeterminate Trunk 17
Indeterminate Extremities 28
;
run;
proc genmod;
class type site;
model count=type|site / dist=poisson link=log type3;
run;
data melanoma;
input age $ region $ cases total;
ltotal=log(total);
datalines;
35-44 south 75 220407
45-54 south 68 198119
55-64 south 63 134084
65-74 south 45 70708
75+ south 27 34233
<35 south 64 1074246
35-44 north 76 564535
45-54 north 98 592983
55-64 north 104 450740
65-74 north 63 270908
75+ north 80 161850
<35 north 61 2880262
;
proc genmod data=melanoma order=data;
class age region;
model cases = age region
/ dist=poisson link=log offset=ltotal;
run;
data lri;
input id count risk passive crowding ses agegroup race @@;
logrisk =log(risk/52);
datalines;
1 0 42 1 0 2 2 0 96 1 41 1 0 1 2 0 191 0 44 1 0 0 2 0
2 0 43 1 0 0 2 0 97 1 26 1 1 2 2 0 192 0 45 0 0 0 2 1
3 0 41 1 0 1 2 0 98 0 36 0 0 0 2 0 193 0 42 0 0 0 2 0
4 1 36 0 1 0 2 0 99 0 34 0 0 0 2 0 194 1 31 0 0 0 2 1
5 1 31 0 0 0 2 0 100 1 3 1 1 2 3 1 195 0 35 0 0 0 2 0
6 0 43 1 0 0 2 0 101 0 45 1 0 0 2 0 196 1 35 1 0 0 2 0
7 0 45 0 0 0 2 0 102 0 38 0 0 1 2 0 197 1 27 1 0 1 2 0
8 0 42 0 0 0 2 1 103 0 41 1 1 1 2 1 198 1 33 0 0 0 2 0
9 0 45 0 0 0 2 1 104 1 37 0 1 0 2 0 199 0 39 1 0 1 2 0
10 0 35 1 1 0 2 0 105 0 40 0 0 0 2 0 200 3 40 0 1 2 2 0
11 0 43 0 0 0 2 0 106 1 35 1 0 0 2 0 201 4 26 1 0 1 2 0
12 2 38 0 0 0 2 0 107 0 28 0 1 2 2 0 202 0 14 1 1 1 1 1
13 0 41 0 0 0 2 0 108 3 33 0 1 2 2 0 203 0 39 0 1 1 2 0
14 0 12 1 1 0 1 0 109 0 38 0 0 0 2 0 204 0 4 1 1 1 3 0
15 0 6 0 0 0 3 0 110 0 42 1 1 2 2 1 205 1 27 1 1 1 2 1
16 0 43 0 0 0 2 0 111 0 40 1 1 2 2 0 206 0 36 1 0 0 2 1
17 2 39 1 0 1 2 0 112 0 38 0 0 0 2 0 207 0 30 1 0 2 2 1
18 0 43 0 1 0 2 0 113 2 37 0 1 1 2 0 208 0 34 0 1 0 2 0
19 2 37 0 0 0 2 1 114 1 42 0 1 0 2 0 209 1 40 1 1 1 2 0
20 0 31 1 1 1 2 0 115 5 37 1 1 1 2 1 210 0 6 1 0 1 1 1
21 0 45 0 1 0 2 0 116 0 38 0 0 0 2 0 211 1 40 1 1 1 2 0
22 1 29 1 1 1 2 1 117 0 4 0 0 0 3 0 212 2 43 0 1 0 2 0
23 1 35 1 1 1 2 0 118 2 37 1 1 1 2 0 213 0 36 1 1 1 2 0
24 3 20 1 1 2 2 0 119 0 39 1 0 1 2 0 214 0 35 1 1 1 2 1
25 1 23 1 1 1 2 0 120 0 42 1 1 0 2 0 215 1 35 1 1 2 2 0
26 1 37 1 0 0 2 0 121 0 40 1 0 0 2 0 216 0 43 1 0 1 2 0
27 0 49 0 0 0 2 0 122 0 36 1 0 0 2 0 217 0 33 1 1 2 2 0
28 0 35 0 0 0 2 0 123 1 42 0 1 1 2 0 218 0 36 0 1 1 2 1
29 3 44 1 1 1 2 0 124 1 39 0 0 0 2 0 219 1 41 0 0 0 2 0
30 0 37 1 0 0 2 0 125 2 29 0 0 0 2 0 220 0 41 1 1 0 2 1
31 2 39 0 1 1 2 0 126 3 37 1 1 2 2 1 221 1 42 0 0 0 2 1
32 0 41 0 0 0 2 0 127 0 40 1 0 0 2 0 222 0 33 0 1 2 2 1
33 1 46 1 1 2 2 0 128 0 40 0 0 0 2 0 223 0 40 1 1 2 2 0
34 0 5 1 1 2 3 1 129 0 39 0 0 0 2 0 224 0 40 1 1 1 2 1
35 1 29 0 0 0 2 0 130 0 40 1 0 1 2 0 225 0 40 0 0 2 2 0
36 0 31 0 1 0 2 0 131 1 32 0 0 0 2 0 226 0 28 1 0 1 2 0
37 0 22 1 1 2 2 0 132 0 46 1 0 1 2 0 227 0 47 0 0 0 2 1
38 1 22 1 1 2 2 1 133 4 39 1 1 0 2 0 228 0 18 1 1 2 2 1
39 0 47 0 0 0 2 0 134 0 37 0 0 0 2 0 229 0 45 1 0 0 2 0
40 1 46 1 1 1 2 1 135 0 51 0 0 1 2 0 230 0 35 0 0 0 2 0
41 0 37 0 0 0 2 0 136 1 39 1 1 0 2 0 231 1 17 1 0 1 1 1
42 1 39 0 0 0 2 0 137 1 34 1 1 0 2 0 232 0 40 0 0 0 2 0
43 0 33 0 1 1 2 1 138 1 14 0 1 0 1 0 233 0 29 1 1 2 2 0
44 0 34 1 0 1 2 0 139 2 15 1 0 0 2 0 234 1 35 1 1 1 2 0
45 3 32 1 1 1 2 0 140 1 34 1 1 0 2 1 235 0 40 0 0 2 2 0
46 3 22 0 0 0 2 0 141 0 43 0 1 0 2 0 236 1 22 1 1 1 2 0
47 1 6 1 0 2 3 0 142 1 33 0 0 0 2 0 237 0 42 0 0 0 2 0
48 0 38 0 0 0 2 0 143 3 34 1 0 0 2 1 238 0 34 1 1 1 2 1
49 1 43 0 1 0 2 0 144 0 48 0 0 0 2 0 239 6 38 1 0 1 2 0
50 2 36 0 1 0 2 0 145 4 26 1 1 0 2 0 240 0 25 0 0 1 2 1
51 0 43 0 0 0 2 0 146 0 30 0 1 2 2 1 241 0 39 0 1 0 2 0
52 0 24 1 0 0 2 0 147 0 41 1 1 1 2 0 242 1 35 0 1 2 2 1
53 0 25 1 0 1 2 1 148 0 34 0 1 1 2 0 243 1 36 1 1 1 2 1
54 0 41 0 0 0 2 0 149 0 43 0 1 0 2 0 244 0 23 1 0 0 2 0
55 0 43 0 0 0 2 0 150 1 31 1 0 1 2 0 245 4 30 1 1 1 2 0
56 2 31 0 1 1 2 0 151 0 26 1 0 1 2 0 246 1 41 1 1 1 2 1
57 3 28 1 1 1 2 0 152 0 37 0 0 0 2 0 247 0 37 0 1 1 2 0
58 1 22 0 0 1 2 1 153 0 44 0 0 0 2 0 248 0 46 1 1 0 2 0
59 1 11 1 1 1 1 0 154 0 40 1 0 0 2 0 249 0 45 1 1 0 2 1
60 3 41 0 1 1 2 0 155 0 8 1 1 1 3 1 250 1 38 1 1 1 2 0
61 0 31 0 0 1 2 0 156 0 40 1 1 1 2 1 251 0 10 1 1 1 1 0
62 0 11 0 0 1 1 1 157 1 45 0 0 0 2 0 252 0 30 1 1 2 2 0
63 0 44 0 1 0 2 0 158 0 4 0 0 2 3 0 253 0 32 0 1 2 2 0
64 0 9 1 0 0 3 1 159 1 36 0 1 0 2 0 254 0 46 1 0 0 2 0
65 0 36 1 1 1 2 0 160 3 37 1 1 1 2 0 255 5 35 1 1 2 2 1
66 0 29 1 0 0 2 0 161 0 15 1 0 0 1 0 256 0 44 0 0 0 2 0
67 0 27 0 1 0 2 1 162 1 27 1 0 1 2 1 257 0 41 0 1 1 2 0
68 0 36 0 1 0 2 0 163 2 31 0 1 0 2 0 258 2 36 1 0 1 2 0
69 1 33 1 0 0 2 0 164 0 42 0 0 0 2 0 259 0 34 1 1 1 2 1
70 2 13 1 1 2 1 1 165 0 42 1 0 0 2 0 260 1 30 0 1 0 2 1
71 0 38 0 0 0 2 0 166 1 38 0 0 0 2 0 261 1 27 1 0 0 2 0
72 0 41 0 0 0 2 1 167 0 44 1 0 0 2 0 262 0 48 1 0 0 2 0
73 0 41 1 0 2 2 0 168 0 45 0 0 0 2 0 263 1 6 0 1 2 3 1
74 0 35 0 0 1 2 0 169 0 34 0 1 0 2 0 264 0 38 1 1 0 2 1
75 0 45 0 0 0 2 0 170 2 41 0 0 0 2 0 265 0 29 1 1 1 2 1
76 4 38 1 0 2 2 1 171 2 30 1 1 1 2 0 266 1 43 0 1 2 2 1
77 1 42 1 0 0 2 1 172 0 44 0 0 0 2 0 267 0 43 0 1 0 2 0
78 1 42 1 1 2 2 1 173 0 40 1 0 0 2 0 268 0 37 1 0 2 2 0
79 6 36 1 1 0 2 0 174 2 31 0 0 0 2 0 269 1 23 1 1 0 2 1
80 2 23 1 1 1 2 1 175 0 41 1 0 0 2 0 270 0 44 0 0 1 2 0
81 1 32 0 0 1 2 0 176 0 41 0 0 0 2 0 271 0 5 0 1 1 3 1
82 0 41 0 1 0 2 0 177 0 39 1 0 0 2 0 272 0 25 1 0 2 2 0
83 0 50 0 0 0 2 0 178 0 40 1 0 0 2 0 273 0 25 1 0 1 2 0
84 0 42 1 1 1 2 1 179 2 35 1 0 2 2 0 274 1 28 1 1 1 2 1
85 1 30 0 0 0 2 0 180 1 43 1 0 0 2 0 275 0 7 0 1 0 3 1
86 2 47 0 1 0 2 0 181 2 39 0 0 0 2 0 276 0 32 0 0 0 2 0
87 1 35 1 1 2 2 0 182 0 35 1 1 0 2 0 277 0 41 0 0 0 2 0
88 1 38 1 0 1 2 1 183 0 37 0 0 0 2 0 278 1 33 1 1 2 2 1
89 1 38 1 1 1 2 1 184 3 37 0 0 0 2 0 279 2 36 1 1 2 2 0
90 1 38 1 1 1 2 1 185 0 43 0 0 0 2 0 280 0 31 0 0 0 2 0
91 0 32 1 1 1 2 0 186 0 42 0 0 0 2 0 281 0 18 0 0 0 2 0
92 1 3 1 0 1 3 1 187 0 42 0 0 0 2 0 282 1 32 1 0 2 2 0
93 0 26 1 0 0 2 1 188 0 38 0 0 0 2 0 283 0 22 1 1 2 2 1
94 0 35 1 0 0 2 0 189 0 36 1 0 0 2 0 284 0 35 0 0 0 2 1
95 3 37 1 0 0 2 0 190 0 39 0 1 0 2 0
;
proc genmod data=lri;
class ses id race agegroup;
model count = passive crowding ses race agegroup /
dist=poisson offset=logrisk type3;
run;
proc genmod data=lri;
class ses id race agegroup;
model count = passive crowding ses race agegroup /
dist=poisson offset=logrisk type3 scale=pearson;
run;
Statistics and Operations Research
