These packages should already be installed on your computer.
library(tidyverse)
library(VIM)
library(naniar)
library(finalfit)
library(MissMech)
library(norm)The colon_s dataset is contained in the finalfit package.
?colon_scolon_s## id rx sex age obstruct perfor adhere nodes status differ extent surg
## 1 1 Lev+5FU 1 43 NA 0 0 5 1 2 3 0
## 2 2 Lev+5FU 1 63 0 0 0 1 0 2 3 0
## 3 3 Obs 0 71 0 0 1 7 1 2 2 0
## 4 4 Lev+5FU 0 66 1 0 0 6 1 2 3 1
## 5 5 Obs 1 69 0 0 0 22 1 2 3 1
## 6 6 Lev+5FU 0 57 0 0 0 9 1 2 3 0
## 7 7 Lev 1 77 0 0 0 5 1 2 3 1
## 8 8 Obs 1 54 0 0 0 1 0 2 3 0
## 9 9 Lev 1 46 0 0 1 2 0 2 3 0
## 10 10 Lev+5FU 0 68 0 0 0 1 0 2 3 1
## 11 11 Lev 0 47 0 0 1 1 0 2 3 0
## 12 12 Lev+5FU 1 52 0 0 0 2 0 3 3 1
## 13 13 Obs 1 64 0 0 0 1 1 2 3 0
## 14 14 Lev 1 68 1 0 0 3 1 2 3 0
## 15 15 Obs 1 46 1 0 0 4 0 2 3 0
## 16 16 Obs 1 68 0 0 0 1 0 2 3 1
## 17 17 Lev 1 62 1 0 1 6 1 2 3 0
## 18 18 Lev 1 79 1 0 0 1 1 2 3 1
## 19 19 Lev+5FU 0 34 1 0 0 1 1 2 2 0
## 20 20 Lev 0 50 0 0 1 1 0 2 3 0
## 21 21 Obs 1 64 NA 0 0 1 1 2 3 1
## 22 22 Lev 1 56 1 0 0 4 1 2 3 1
## 23 23 Lev 0 61 0 0 0 4 1 2 3 0
## 24 24 Lev+5FU 0 50 0 0 0 1 0 2 2 0
## 25 25 Lev+5FU 0 70 0 0 0 4 0 2 3 0
## 26 26 Obs 1 73 0 0 0 1 1 2 3 0
## 27 27 Obs 0 70 0 0 1 13 1 2 3 0
## 28 28 Lev 0 68 0 0 0 1 1 2 3 0
## 29 29 Obs 0 56 1 0 0 6 1 3 3 0
## 30 30 Lev 1 80 0 0 0 1 1 3 3 0
## 31 31 Lev+5FU 0 64 0 0 0 1 0 2 1 0
## 32 32 Lev+5FU 0 33 1 0 0 3 0 2 3 0
## 33 33 Obs 0 49 0 0 0 2 1 2 3 1
## 34 34 Obs 1 47 0 0 0 3 1 2 3 1
## 35 35 Lev+5FU 0 56 0 0 0 1 1 2 3 1
## 36 36 Lev+5FU 0 72 0 0 1 1 0 3 3 1
## 37 37 Obs 1 79 0 0 0 19 1 2 3 0
## 38 38 Obs 0 64 0 0 0 1 0 3 3 0
## 39 39 Lev 1 61 0 0 0 2 0 3 3 0
## 40 40 Lev 1 58 0 0 0 7 1 2 3 0
## 41 41 Lev+5FU 1 75 0 0 0 2 1 2 3 1
## 42 42 Obs 0 39 1 0 0 1 0 1 3 1
## 43 43 Obs 1 71 1 0 0 3 1 2 2 1
## 44 44 Lev 0 58 1 0 0 2 0 2 3 0
## 45 45 Lev+5FU 1 40 0 0 0 1 0 1 3 1
## 46 46 Obs 0 63 0 1 0 2 0 2 3 0
## 47 47 Lev+5FU 0 59 0 0 0 1 0 3 1 0
## 48 48 Lev 0 59 1 0 0 2 0 1 3 1
## 49 49 Lev+5FU 1 59 0 0 0 6 0 2 3 0
## 50 50 Lev 1 60 0 0 0 5 1 3 3 0
## 51 51 Obs 0 68 0 0 0 2 1 2 3 1
## 52 52 Lev+5FU 0 70 0 0 0 3 1 2 3 0
## 53 53 Obs 1 76 0 0 0 2 0 2 3 0
## 54 54 Lev 0 45 0 0 0 3 0 2 3 0
## 55 55 Lev+5FU 1 61 0 0 0 2 0 2 2 1
## 56 56 Obs 1 76 0 0 0 3 1 1 3 0
## 57 57 Lev 1 53 0 0 0 2 0 2 3 0
## 58 58 Lev+5FU 0 63 0 0 0 5 0 2 3 1
## 59 59 Obs 0 65 0 0 0 6 0 3 3 1
## 60 60 Obs 0 57 1 0 0 4 0 3 3 0
## 61 61 Lev 1 80 0 1 0 4 1 2 3 1
## 62 62 Lev 1 58 0 0 0 1 0 1 2 1
## 63 63 Obs 0 53 0 0 0 15 1 3 3 0
## 64 64 Lev 0 53 1 0 0 1 0 NA 3 0
## 65 65 Obs 0 71 0 0 0 1 1 1 3 0
## 66 66 Lev+5FU 0 66 0 0 0 2 0 2 3 0
## 67 67 Lev+5FU 1 49 0 0 0 6 0 3 3 0
## 68 68 Obs 1 60 0 0 0 10 1 2 3 0
## 69 69 Obs 0 70 0 0 0 3 0 2 1 0
## 70 70 Obs 0 40 0 0 0 2 1 2 3 1
## 71 71 Lev+5FU 0 55 0 0 0 1 1 2 3 0
## 72 72 Lev+5FU 0 56 0 0 0 15 1 2 3 0
## 73 73 Lev+5FU 1 54 0 0 0 9 0 2 3 0
## 74 74 Obs 0 49 1 0 0 5 1 3 3 0
## 75 75 Lev 0 71 0 0 0 7 1 2 3 0
## 76 76 Obs 0 67 0 0 0 4 0 2 3 0
## 77 77 Lev 0 68 0 0 0 5 1 2 3 1
## 78 78 Lev+5FU 1 63 0 0 0 2 0 2 3 1
## 79 79 Lev 1 50 1 0 1 1 0 2 3 0
## 80 80 Lev+5FU 0 45 0 0 0 7 1 2 2 0
## 81 81 Lev 1 66 0 0 0 1 0 2 2 0
## 82 82 Obs 0 46 0 0 0 1 1 3 3 0
## 83 83 Lev 1 70 0 0 0 3 1 NA 2 0
## 84 84 Lev 1 63 1 0 0 2 0 2 2 0
## 85 85 Lev+5FU 1 45 0 0 0 8 1 3 3 0
## 86 86 Lev 0 49 0 0 0 1 0 2 3 0
## 87 87 Lev 0 62 0 0 0 2 0 2 2 0
## 88 88 Obs 1 59 0 0 0 4 1 2 3 0
## 89 89 Lev+5FU 0 80 NA 0 0 4 0 1 3 NA
## 90 90 Lev 1 73 1 0 0 4 1 NA 3 0
## 91 91 Obs 1 46 0 0 0 11 1 2 3 0
## 92 92 Lev 1 64 0 0 0 4 1 2 3 0
## 93 93 Lev 1 45 0 0 0 9 0 2 3 0
## 94 94 Lev+5FU 0 26 0 0 1 NA 0 2 4 1
## 95 95 Lev+5FU 1 66 NA 0 0 1 0 2 3 0
## 96 96 Lev 1 67 0 0 1 2 1 2 4 1
## 97 97 Obs 0 65 0 0 0 20 1 2 4 0
## 98 98 Lev+5FU 1 74 0 0 1 1 1 2 3 0
## 99 99 Lev 1 71 0 0 1 NA 1 2 4 0
## 100 100 Obs 0 58 0 0 1 8 1 2 2 0
## 101 101 Obs 1 59 0 0 0 6 1 2 3 0
## 102 102 Lev 1 61 NA 0 0 5 1 3 3 0
## 103 103 Lev+5FU 1 49 0 0 0 2 1 2 3 0
## 104 104 Lev+5FU 0 50 0 0 0 6 1 2 3 0
## 105 105 Obs 0 75 0 0 0 1 0 2 3 0
## 106 106 Obs 1 68 0 0 0 3 1 3 3 0
## 107 107 Lev 0 60 0 0 1 10 1 2 3 1
## 108 108 Lev+5FU 0 65 0 0 1 2 1 2 3 0
## 109 109 Lev 0 74 0 0 0 5 0 2 3 0
## 110 110 Lev+5FU 0 52 0 0 0 3 1 3 3 1
## 111 111 Lev+5FU 1 64 0 0 1 6 0 2 3 0
## 112 112 Lev 1 47 0 0 1 1 1 2 3 0
## 113 113 Obs 0 45 0 0 0 1 0 2 1 0
## 114 114 Obs 1 61 1 0 1 5 1 3 3 0
## 115 115 Lev 1 53 0 0 0 2 1 3 3 0
## 116 116 Obs 1 60 1 0 0 5 1 2 3 1
## 117 117 Lev+5FU 0 60 0 0 0 1 0 2 3 0
## 118 118 Lev 0 51 0 0 0 5 0 2 3 0
## 119 119 Lev+5FU 0 60 0 0 1 1 0 2 3 1
## 120 120 Obs 0 64 0 0 0 1 1 2 3 0
## 121 121 Lev+5FU 0 52 0 0 0 1 0 2 3 0
## 122 122 Lev 0 65 0 0 0 2 1 3 3 0
## 123 123 Lev+5FU 0 70 0 0 0 1 0 2 3 1
## 124 124 Obs 1 55 0 0 0 2 0 2 3 1
## 125 125 Lev+5FU 1 71 0 0 0 5 1 3 3 0
## 126 126 Obs 1 30 0 0 0 1 0 2 2 0
## 127 127 Obs 0 40 0 0 0 3 1 2 3 0
## 128 128 Obs 1 31 1 0 0 11 1 3 3 0
## 129 129 Obs 1 53 0 0 0 1 1 2 2 0
## 130 130 Obs 1 67 0 0 0 1 1 2 3 0
## 131 131 Lev+5FU 0 58 0 0 0 1 1 2 3 0
## 132 132 Lev+5FU 0 79 1 0 0 2 1 3 3 0
## 133 133 Lev 0 55 0 0 0 1 0 3 2 1
## 134 134 Obs 0 63 0 0 1 2 1 2 3 0
## 135 135 Lev+5FU 1 55 1 0 0 2 0 2 3 1
## 136 136 Lev 1 42 1 0 0 5 1 2 3 0
## 137 137 Obs 1 56 0 0 0 1 0 2 3 1
## 138 138 Lev 0 64 0 0 0 8 1 2 3 0
## 139 139 Lev 1 55 1 0 0 2 1 2 3 0
## 140 140 Obs 0 25 1 0 0 7 0 2 3 0
## 141 141 Lev+5FU 1 59 0 0 0 1 0 2 3 0
## 142 142 Lev 1 28 0 0 0 9 1 3 3 0
## 143 143 Lev+5FU 0 49 0 0 0 NA 0 1 3 0
## 144 144 Obs 0 52 0 0 0 1 0 2 1 0
## 145 145 Obs 0 64 0 0 0 5 1 3 3 1
## 146 146 Obs 0 33 1 0 1 1 0 1 3 0
## 147 147 Obs 1 76 0 0 0 1 1 2 3 1
## 148 148 Lev 1 38 0 0 0 2 1 1 3 0
## 149 149 Lev 0 53 1 1 0 1 1 2 3 0
## 150 150 Obs 0 72 1 0 0 2 0 2 3 1
## 151 151 Lev 1 46 0 0 0 1 0 2 3 0
## 152 152 Lev+5FU 0 69 0 0 0 13 1 2 3 0
## 153 153 Obs 1 43 1 0 0 0 1 3 3 1
## 154 154 Lev+5FU 1 72 1 0 1 2 1 2 3 0
## 155 155 Lev+5FU 1 73 1 0 0 2 1 2 3 1
## 156 156 Obs 1 68 0 0 0 3 0 2 3 0
## 157 157 Obs 0 52 0 1 0 6 1 1 3 0
## 158 158 Lev 0 73 1 0 0 2 0 2 3 0
## 159 159 Lev+5FU 1 66 1 0 0 1 0 2 3 0
## 160 160 Obs 0 75 0 0 0 2 0 3 3 0
## 161 161 Lev 1 43 1 0 0 6 1 NA 3 0
## 162 162 Lev+5FU 0 57 0 0 0 1 1 2 3 0
## 163 163 Obs 1 74 1 0 0 6 1 2 3 1
## 164 164 Lev 0 67 0 0 0 1 0 2 3 0
## 165 165 Lev+5FU 0 66 0 0 1 2 1 2 3 1
## 166 166 Obs 1 57 1 0 0 3 0 2 3 0
## 167 167 Lev+5FU 0 81 0 0 0 3 1 2 3 0
## 168 168 Obs 1 50 0 0 0 4 1 3 3 1
## 169 169 Lev 1 62 1 1 0 2 0 2 3 0
## 170 170 Lev+5FU 0 48 0 0 0 4 0 1 3 0
## 171 171 Lev+5FU 1 45 0 0 0 2 0 2 2 0
## 172 172 Lev 1 46 0 0 1 2 1 2 3 1
## 173 173 Lev+5FU 0 72 0 0 0 2 1 2 3 1
## 174 174 Obs 0 55 0 0 0 4 1 2 3 0
## 175 175 Lev 1 67 1 0 0 1 1 2 3 1
## 176 176 Lev+5FU 0 41 0 0 0 2 0 2 3 1
## 177 177 Lev+5FU 1 56 0 0 0 2 0 2 1 0
## 178 178 Lev+5FU 1 50 0 0 0 4 0 2 1 0
## 179 179 Lev+5FU 0 65 0 0 0 1 0 1 2 0
## 180 180 Lev+5FU 1 74 0 0 1 1 1 2 3 0
## 181 181 Obs 0 74 0 0 0 2 0 2 3 0
## 182 182 Obs 0 58 0 0 0 4 0 2 3 0
## 183 183 Lev 0 56 0 0 0 4 0 3 3 0
## 184 184 Obs 0 75 0 0 0 1 0 2 2 0
## 185 185 Lev+5FU 1 67 0 0 0 4 0 2 3 0
## 186 186 Lev 0 58 0 0 0 6 0 1 3 1
## 187 187 Lev+5FU 0 58 0 0 0 2 0 2 3 1
## 188 188 Lev 1 41 0 0 0 33 1 3 3 0
## 189 189 Lev 1 72 0 0 0 NA 0 2 3 0
## 190 190 Lev 1 48 0 0 1 2 1 NA 3 0
## 191 191 Lev+5FU 0 69 0 0 0 1 1 2 3 0
## 192 192 Obs 1 57 1 0 1 1 1 2 3 0
## 193 193 Lev+5FU 0 45 1 0 1 1 1 2 3 1
## 194 194 Lev+5FU 0 76 0 0 0 4 0 2 3 0
## 195 195 Obs 1 59 0 0 1 2 0 2 3 0
## 196 196 Obs 0 66 0 0 0 1 1 2 3 0
## 197 197 Obs 0 65 0 0 0 1 0 3 2 0
## 198 198 Lev 1 69 0 0 0 1 1 1 3 0
## 199 199 Lev+5FU 0 32 0 0 0 NA 1 3 3 1
## 200 200 Obs 0 56 0 0 0 1 0 NA 2 1
## 201 201 Lev 1 71 0 0 0 1 1 1 3 1
## 202 202 Lev 1 75 0 0 0 8 1 NA 3 1
## 203 203 Lev+5FU 1 58 0 0 0 7 0 3 3 0
## 204 204 Obs 0 40 0 0 0 4 1 2 3 0
## 205 205 Lev+5FU 0 39 0 0 0 2 0 1 1 0
## 206 206 Lev 0 42 0 0 0 4 0 2 3 0
## 207 207 Lev+5FU 0 53 0 0 0 4 0 1 1 0
## 208 208 Obs 1 43 0 0 0 2 0 2 3 1
## 209 209 Obs 0 51 0 0 0 4 1 2 3 1
## 210 210 Lev 1 77 0 0 0 2 0 1 3 0
## 211 211 Lev 1 67 1 0 0 1 0 2 3 0
## 212 212 Obs 1 41 0 0 0 7 1 2 3 0
## 213 213 Lev+5FU 1 63 1 1 1 2 0 3 4 1
## 214 214 Lev 1 63 0 0 1 3 0 2 2 0
## 215 215 Lev+5FU 0 63 0 0 0 6 0 2 3 0
## 216 216 Lev+5FU 0 58 1 0 0 8 0 2 3 0
## 217 217 Lev+5FU 0 67 0 0 0 4 0 2 4 NA
## 218 218 Lev+5FU 1 55 1 0 0 7 1 2 3 0
## 219 219 Lev 1 63 1 0 0 5 1 3 3 0
## 220 220 Lev 1 77 0 0 1 1 1 2 3 0
## 221 221 Lev 1 43 1 1 1 4 0 3 3 1
## 222 222 Lev+5FU 0 78 0 0 0 2 0 2 2 0
## 223 223 Obs 0 51 0 0 1 5 1 2 3 1
## 224 224 Obs 1 67 1 0 0 1 1 2 3 0
## 225 225 Lev 1 66 0 0 0 1 0 2 3 0
## 226 226 Obs 0 64 0 0 1 1 1 2 4 1
## 227 227 Obs 0 75 1 0 1 1 0 2 3 0
## 228 228 Lev 1 53 0 0 0 1 1 2 3 0
## 229 229 Lev 1 48 1 1 0 2 0 2 3 0
## 230 230 Obs 0 59 0 0 1 1 1 2 4 0
## 231 231 Obs 0 60 0 0 0 1 0 2 3 1
## 232 232 Obs 1 42 0 0 0 2 0 2 3 0
## 233 233 Lev 1 60 0 0 0 1 0 2 2 1
## 234 234 Lev+5FU 1 58 NA 0 0 1 0 1 3 0
## 235 235 Lev+5FU 1 59 NA 0 0 2 1 2 2 0
## 236 236 Obs 0 70 0 0 0 2 1 2 3 0
## 237 237 Lev+5FU 0 75 0 0 0 3 0 2 3 0
## 238 238 Lev+5FU 0 73 0 0 0 3 0 2 3 0
## 239 239 Obs 1 76 0 0 0 1 0 2 3 0
## 240 240 Lev+5FU 0 68 0 0 0 3 1 2 3 0
## 241 241 Lev 1 61 0 0 0 2 0 2 4 NA
## 242 242 Lev+5FU 1 76 NA 0 0 1 0 2 2 0
## 243 243 Lev+5FU 0 56 0 1 1 3 0 2 3 1
## 244 244 Lev 0 55 1 0 0 2 0 NA 3 0
## 245 245 Obs 0 60 1 0 1 4 1 3 3 0
## 246 246 Lev 1 72 0 0 0 9 1 2 3 1
## 247 247 Lev+5FU 0 74 1 0 0 11 1 2 3 0
## 248 248 Lev+5FU 0 62 0 0 0 3 1 2 3 1
## 249 249 Lev 0 76 0 0 0 1 1 1 3 0
## 250 250 Lev+5FU 1 72 0 0 0 2 0 2 3 1
## 251 251 Lev 1 57 0 0 0 2 1 3 3 0
## 252 252 Obs 0 39 0 0 0 1 0 2 4 0
## 253 253 Lev+5FU 1 61 0 0 0 1 0 2 3 0
## 254 254 Obs 0 62 0 0 0 5 1 3 3 0
## 255 255 Lev 1 70 0 0 0 2 1 2 3 1
## 256 256 Obs 0 70 0 0 0 5 1 2 3 0
## 257 257 Lev 0 57 1 0 0 8 1 2 3 0
## 258 258 Lev 1 65 0 0 0 3 0 2 2 0
## 259 259 Lev 0 65 0 0 0 1 0 2 3 0
## 260 260 Obs 0 71 0 0 0 15 1 2 3 0
## 261 261 Lev 0 70 1 0 0 3 1 2 3 0
## 262 262 Obs 0 36 0 0 0 1 0 2 3 1
## 263 263 Lev 1 48 0 0 0 2 0 2 1 0
## 264 264 Lev 1 53 0 0 0 1 0 1 3 0
## 265 265 Lev+5FU 1 54 0 0 0 3 1 2 3 1
## 266 266 Lev 1 58 0 0 0 3 1 1 3 0
## 267 267 Obs 1 67 0 0 0 3 0 2 3 0
## 268 268 Lev 1 59 1 0 0 2 0 2 3 1
## 269 269 Obs 0 67 0 0 1 4 1 2 3 0
## 270 270 Lev+5FU 0 60 1 0 0 1 0 3 3 1
## 271 271 Lev 0 70 0 0 0 1 0 2 2 0
## 272 272 Obs 1 76 0 0 0 3 1 1 3 0
## 273 273 Lev+5FU 1 60 1 0 0 1 1 1 3 0
## 274 274 Obs 0 67 1 0 0 12 1 1 3 0
## 275 275 Lev 1 53 0 0 0 3 1 2 3 0
## 276 276 Lev+5FU 0 76 0 0 0 1 0 1 3 0
## 277 277 Obs 1 74 0 0 0 2 1 2 3 1
## 278 278 Obs 0 56 1 0 0 6 1 2 4 0
## 279 279 Lev 0 65 0 0 0 1 0 2 2 0
## 280 280 Lev+5FU 1 63 0 0 0 2 1 2 3 1
## 281 281 Obs 1 56 0 0 0 2 1 2 3 0
## 282 282 Lev 0 70 0 0 1 4 0 3 3 0
## 283 283 Lev+5FU 0 48 0 0 0 9 0 2 3 0
## 284 284 Lev 1 45 1 0 0 2 0 2 3 0
## 285 285 Lev 0 68 0 0 0 8 1 2 3 0
## 286 286 Lev 0 57 0 0 0 1 0 2 2 0
## 287 287 Lev+5FU 1 70 0 0 0 1 1 2 2 1
## 288 288 Lev+5FU 1 39 0 0 0 1 0 2 3 0
## 289 289 Obs 1 46 0 0 1 1 1 3 4 0
## 290 290 Obs 0 77 1 0 0 4 0 2 3 0
## 291 291 Lev+5FU 1 59 NA 0 0 1 0 1 3 0
## 292 292 Lev 0 58 0 0 0 1 0 2 3 1
## 293 293 Obs 1 56 0 0 0 8 0 2 3 1
## 294 294 Lev+5FU 1 68 0 0 0 2 0 NA 3 0
## 295 295 Obs 0 57 0 1 1 1 0 2 3 0
## 296 296 Lev+5FU 0 44 0 0 0 3 1 2 3 0
## 297 297 Lev+5FU 1 56 0 0 1 3 1 2 3 0
## 298 298 Obs 1 67 0 0 0 4 1 2 3 0
## 299 299 Lev+5FU 1 62 0 0 0 6 0 2 2 0
## 300 300 Lev 0 68 0 0 0 7 1 2 3 0
## 301 301 Lev 1 61 0 0 0 2 0 2 2 1
## 302 302 Lev 0 44 1 0 0 5 1 2 3 1
## 303 303 Lev 0 52 0 0 0 7 0 2 3 1
## 304 304 Lev 1 51 1 0 0 1 1 3 3 0
## 305 305 Obs 0 59 0 0 0 9 0 2 3 0
## 306 306 Lev+5FU 1 61 0 0 0 1 0 3 3 0
## 307 307 Obs 0 57 0 0 0 2 0 3 3 1
## 308 308 Lev+5FU 1 65 0 0 0 1 0 2 3 1
## 309 309 Lev 0 73 1 0 0 1 0 2 3 0
## 310 310 Obs 0 69 0 0 0 6 1 3 3 0
## 311 311 Lev+5FU 1 63 0 0 0 1 0 2 3 1
## 312 312 Lev 1 75 0 0 0 2 0 2 2 0
## 313 313 Lev 0 64 0 0 0 5 0 1 3 0
## 314 314 Obs 0 56 0 0 0 1 0 1 1 0
## 315 315 Lev 1 69 0 0 0 2 0 2 3 0
## 316 316 Lev 0 64 0 0 0 2 0 2 3 0
## 317 317 Lev 0 74 1 0 0 2 1 2 3 0
## 318 318 Lev 1 72 0 0 0 4 0 2 2 1
## 319 319 Lev 1 58 1 0 0 9 0 2 3 1
## 320 320 Lev+5FU 0 74 0 0 1 15 0 3 4 0
## 321 321 Obs 0 61 0 0 0 2 0 1 2 0
## 322 322 Obs 0 74 NA 0 0 1 1 2 2 0
## 323 323 Lev+5FU 1 64 0 0 0 5 0 2 3 0
## 324 324 Lev+5FU 0 71 0 0 0 20 1 2 3 0
## 325 325 Obs 0 66 0 0 1 1 1 NA 4 0
## 326 326 Obs 0 53 1 0 0 2 0 1 3 1
## 327 327 Lev 0 76 1 0 0 1 0 2 3 1
## 328 328 Lev 0 75 1 0 1 3 1 2 2 1
## 329 329 Lev+5FU 1 64 0 0 0 3 0 NA 3 0
## 330 330 Lev 1 65 0 0 0 8 1 2 3 1
## 331 331 Obs 0 57 0 0 0 5 1 2 3 NA
## 332 332 Lev 1 65 0 0 1 1 0 3 3 0
## 333 333 Obs 1 53 0 0 0 2 0 2 4 0
## 334 334 Lev 1 74 0 0 0 4 1 2 3 0
## 335 335 Lev+5FU 1 74 0 0 0 1 0 2 3 0
## 336 336 Lev+5FU 0 74 0 0 1 1 1 3 3 0
## 337 337 Lev+5FU 0 48 0 0 0 6 1 2 3 0
## 338 338 Lev 1 58 0 0 0 NA 1 3 3 0
## 339 339 Lev+5FU 0 74 0 0 0 3 1 2 3 0
## 340 340 Lev+5FU 0 71 0 0 0 1 0 2 3 1
## 341 341 Obs 0 54 0 0 0 2 1 2 3 1
## 342 342 Lev+5FU 1 80 0 0 0 4 0 2 2 1
## 343 343 Lev 1 70 0 0 1 8 1 2 3 1
## 344 344 Lev+5FU 1 70 1 0 0 1 0 2 3 0
## 345 345 Obs 1 70 NA 0 0 1 1 3 3 1
## 346 346 Obs 1 71 0 0 0 4 0 2 3 0
## 347 347 Obs 1 59 0 0 0 2 1 2 3 0
## 348 348 Lev 1 47 0 0 0 2 1 NA 3 1
## 349 349 Lev 1 63 0 0 0 2 0 3 3 0
## 350 350 Lev 0 69 0 0 0 7 1 2 3 0
## 351 351 Lev+5FU 0 73 0 0 0 1 0 2 3 0
## 352 352 Obs 1 67 0 0 0 1 0 2 3 0
## 353 353 Lev+5FU 0 55 0 0 0 1 0 2 3 0
## 354 354 Obs 1 45 0 0 0 2 0 2 3 1
## 355 355 Lev+5FU 0 78 1 0 0 3 0 2 3 1
## 356 356 Lev 1 80 0 0 0 3 1 2 3 0
## 357 357 Obs 1 55 0 0 0 8 1 2 3 0
## 358 358 Lev+5FU 0 64 1 0 0 NA 0 2 3 0
## 359 359 Lev 0 60 0 1 0 10 1 2 3 1
## 360 360 Lev+5FU 0 74 0 0 0 5 1 2 3 1
## 361 361 Lev 0 61 0 0 0 1 1 2 3 0
## 362 362 Obs 1 64 0 0 0 4 0 2 2 0
## 363 363 Obs 0 48 0 0 1 1 1 3 3 1
## 364 364 Lev 1 76 0 0 0 2 1 2 3 0
## 365 365 Lev+5FU 0 76 0 0 0 NA 1 3 3 0
## 366 366 Lev 0 50 0 0 0 4 0 2 3 1
## 367 367 Lev 1 56 0 0 0 3 1 2 4 0
## 368 368 Lev+5FU 0 42 0 0 0 10 1 3 3 1
## 369 369 Lev 0 72 0 0 0 1 1 2 3 0
## 370 370 Obs 0 68 0 0 1 9 1 2 3 1
## 371 371 Lev 1 49 0 0 0 1 0 2 2 1
## 372 372 Lev 1 64 0 0 0 12 0 2 3 1
## 373 373 Obs 0 70 NA 0 0 1 0 1 2 0
## 374 374 Lev+5FU 1 50 0 0 1 2 1 2 4 0
## 375 375 Obs 1 74 0 0 1 3 0 3 3 1
## 376 376 Lev 0 37 0 0 0 1 0 2 3 0
## 377 377 Lev+5FU 0 75 NA 0 0 1 0 3 3 0
## 378 378 Obs 0 56 0 0 0 2 1 3 3 0
## 379 379 Lev+5FU 1 74 0 0 0 3 0 1 3 1
## 380 380 Obs 1 63 0 0 0 2 1 2 3 0
## 381 381 Lev 1 56 0 0 0 2 0 2 2 0
## 382 382 Lev+5FU 1 42 0 0 0 13 0 2 3 0
## 383 383 Lev 1 63 0 0 0 NA 1 2 3 0
## 384 384 Lev 0 62 0 0 0 2 1 2 3 1
## 385 385 Lev+5FU 0 33 0 0 0 2 0 2 3 0
## 386 386 Obs 0 50 0 0 0 8 1 2 3 0
## 387 387 Lev 1 73 0 0 0 6 1 3 3 0
## 388 388 Lev+5FU 0 61 0 0 0 9 1 3 3 1
## 389 389 Obs 1 70 1 1 0 1 1 2 3 1
## 390 390 Lev 0 38 0 0 0 3 1 2 3 0
## 391 391 Obs 0 64 1 0 0 3 1 2 3 0
## 392 392 Lev 0 39 0 0 0 2 0 2 3 0
## 393 393 Lev+5FU 0 47 0 0 0 1 0 2 3 0
## 394 394 Obs 1 76 0 0 1 13 1 3 3 0
## 395 395 Obs 1 65 0 0 0 2 0 2 3 0
## 396 396 Lev 0 43 1 0 0 4 1 2 3 0
## 397 397 Lev 1 72 0 0 0 1 0 2 3 1
## 398 398 Obs 1 33 0 0 0 2 0 2 3 1
## 399 399 Lev+5FU 1 66 0 0 0 7 0 2 3 0
## 400 400 Lev+5FU 0 74 0 0 0 2 0 2 3 0
## 401 401 Lev+5FU 1 54 0 0 0 1 0 2 3 0
## 402 402 Obs 1 44 0 0 0 14 1 2 3 0
## 403 403 Obs 1 75 1 0 0 27 1 2 2 NA
## 404 404 Lev 1 58 0 0 0 6 0 2 3 0
## 405 405 Lev 1 48 0 0 0 6 0 1 2 1
## 406 406 Lev+5FU 0 64 0 0 0 1 1 2 3 0
## 407 407 Lev 1 49 NA 0 0 1 0 1 3 0
## 408 408 Obs 0 55 0 0 0 1 0 2 3 0
## 409 409 Lev+5FU 1 60 0 0 0 3 0 2 3 0
## 410 410 Obs 1 67 0 0 0 2 0 2 3 0
## 411 411 Lev+5FU 1 79 0 0 0 1 1 2 2 0
## 412 412 Lev 1 57 0 0 0 1 0 2 3 0
## 413 413 Obs 0 22 0 0 0 3 0 2 3 1
## 414 414 Obs 1 59 1 0 0 4 1 1 3 0
## 415 415 Lev+5FU 0 66 1 0 0 1 0 1 3 0
## 416 416 Lev 1 54 0 0 1 2 1 2 4 0
## 417 417 Obs 1 58 0 0 0 1 0 2 2 0
## 418 418 Obs 0 36 1 0 0 7 0 2 3 0
## 419 419 Obs 1 52 0 0 0 4 1 2 3 0
## 420 420 Obs 0 61 0 0 0 1 1 2 3 0
## 421 421 Lev 0 76 0 0 0 2 1 1 3 0
## 422 422 Lev 0 58 0 0 1 6 1 1 3 0
## 423 423 Lev 1 52 0 0 0 5 0 1 3 0
## 424 424 Obs 1 72 0 0 0 1 1 2 3 1
## 425 425 Lev 1 74 0 0 0 1 0 1 3 0
## 426 426 Obs 1 62 0 0 0 6 1 2 2 1
## 427 427 Obs 0 46 0 0 1 1 1 2 3 0
## 428 428 Obs 1 66 0 0 0 1 0 2 3 0
## 429 429 Lev+5FU 1 52 0 0 0 5 1 2 3 0
## 430 430 Lev+5FU 0 38 0 0 0 24 1 NA 3 0
## 431 431 Obs 1 61 0 0 0 1 1 2 3 1
## 432 432 Obs 0 60 0 0 0 1 0 1 3 0
## 433 433 Lev 0 68 0 0 1 2 1 1 3 0
## 434 434 Lev 0 53 0 0 0 6 1 2 3 1
## 435 435 Lev+5FU 1 58 0 0 0 1 0 2 3 1
## 436 436 Obs 1 64 0 0 0 4 1 2 3 0
## 437 437 Obs 1 68 1 0 1 3 0 2 3 0
## 438 438 Obs 1 62 0 0 1 6 1 2 4 0
## 439 439 Obs 1 70 0 0 0 1 1 1 3 0
## 440 440 Lev+5FU 1 57 0 0 0 1 0 2 3 0
## 441 441 Lev+5FU 0 66 0 0 1 1 1 2 4 0
## 442 442 Lev 0 59 NA 0 0 11 1 2 3 0
## 443 443 Lev 1 75 0 0 0 3 0 1 3 0
## 444 444 Lev+5FU 1 77 0 0 0 2 0 2 3 NA
## 445 445 Lev 1 57 0 0 0 6 1 2 3 0
## 446 446 Obs 1 72 0 0 0 2 1 1 2 1
## 447 447 Lev+5FU 0 64 1 0 0 3 1 2 3 0
## 448 448 Lev+5FU 1 33 0 0 0 2 0 3 3 0
## 449 449 Lev+5FU 0 62 0 0 0 2 0 2 3 1
## 450 450 Lev+5FU 1 70 0 0 0 1 1 2 3 0
## 451 451 Lev 0 55 1 0 0 4 0 1 3 0
## 452 452 Obs 1 32 1 0 1 11 0 2 3 0
## 453 453 Obs 0 64 1 0 0 2 0 2 2 0
## 454 454 Obs 0 48 0 0 0 1 0 2 4 0
## 455 455 Lev 1 68 0 0 1 3 1 2 3 1
## 456 456 Lev+5FU 0 59 0 0 0 1 1 2 3 1
## 457 457 Obs 1 68 0 0 1 9 1 3 3 0
## 458 458 Lev 0 50 0 0 1 1 0 1 3 1
## 459 459 Obs 0 41 1 0 0 4 1 2 3 0
## 460 460 Lev 0 69 0 0 1 1 0 2 3 0
## 461 461 Lev+5FU 1 46 0 0 0 2 0 1 2 0
## 462 462 Obs 1 43 0 0 0 1 0 2 3 0
## 463 463 Lev+5FU 1 68 0 0 0 3 1 3 3 1
## 464 464 Lev 1 73 0 0 0 3 1 2 3 0
## 465 465 Lev+5FU 0 66 0 0 1 4 1 3 4 0
## 466 466 Obs 0 60 0 0 1 1 0 2 3 0
## 467 467 Lev+5FU 1 74 0 0 0 2 0 2 3 1
## 468 468 Lev 1 68 0 0 0 1 1 1 3 0
## 469 469 Lev+5FU 0 60 1 0 0 1 0 2 3 0
## 470 470 Obs 1 71 0 0 1 1 0 2 4 0
## 471 471 Obs 1 76 0 0 0 2 0 2 1 0
## 472 472 Obs 1 57 0 0 0 8 1 3 2 0
## 473 473 Lev 0 33 0 0 0 7 1 3 3 0
## 474 474 Lev 1 54 0 0 0 4 1 2 3 0
## 475 475 Obs 1 68 0 0 0 13 1 2 3 1
## 476 476 Obs 0 70 0 0 0 6 1 3 2 1
## 477 477 Obs 1 66 0 0 0 5 1 2 3 0
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## 908 908 Obs 0 55 0 0 0 2 0 2 3 0
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## 922 922 Lev+5FU 0 70 0 0 0 1 1 2 3 0
## 923 923 Lev+5FU 1 55 1 0 0 2 0 3 3 0
## 924 924 Obs 1 64 1 0 1 2 0 3 3 0
## 925 925 Lev+5FU 1 71 0 0 1 4 0 2 3 0
## 926 926 Lev 0 72 0 0 0 1 0 2 3 0
## 927 927 Lev 1 76 0 0 1 1 1 3 3 0
## 928 928 Lev+5FU 0 48 1 0 0 4 0 2 3 1
## 929 929 Lev 0 66 1 0 0 1 0 2 3 0
## node4 time sex.factor rx.factor obstruct.factor perfor.factor adhere.factor
## 1 1 1521 Male Lev+5FU <NA> No No
## 2 0 3087 Male Lev+5FU No No No
## 3 1 963 Female Obs No No Yes
## 4 1 293 Female Lev+5FU Yes No No
## 5 1 659 Male Obs No No No
## 6 1 1767 Female Lev+5FU No No No
## 7 1 420 Male Lev No No No
## 8 0 3192 Male Obs No No No
## 9 0 3173 Male Lev No No Yes
## 10 0 3308 Female Lev+5FU No No No
## 11 0 2908 Female Lev No No Yes
## 12 0 3309 Male Lev+5FU No No No
## 13 0 2085 Male Obs No No No
## 14 0 2910 Male Lev Yes No No
## 15 0 2754 Male Obs Yes No No
## 16 0 3214 Male Obs No No No
## 17 1 406 Male Lev Yes No Yes
## 18 0 522 Male Lev Yes No No
## 19 0 887 Female Lev+5FU Yes No No
## 20 0 3329 Female Lev No No Yes
## 21 0 2789 Male Obs <NA> No No
## 22 0 739 Male Lev Yes No No
## 23 0 709 Female Lev No No No
## 24 0 2969 Female Lev+5FU No No No
## 25 0 2889 Female Lev+5FU No No No
## 26 0 1772 Male Obs No No No
## 27 1 384 Female Obs No No Yes
## 28 0 968 Female Lev No No No
## 29 1 218 Female Obs Yes No No
## 30 0 133 Male Lev No No No
## 31 0 3238 Female Lev+5FU No No No
## 32 0 3019 Female Lev+5FU Yes No No
## 33 0 1745 Female Obs No No No
## 34 0 2527 Male Obs No No No
## 35 0 1387 Female Lev+5FU No No No
## 36 0 3024 Female Lev+5FU No No Yes
## 37 1 570 Male Obs No No No
## 38 0 2815 Female Obs No No No
## 39 0 2901 Male Lev No No No
## 40 1 553 Male Lev No No No
## 41 0 905 Male Lev+5FU No No No
## 42 0 3030 Female Obs Yes No No
## 43 0 685 Male Obs Yes No No
## 44 0 2740 Female Lev Yes No No
## 45 0 2899 Male Lev+5FU No No No
## 46 0 2598 Female Obs No Yes No
## 47 0 2840 Female Lev+5FU No No No
## 48 0 2802 Female Lev Yes No No
## 49 1 2781 Male Lev+5FU No No No
## 50 1 833 Male Lev No No No
## 51 0 1290 Female Obs No No No
## 52 0 1620 Female Lev+5FU No No No
## 53 0 2765 Male Obs No No No
## 54 0 2708 Female Lev No No No
## 55 0 2737 Male Lev+5FU No No No
## 56 0 1178 Male Obs No No No
## 57 0 2765 Male Lev No No No
## 58 1 2883 Female Lev+5FU No No No
## 59 1 2679 Female Obs No No No
## 60 0 2925 Female Obs Yes No No
## 61 0 472 Male Lev No Yes No
## 62 0 2772 Male Lev No No No
## 63 1 474 Female Obs No No No
## 64 0 2739 Female Lev Yes No No
## 65 0 365 Female Obs No No No
## 66 0 2653 Female Lev+5FU No No No
## 67 1 2726 Male Lev+5FU No No No
## 68 1 774 Male Obs No No No
## 69 0 3078 Female Obs No No No
## 70 0 2133 Female Obs No No No
## 71 0 2127 Female Lev+5FU No No No
## 72 1 400 Female Lev+5FU No No No
## 73 1 3185 Male Lev+5FU No No No
## 74 1 1237 Female Obs Yes No No
## 75 1 1219 Female Lev No No No
## 76 0 3017 Female Obs No No No
## 77 1 806 Female Lev No No No
## 78 0 2985 Male Lev+5FU No No No
## 79 0 2969 Male Lev Yes No Yes
## 80 1 1995 Female Lev+5FU No No No
## 81 0 2958 Male Lev No No No
## 82 0 1133 Female Obs No No No
## 83 0 1548 Male Lev No No No
## 84 0 3085 Male Lev Yes No No
## 85 1 736 Male Lev+5FU No No No
## 86 0 2789 Female Lev No No No
## 87 0 3325 Female Lev No No No
## 88 0 381 Male Obs No No No
## 89 0 2724 Female Lev+5FU <NA> No No
## 90 0 997 Male Lev Yes No No
## 91 1 413 Male Obs No No No
## 92 0 708 Male Lev No No No
## 93 1 2765 Male Lev No No No
## 94 1 2869 Female Lev+5FU No No Yes
## 95 0 2918 Male Lev+5FU <NA> No No
## 96 0 2458 Male Lev No No Yes
## 97 1 459 Female Obs No No No
## 98 0 2318 Male Lev+5FU No No Yes
## 99 1 569 Male Lev No No Yes
## 100 1 2077 Female Obs No No Yes
## 101 1 1216 Male Obs No No No
## 102 1 171 Male Lev <NA> No No
## 103 0 712 Male Lev+5FU No No No
## 104 1 614 Female Lev+5FU No No No
## 105 0 2849 Female Obs No No No
## 106 0 1530 Male Obs No No No
## 107 1 402 Female Lev No No Yes
## 108 0 1511 Female Lev+5FU No No Yes
## 109 1 2828 Female Lev No No No
## 110 0 23 Female Lev+5FU No No No
## 111 1 2941 Male Lev+5FU No No Yes
## 112 0 755 Male Lev No No Yes
## 113 0 2815 Female Obs No No No
## 114 1 761 Male Obs Yes No Yes
## 115 0 1839 Male Lev No No No
## 116 1 2351 Male Obs Yes No No
## 117 0 2760 Female Lev+5FU No No No
## 118 1 2951 Female Lev No No No
## 119 0 2820 Female Lev+5FU No No Yes
## 120 0 1327 Female Obs No No No
## 121 0 2678 Female Lev+5FU No No No
## 122 0 226 Female Lev No No No
## 123 0 2913 Female Lev+5FU No No No
## 124 0 2862 Male Obs No No No
## 125 1 454 Male Lev+5FU No No No
## 126 0 2743 Male Obs No No No
## 127 0 1679 Female Obs No No No
## 128 1 924 Male Obs Yes No No
## 129 0 721 Male Obs No No No
## 130 0 709 Male Obs No No No
## 131 0 961 Female Lev+5FU No No No
## 132 0 326 Female Lev+5FU Yes No No
## 133 0 2703 Female Lev No No No
## 134 0 289 Female Obs No No Yes
## 135 0 2905 Male Lev+5FU Yes No No
## 136 1 206 Male Lev Yes No No
## 137 0 2618 Male Obs No No No
## 138 1 283 Female Lev No No No
## 139 0 2718 Male Lev Yes No No
## 140 1 2826 Female Obs Yes No No
## 141 0 2916 Male Lev+5FU No No No
## 142 1 499 Male Lev No No No
## 143 0 2950 Female Lev+5FU No No No
## 144 0 2899 Female Obs No No No
## 145 1 673 Female Obs No No No
## 146 0 3000 Female Obs Yes No Yes
## 147 0 2284 Male Obs No No No
## 148 0 362 Male Lev No No No
## 149 0 2152 Female Lev Yes Yes No
## 150 0 2562 Female Obs Yes No No
## 151 0 2730 Male Lev No No No
## 152 1 802 Female Lev+5FU No No No
## 153 0 1166 Male Obs Yes No No
## 154 0 1193 Male Lev+5FU Yes No Yes
## 155 0 45 Male Lev+5FU Yes No No
## 156 0 2577 Male Obs No No No
## 157 1 1136 Female Obs No Yes No
## 158 0 2497 Female Lev Yes No No
## 159 0 2648 Male Lev+5FU Yes No No
## 160 0 2458 Female Obs No No No
## 161 1 1135 Male Lev Yes No No
## 162 0 580 Female Lev+5FU No No No
## 163 1 485 Male Obs Yes No No
## 164 0 2656 Female Lev No No No
## 165 0 806 Female Lev+5FU No No Yes
## 166 0 2435 Male Obs Yes No No
## 167 0 1439 Female Lev+5FU No No No
## 168 0 717 Male Obs No No No
## 169 0 2568 Male Lev Yes Yes No
## 170 0 2631 Female Lev+5FU No No No
## 171 0 1474 Male Lev+5FU No No No
## 172 0 2593 Male Lev No No Yes
## 173 0 1550 Female Lev+5FU No No No
## 174 0 670 Female Obs No No No
## 175 0 430 Male Lev Yes No No
## 176 0 2821 Female Lev+5FU No No No
## 177 0 2672 Male Lev+5FU No No No
## 178 0 2699 Male Lev+5FU No No No
## 179 0 2927 Female Lev+5FU No No No
## 180 0 993 Male Lev+5FU No No Yes
## 181 0 2580 Female Obs No No No
## 182 0 2621 Female Obs No No No
## 183 0 2779 Female Lev No No No
## 184 0 2794 Female Obs No No No
## 185 0 2656 Male Lev+5FU No No No
## 186 1 2513 Female Lev No No No
## 187 0 2488 Female Lev+5FU No No No
## 188 1 1112 Male Lev No No No
## 189 1 2618 Male Lev No No No
## 190 0 795 Male Lev No No Yes
## 191 0 363 Female Lev+5FU No No No
## 192 0 949 Male Obs Yes No Yes
## 193 0 127 Female Lev+5FU Yes No Yes
## 194 0 2871 Female Lev+5FU No No No
## 195 0 2558 Male Obs No No Yes
## 196 0 2083 Female Obs No No No
## 197 0 2747 Female Obs No No No
## 198 0 1105 Male Lev No No No
## 199 1 490 Female Lev+5FU No No No
## 200 0 2507 Female Obs No No No
## 201 0 961 Male Lev No No No
## 202 1 1879 Male Lev No No No
## 203 1 2592 Male Lev+5FU No No No
## 204 0 2552 Female Obs No No No
## 205 0 2474 Female Lev+5FU No No No
## 206 0 2349 Female Lev No No No
## 207 0 2835 Female Lev+5FU No No No
## 208 0 2761 Male Obs No No No
## 209 0 411 Female Obs No No No
## 210 0 2720 Male Lev No No No
## 211 0 2495 Male Lev Yes No No
## 212 1 462 Male Obs No No No
## 213 0 2497 Male Lev+5FU Yes Yes Yes
## 214 0 2343 Male Lev No No Yes
## 215 1 2630 Female Lev+5FU No No No
## 216 1 2461 Female Lev+5FU Yes No No
## 217 0 2747 Female Lev+5FU No No No
## 218 1 2482 Male Lev+5FU Yes No No
## 219 1 580 Male Lev Yes No No
## 220 0 1215 Male Lev No No Yes
## 221 0 2525 Male Lev Yes Yes Yes
## 222 0 2842 Female Lev+5FU No No No
## 223 1 1272 Female Obs No No Yes
## 224 0 438 Male Obs Yes No No
## 225 0 2423 Male Lev No No No
## 226 0 599 Female Obs No No Yes
## 227 0 2706 Female Obs Yes No Yes
## 228 0 2683 Male Lev No No No
## 229 0 2723 Male Lev Yes Yes No
## 230 0 1230 Female Obs No No Yes
## 231 0 2731 Female Obs No No No
## 232 0 2313 Male Obs No No No
## 233 0 2484 Male Lev No No No
## 234 0 2754 Male Lev+5FU <NA> No No
## 235 0 2725 Male Lev+5FU <NA> No No
## 236 0 1295 Female Obs No No No
## 237 0 2506 Female Lev+5FU No No No
## 238 0 2713 Female Lev+5FU No No No
## 239 0 2695 Male Obs No No No
## 240 0 1276 Female Lev+5FU No No No
## 241 0 2600 Male Lev No No No
## 242 0 2352 Male Lev+5FU <NA> No No
## 243 0 2775 Female Lev+5FU No Yes Yes
## 244 0 2442 Female Lev Yes No No
## 245 0 437 Female Obs Yes No Yes
## 246 1 1709 Male Lev No No No
## 247 1 1607 Female Lev+5FU Yes No No
## 248 0 1637 Female Lev+5FU No No No
## 249 0 1117 Female Lev No No No
## 250 0 2732 Male Lev+5FU No No No
## 251 0 222 Male Lev No No No
## 252 0 2688 Female Obs No No No
## 253 0 2520 Male Lev+5FU No No No
## 254 1 595 Female Obs No No No
## 255 0 343 Male Lev No No No
## 256 0 874 Female Obs No No No
## 257 1 232 Female Lev Yes No No
## 258 0 2558 Male Lev No No No
## 259 0 2711 Female Lev No No No
## 260 1 113 Female Obs No No No
## 261 0 643 Female Lev Yes No No
## 262 0 2413 Female Obs No No No
## 263 0 2509 Male Lev No No No
## 264 0 2356 Male Lev No No No
## 265 0 1279 Male Lev+5FU No No No
## 266 0 938 Male Lev No No No
## 267 0 2761 Male Obs No No No
## 268 0 2386 Male Lev Yes No No
## 269 1 433 Female Obs No No Yes
## 270 0 2445 Female Lev+5FU Yes No No
## 271 0 2280 Female Lev No No No
## 272 0 311 Male Obs No No No
## 273 0 977 Male Lev+5FU Yes No No
## 274 1 833 Female Obs Yes No No
## 275 0 582 Male Lev No No No
## 276 0 2541 Female Lev+5FU No No No
## 277 0 238 Male Obs No No No
## 278 1 2257 Female Obs Yes No No
## 279 0 2501 Female Lev No No No
## 280 0 1798 Male Lev+5FU No No No
## 281 0 883 Male Obs No No No
## 282 0 2548 Female Lev No No Yes
## 283 1 2527 Female Lev+5FU No No No
## 284 0 2263 Male Lev Yes No No
## 285 1 706 Female Lev No No No
## 286 0 2588 Female Lev No No No
## 287 0 2542 Male Lev+5FU No No No
## 288 0 1279 Male Lev+5FU No No No
## 289 0 1304 Male Obs No No Yes
## 290 0 2324 Female Obs Yes No No
## 291 0 2488 Male Lev+5FU <NA> No No
## 292 0 2628 Female Lev No No No
## 293 1 2800 Male Obs No No No
## 294 0 2456 Male Lev+5FU No No No
## 295 0 2503 Female Obs No Yes Yes
## 296 0 1446 Female Lev+5FU No No No
## 297 0 641 Male Lev+5FU No No Yes
## 298 0 1788 Male Obs No No No
## 299 1 2304 Male Lev+5FU No No No
## 300 1 944 Female Lev No No No
## 301 0 2679 Male Lev No No No
## 302 1 559 Female Lev Yes No No
## 303 1 2663 Female Lev No No No
## 304 1 647 Male Lev Yes No No
## 305 1 2697 Female Obs No No No
## 306 0 2538 Male Lev+5FU No No No
## 307 0 2219 Female Obs No No No
## 308 0 2487 Male Lev+5FU No No No
## 309 0 2709 Female Lev Yes No No
## 310 1 840 Female Obs No No No
## 311 0 2267 Male Lev+5FU No No No
## 312 0 2444 Male Lev No No No
## 313 1 2393 Female Lev No No No
## 314 0 2237 Female Obs No No No
## 315 0 2915 Male Lev No No No
## 316 0 2467 Female Lev No No No
## 317 0 1092 Female Lev Yes No No
## 318 0 2726 Male Lev No No No
## 319 0 2764 Male Lev Yes No No
## 320 1 2592 Female Lev+5FU No No Yes
## 321 0 2730 Female Obs No No No
## 322 0 2287 Female Obs <NA> No No
## 323 1 2117 Male Lev+5FU No No No
## 324 1 1668 Female Lev+5FU No No No
## 325 0 528 Female Obs No No Yes
## 326 0 2651 Female Obs Yes No No
## 327 0 2676 Female Lev Yes No No
## 328 0 1885 Female Lev Yes No Yes
## 329 0 2350 Male Lev+5FU No No No
## 330 1 475 Male Lev No No No
## 331 1 1246 Female Obs No No No
## 332 0 2204 Male Lev No No Yes
## 333 0 2716 Male Obs No No No
## 334 0 797 Male Lev No No No
## 335 0 2527 Male Lev+5FU No No No
## 336 0 2021 Female Lev+5FU No No Yes
## 337 1 498 Female Lev+5FU No No No
## 338 1 885 Male Lev No No No
## 339 0 802 Female Lev+5FU No No No
## 340 0 2674 Female Lev+5FU No No No
## 341 0 743 Female Obs No No No
## 342 0 2517 Male Lev+5FU No No No
## 343 1 349 Male Lev No No Yes
## 344 0 2723 Male Lev+5FU Yes No No
## 345 0 775 Male Obs <NA> No No
## 346 0 2326 Male Obs No No No
## 347 0 1134 Male Obs No No No
## 348 0 602 Male Lev No No No
## 349 0 2547 Male Lev No No No
## 350 1 940 Female Lev No No No
## 351 0 2496 Female Lev+5FU No No No
## 352 0 2628 Male Obs No No No
## 353 0 2353 Female Lev+5FU No No No
## 354 0 2184 Male Obs No No No
## 355 0 2219 Female Lev+5FU Yes No No
## 356 0 191 Male Lev No No No
## 357 1 421 Male Obs No No No
## 358 1 2362 Female Lev+5FU Yes No No
## 359 1 952 Female Lev No Yes No
## 360 1 911 Female Lev+5FU No No No
## 361 0 1851 Female Lev No No No
## 362 0 2423 Male Obs No No No
## 363 0 464 Female Obs No No Yes
## 364 0 443 Male Lev No No No
## 365 1 186 Female Lev+5FU No No No
## 366 0 2545 Female Lev No No No
## 367 0 356 Male Lev No No No
## 368 1 484 Female Lev+5FU No No No
## 369 0 382 Female Lev No No No
## 370 1 1021 Female Obs No No Yes
## 371 0 2472 Male Lev No No No
## 372 1 2352 Male Lev No No No
## 373 0 2486 Female Obs <NA> No No
## 374 0 324 Male Lev+5FU No No Yes
## 375 0 2517 Male Obs No No Yes
## 376 0 2613 Female Lev No No No
## 377 0 2450 Female Lev+5FU <NA> No No
## 378 0 770 Female Obs No No No
## 379 0 2490 Male Lev+5FU No No No
## 380 0 1548 Male Obs No No No
## 381 0 2449 Male Lev No No No
## 382 1 2299 Male Lev+5FU No No No
## 383 1 1252 Male Lev No No No
## 384 0 730 Female Lev No No No
## 385 0 2460 Female Lev+5FU No No No
## 386 1 499 Female Obs No No No
## 387 1 129 Male Lev No No No
## 388 1 52 Female Lev+5FU No No No
## 389 0 2171 Male Obs Yes Yes No
## 390 0 1178 Female Lev No No No
## 391 0 1915 Female Obs Yes No No
## 392 0 2572 Female Lev No No No
## 393 0 2590 Female Lev+5FU No No No
## 394 1 215 Male Obs No No Yes
## 395 0 2325 Male Obs No No No
## 396 1 961 Female Lev Yes No No
## 397 0 2691 Male Lev No No No
## 398 0 2574 Male Obs No No No
## 399 1 2540 Male Lev+5FU No No No
## 400 0 2364 Female Lev+5FU No No No
## 401 0 2472 Male Lev+5FU No No No
## 402 1 409 Male Obs No No No
## 403 1 961 Male Obs Yes No No
## 404 1 2449 Male Lev No No No
## 405 1 2520 Male Lev No No No
## 406 0 916 Female Lev+5FU No No No
## 407 0 2227 Male Lev <NA> No No
## 408 1 2394 Female Obs No No No
## 409 0 2029 Male Lev+5FU No No No
## 410 0 2487 Male Obs No No No
## 411 0 2052 Male Lev+5FU No No No
## 412 0 2690 Male Lev No No No
## 413 0 2234 Female Obs No No No
## 414 0 537 Male Obs Yes No No
## 415 0 2277 Female Lev+5FU Yes No No
## 416 0 729 Male Lev No No Yes
## 417 0 2194 Male Obs No No No
## 418 1 2551 Female Obs Yes No No
## 419 0 1692 Male Obs No No No
## 420 0 758 Female Obs No No No
## 421 0 2079 Female Lev No No No
## 422 1 720 Female Lev No No Yes
## 423 1 2380 Male Lev No No No
## 424 0 845 Male Obs No No No
## 425 0 2416 Male Lev No No No
## 426 1 863 Male Obs No No No
## 427 0 1363 Female Obs No No Yes
## 428 0 2528 Male Obs No No No
## 429 1 1145 Male Lev+5FU No No No
## 430 1 499 Female Lev+5FU No No No
## 431 0 242 Male Obs No No No
## 432 0 2294 Female Obs No No No
## 433 0 858 Female Lev No No Yes
## 434 1 122 Female Lev No No No
## 435 0 2682 Male Lev+5FU No No No
## 436 0 1818 Male Obs No No No
## 437 0 2532 Male Obs Yes No Yes
## 438 1 331 Male Obs No No Yes
## 439 0 1048 Male Obs No No No
## 440 0 2513 Male Lev+5FU No No No
## 441 0 340 Female Lev+5FU No No Yes
## 442 1 1850 Female Lev <NA> No No
## 443 0 2332 Male Lev No No No
## 444 0 2279 Male Lev+5FU No No No
## 445 1 1041 Male Lev No No No
## 446 0 1790 Male Obs No No No
## 447 0 304 Female Lev+5FU Yes No No
## 448 0 2517 Male Lev+5FU No No No
## 449 0 2156 Female Lev+5FU No No No
## 450 0 1388 Male Lev+5FU No No No
## 451 0 2544 Female Lev Yes No No
## 452 1 1852 Male Obs Yes No Yes
## 453 0 2122 Female Obs Yes No No
## 454 0 2577 Female Obs No No No
## 455 0 2023 Male Lev No No Yes
## 456 0 1201 Female Lev+5FU No No No
## 457 1 901 Male Obs No No Yes
## 458 0 2385 Female Lev No No Yes
## 459 0 663 Female Obs Yes No No
## 460 0 2506 Female Lev No No Yes
## 461 0 2332 Male Lev+5FU No No No
## 462 0 2176 Male Obs No No No
## 463 0 1212 Male Lev+5FU No No No
## 464 0 890 Male Lev No No No
## 465 0 302 Female Lev+5FU No No Yes
## 466 0 2396 Female Obs No No Yes
## 467 0 2481 Male Lev+5FU No No No
## 468 0 316 Male Lev No No No
## 469 0 2245 Female Lev+5FU Yes No No
## 470 0 2447 Male Obs No No Yes
## 471 0 2213 Male Obs No No No
## 472 1 1070 Male Obs No No No
## 473 1 439 Female Lev No No No
## 474 0 905 Male Lev No No No
## 475 1 1723 Male Obs No No No
## 476 1 241 Female Obs No No No
## 477 1 1314 Male Obs No No No
## 478 0 438 Female Lev Yes No No
## 479 0 1981 Female Lev No No No
## 480 0 2195 Female Obs No No Yes
## 481 0 1101 Male Obs Yes Yes Yes
## 482 1 79 Female Lev+5FU Yes No No
## 483 0 976 Male Obs No No No
## 484 1 664 Male Lev No No No
## 485 0 2299 Female Obs No No No
## 486 1 279 Male Lev+5FU No No No
## 487 1 1037 Female Lev No No No
## 488 1 692 Female Obs No No No
## 489 1 2174 Female Lev+5FU No No Yes
## 490 0 2144 Female Lev No No No
## 491 0 2058 Female Lev No No Yes
## 492 0 2485 Male Obs No No No
## 493 0 2410 Female Lev+5FU No No No
## 494 0 2565 Female Lev Yes No Yes
## 495 0 884 Female Lev+5FU No No No
## 496 0 389 Female Lev+5FU No No No
## 497 0 692 Female Lev+5FU No No No
## 498 0 642 Male Lev+5FU Yes No No
## 499 0 846 Male Lev Yes No No
## 500 0 2203 Male Lev+5FU No No No
## 501 0 2164 Male Lev+5FU No No No
## 502 1 1273 Female Lev+5FU No No No
## 503 1 2393 Male Obs No No No
## 504 0 862 Female Lev+5FU No No No
## 505 0 2331 Female Lev+5FU No No No
## 506 0 2264 Male Lev No No No
## 507 1 144 Male Lev+5FU No No No
## 508 0 2429 Male Obs No No No
## 509 0 723 Male Lev Yes No No
## 510 0 2530 Male Obs No No No
## 511 0 1568 Female Lev No No No
## 512 0 2292 Female Obs No No No
## 513 0 2252 Male Lev No No No
## 514 0 2408 Female Lev+5FU No No No
## 515 0 2555 Male Lev No No No
## 516 1 276 Female Lev+5FU No No No
## 517 0 1896 Female Obs No No No
## 518 0 2147 Female Lev+5FU Yes No No
## 519 0 2269 Male Obs No No No
## 520 0 2391 Female Obs No No No
## 521 0 1424 Male Lev+5FU No No No
## 522 1 2257 Female Obs No No No
## 523 1 2381 Female Lev+5FU <NA> No No
## 524 0 2103 Female Lev+5FU Yes No No
## 525 0 2210 Female Obs No No Yes
## 526 0 2530 Female Lev+5FU No No No
## 527 0 2386 Male Lev No No No
## 528 0 219 Male Lev No No No
## 529 0 486 Male Lev No No No
## 530 1 1246 Male Lev+5FU No No No
## 531 1 2138 Male Lev No No No
## 532 0 2439 Female Lev+5FU No No No
## 533 0 2231 Male Obs No No No
## 534 1 384 Male Obs No No No
## 535 0 2505 Male Lev+5FU No No No
## 536 0 1652 Female Lev No No No
## 537 0 2441 Female Lev+5FU No No Yes
## 538 0 687 Female Obs No No No
## 539 0 2179 Male Lev+5FU No No No
## 540 1 2189 Female Lev+5FU Yes No No
## 541 1 2472 Male Lev No No No
## 542 0 2111 Male Lev+5FU No No No
## 543 1 2020 Male Lev+5FU No No No
## 544 1 1161 Female Lev No Yes No
## 545 0 2231 Male Obs No No No
## 546 0 2300 Male Lev+5FU No No No
## 547 0 2391 Male Obs No No No
## 548 0 759 Male Lev No No Yes
## 549 1 166 Male Obs No No No
## 550 0 2323 Female Lev No No Yes
## 551 0 2321 Female Lev+5FU No No No
## 552 1 1976 Female Obs Yes No No
## 553 1 2229 Male Obs No No No
## 554 0 1671 Female Lev+5FU No No No
## 555 0 1907 Male Obs No No No
## 556 1 1783 Male Lev+5FU No No No
## 557 1 684 Female Lev No No No
## 558 1 441 Male Lev+5FU No No No
## 559 0 902 Female Lev No No No
## 560 1 2244 Male Lev No No No
## 561 1 2170 Female Obs Yes No No
## 562 0 1870 Male Obs No No No
## 563 0 2066 Male Lev No No No
## 564 0 2030 Male Lev No No No
## 565 0 253 Female Obs No No No
## 566 0 2047 Male Lev+5FU No No No
## 567 1 1768 Female Lev No No No
## 568 0 2043 Female Lev+5FU No No No
## 569 0 2162 Male Lev+5FU No No No
## 570 0 2093 Male Obs No No No
## 571 0 2310 Female Lev No No No
## 572 0 2128 Male Lev No No No
## 573 0 1884 Male Obs No No No
## 574 0 219 Male Lev No No No
## 575 0 2309 Male Lev+5FU No No No
## 576 1 313 Female Obs No No No
## 577 0 546 Male Lev No No Yes
## 578 0 2213 Female Obs No No No
## 579 0 1856 Male Lev+5FU No No No
## 580 0 1421 Female Lev+5FU No No No
## 581 0 460 Female Lev+5FU No No No
## 582 0 2173 Female Lev No No No
## 583 0 283 Female Lev+5FU No No No
## 584 1 34 Male Lev+5FU Yes No No
## 585 0 2191 Male Obs No No No
## 586 1 2186 Female Lev No No No
## 587 0 1159 Female Obs No No No
## 588 0 616 Female Lev+5FU Yes No No
## 589 0 2270 Male Lev No No No
## 590 1 1061 Male Lev No No Yes
## 591 0 591 Male Obs Yes No No
## 592 0 2065 Female Lev No No No
## 593 0 208 Female Obs Yes No Yes
## 594 0 2360 Male Lev+5FU No No No
## 595 0 2312 Female Lev No No No
## 596 0 1902 Female Lev No No No
## 597 1 1814 Male Lev+5FU Yes No No
## 598 0 2111 Male Obs Yes No No
## 599 0 2330 Male Lev+5FU No No No
## 600 1 2202 Male Obs No No No
## 601 0 1295 Female Lev No No No
## 602 1 1918 Female Lev No No Yes
## 603 1 2066 Female Obs No No Yes
## 604 0 2136 Female Lev+5FU No No No
## 605 0 2289 Male Lev No No No
## 606 1 576 Female Lev+5FU Yes No No
## 607 0 2232 Female Obs No No No
## 608 0 1034 Female Lev <NA> No No
## 609 1 583 Male Lev+5FU Yes No No
## 610 0 417 Male Obs No No No
## 611 0 1905 Female Lev+5FU No No Yes
## 612 0 875 Male Lev No No No
## 613 0 674 Male Lev+5FU No No No
## 614 0 2185 Male Lev No No No
## 615 0 1151 Male Lev+5FU No No No
## 616 1 342 Female Lev Yes No No
## 617 1 2187 Female Obs No No No
## 618 1 1434 Female Obs No No Yes
## 619 1 430 Male Lev+5FU No No No
## 620 0 2339 Female Lev No No Yes
## 621 0 1365 Male Lev+5FU No No Yes
## 622 0 2313 Female Obs No No No
## 623 0 2153 Male Obs No No No
## 624 0 2164 Male Lev+5FU No No No
## 625 0 2180 Male Lev+5FU No No No
## 626 0 2110 Male Obs No No No
## 627 0 2139 Male Obs No No No
## 628 0 2120 Male Lev+5FU No No No
## 629 1 2197 Female Lev+5FU No No No
## 630 0 453 Male Obs No No No
## 631 1 928 Male Obs No No No
## 632 0 675 Female Lev Yes No No
## 633 0 2170 Male Obs Yes No No
## 634 0 2138 Female Obs No No No
## 635 0 2255 Male Lev+5FU No Yes No
## 636 1 2290 Female Lev+5FU No No No
## 637 0 1055 Female Lev Yes No No
## 638 0 2347 Female Lev No No No
## 639 0 573 Male Lev No No No
## 640 0 2200 Male Obs No No No
## 641 1 550 Female Lev+5FU No No No
## 642 0 1405 Male Lev No No No
## 643 0 2355 Male Lev+5FU Yes No No
## 644 1 1186 Male Lev No No No
## 645 0 1540 Male Lev No No Yes
## 646 0 2229 Male Lev+5FU Yes No Yes
## 647 0 969 Male Lev No No No
## 648 0 465 Male Obs No No No
## 649 1 603 Female Lev+5FU No No No
## 650 1 997 Female Lev No No Yes
## 651 0 2274 Male Lev No No No
## 652 0 563 Female Obs No No No
## 653 0 1434 Male Lev No No Yes
## 654 0 2316 Female Lev+5FU No No No
## 655 0 692 Female Lev+5FU Yes No No
## 656 0 1447 Male Obs No No No
## 657 0 428 Female Lev+5FU No No No
## 658 0 2152 Female Lev No No No
## 659 0 854 Male Obs No No No
## 660 0 2093 Male Lev No No No
## 661 0 2198 Male Lev+5FU No No Yes
## 662 0 2126 Male Obs No No No
## 663 0 2189 Male Lev+5FU No No No
## 664 0 2142 Male Lev Yes No No
## 665 0 2278 Male Lev+5FU No No No
## 666 0 622 Male Obs Yes No No
## 667 1 2192 Female Lev+5FU Yes No No
## 668 0 413 Male Obs Yes No No
## 669 0 1191 Female Lev No No No
## 670 0 1139 Female Obs No No No
## 671 0 165 Male Lev Yes No No
## 672 0 2210 Male Obs No No Yes
## 673 1 2227 Male Obs No No No
## 674 0 2076 Male Lev No No No
## 675 0 2132 Male Obs No No No
## 676 0 2084 Female Lev+5FU Yes No No
## 677 0 1905 Male Obs No No No
## 678 1 608 Female Lev No No No
## 679 0 2066 Male Lev+5FU No No No
## 680 0 2006 Female Obs No No No
## 681 0 2183 Male Lev No No No
## 682 0 2099 Male Lev+5FU No No No
## 683 0 1879 Male Lev No No No
## 684 0 264 Female Obs Yes No No
## 685 0 2107 Female Lev+5FU Yes No No
## 686 1 743 Male Lev No No No
## 687 0 966 Male Obs No No No
## 688 0 2076 Male Lev+5FU No No No
## 689 0 24 Male Lev Yes No No
## 690 0 448 Female Lev+5FU No Yes No
## 691 1 909 Female Lev No No No
## 692 0 2188 Female Lev No No No
## 693 0 469 Male Obs <NA> No No
## 694 0 594 Female Obs No Yes Yes
## 695 0 2008 Female Lev+5FU No No No
## 696 0 1276 Male Lev+5FU No No No
## 697 0 957 Male Obs No No No
## 698 0 1950 Male Obs No No No
## 699 0 2668 Male Lev+5FU No No No
## 700 0 2250 Female Lev+5FU Yes No No
## 701 0 2191 Female Lev No No No
## 702 0 2365 Male Obs No No Yes
## 703 0 2331 Female Lev No No No
## 704 1 1262 Male Lev No No Yes
## 705 0 1537 Male Lev No No No
## 706 1 2387 Male Lev No No No
## 707 0 2235 Male Obs No No No
## 708 0 1980 Female Lev No No No
## 709 0 578 Male Lev+5FU No No No
## 710 0 1083 Male Obs No No No
## 711 0 1875 Male Obs No No No
## 712 0 2384 Female Obs No No No
## 713 0 563 Male Obs Yes No No
## 714 0 2076 Female Lev+5FU No No No
## 715 0 2025 Male Obs No No No
## 716 1 2055 Male Lev+5FU No No No
## 717 0 1375 Female Obs No No No
## 718 0 2350 Male Lev+5FU No No No
## 719 0 2200 Female Lev No No Yes
## 720 0 2222 Male Lev+5FU Yes Yes No
## 721 1 2149 Male Obs No No No
## 722 0 2303 Male Lev No No No
## 723 0 322 Male Obs No Yes No
## 724 0 764 Male Lev No No No
## 725 0 765 Female Lev+5FU Yes No Yes
## 726 1 93 Female Lev No No No
## 727 0 1918 Male Lev+5FU Yes No No
## 728 0 1932 Male Lev No No No
## 729 0 2278 Female Obs No No No
## 730 1 145 Male Obs Yes No No
## 731 0 1913 Female Lev+5FU No No No
## 732 0 2176 Male Obs No No No
## 733 0 1995 Female Obs No No No
## 734 0 2023 Male Lev+5FU No No Yes
## 735 1 1935 Male Obs No No No
## 736 1 2191 Male Obs No No No
## 737 0 2191 Female Lev+5FU No No No
## 738 0 1856 Male Obs No No No
## 739 1 628 Male Lev No No No
## 740 0 1976 Male Lev+5FU No No No
## 741 1 1819 Female Obs No No No
## 742 1 141 Female Lev+5FU No No Yes
## 743 0 422 Male Lev Yes No No
## 744 0 2006 Male Lev Yes No No
## 745 0 2113 Female Obs No No No
## 746 0 1823 Male Obs No No No
## 747 0 2170 Male Obs Yes No No
## 748 1 1812 Male Lev+5FU No No No
## 749 0 1838 Female Lev No No No
## 750 0 1855 Male Obs Yes No No
## 751 0 269 Female Lev+5FU Yes No No
## 752 0 2414 Male Lev No No No
## 753 0 2174 Male Lev No No Yes
## 754 0 2263 Male Lev+5FU No No No
## 755 1 1495 Male Lev+5FU No No No
## 756 1 314 Female Lev No No No
## 757 0 2261 Male Obs No No No
## 758 1 716 Female Obs No No No
## 759 0 2190 Male Obs No No No
## 760 1 2331 Female Lev+5FU No No No
## 761 0 2187 Female Lev No No No
## 762 0 602 Male Lev No No Yes
## 763 0 666 Female Lev+5FU No No Yes
## 764 1 138 Male Lev+5FU No No No
## 765 0 2001 Female Obs Yes No No
## 766 1 887 Female Lev+5FU No No No
## 767 0 1207 Female Lev No Yes No
## 768 0 1997 Male Lev+5FU No No No
## 769 0 1864 Female Lev No No No
## 770 1 2422 Male Lev+5FU <NA> No Yes
## 771 1 444 Female Lev Yes No No
## 772 0 2375 Female Lev+5FU No Yes Yes
## 773 0 718 Female Obs Yes No No
## 774 0 2204 Male Obs No No No
## 775 0 2120 Male Obs No No Yes
## 776 1 766 Female Lev No Yes Yes
## 777 1 366 Female Lev Yes No Yes
## 778 1 1752 Female Lev+5FU No No No
## 779 1 2183 Male Lev+5FU No No Yes
## 780 0 1902 Female Obs No No Yes
## 781 1 259 Male Obs No No No
## 782 0 609 Female Lev+5FU No Yes Yes
## 783 0 832 Female Obs Yes No No
## 784 0 164 Male Obs Yes No Yes
## 785 0 1828 Male Lev No No Yes
## 786 0 2147 Female Lev No No No
## 787 1 201 Female Obs No No No
## 788 0 2221 Female Lev+5FU No No No
## 789 0 503 Female Lev+5FU No No No
## 790 1 376 Male Lev No No No
## 791 0 811 Female Lev+5FU No No No
## 792 0 1985 Female Lev+5FU No No No
## 793 0 2076 Male Obs No No No
## 794 1 1154 Male Lev No No No
## 795 1 844 Male Lev+5FU No No No
## 796 0 1031 Male Obs Yes No Yes
## 797 0 1302 Male Lev+5FU No No No
## 798 0 2169 Female Lev+5FU Yes No No
## 799 0 1929 Female Obs No No No
## 800 0 1800 Female Lev+5FU No No No
## 801 1 355 Female Lev No No No
## 802 0 669 Male Lev No No No
## 803 1 465 Female Obs <NA> No No
## 804 1 2157 Male Obs No No No
## 805 1 929 Male Obs No No No
## 806 0 2242 Female Lev No No No
## 807 0 2212 Male Lev No No No
## 808 0 2148 Male Lev No No No
## 809 1 171 Male Lev Yes No No
## 810 0 629 Male Lev Yes No No
## 811 0 1829 Male Lev No No No
## 812 1 1939 Male Lev No Yes No
## 813 1 529 Female Lev+5FU No No No
## 814 0 2130 Female Obs Yes No No
## 815 0 1990 Female Obs No No No
## 816 1 587 Male Obs No No No
## 817 1 1145 Female Lev No No No
## 818 0 2162 Male Lev+5FU No No No
## 819 1 643 Male Lev+5FU Yes No No
## 820 1 2129 Male Lev No No No
## 821 0 1437 Male Obs No No No
## 822 1 512 Male Lev Yes No No
## 823 0 2008 Female Obs Yes No No
## 824 0 1814 Female Lev+5FU No No No
## 825 0 2161 Female Lev Yes No Yes
## 826 1 506 Female Obs Yes No No
## 827 0 1482 Male Obs No No No
## 828 1 1964 Male Lev No No No
## 829 1 693 Female Lev+5FU No No No
## 830 0 592 Female Lev+5FU No No Yes
## 831 0 2207 Male Lev+5FU No No No
## 832 0 2181 Female Lev+5FU No No No
## 833 1 696 Male Lev+5FU No No No
## 834 1 257 Female Lev No No No
## 835 0 2171 Female Lev No No No
## 836 0 2209 Female Lev+5FU Yes No No
## 837 0 1122 Female Lev Yes No No
## 838 0 936 Female Obs No No No
## 839 1 601 Female Lev+5FU Yes No No
## 840 0 2265 Female Obs Yes No No
## 841 0 2198 Female Lev+5FU No No No
## 842 1 275 Female Obs No No No
## 843 0 1195 Male Obs No No No
## 844 0 2099 Male Lev Yes No No
## 845 0 2165 Female Lev+5FU No No No
## 846 0 2212 Male Lev No No No
## 847 0 355 Male Lev+5FU No No No
## 848 0 2097 Female Obs No No No
## 849 0 56 Female Lev Yes No No
## 850 0 589 Male Lev Yes No No
## 851 1 510 Male Obs No No No
## 852 0 2250 Female Lev No No No
## 853 0 612 Male Obs Yes No Yes
## 854 1 2284 Female Lev No No No
## 855 0 1992 Female Lev No No No
## 856 1 251 Male Lev+5FU Yes No No
## 857 0 2070 Female Lev+5FU No No No
## 858 0 1209 Female Obs No No No
## 859 0 2122 Female Lev No No No
## 860 0 2111 Female Lev Yes No No
## 861 1 274 Female Lev+5FU No No Yes
## 862 0 1306 Female Lev+5FU No No No
## 863 0 1325 Female Lev No No No
## 864 1 1968 Male Obs No No Yes
## 865 0 753 Female Obs No No No
## 866 0 760 Male Obs No No Yes
## 867 1 1861 Male Lev+5FU No No No
## 868 0 1138 Male Lev+5FU No No No
## 869 0 2167 Female Obs No No No
## 870 0 1944 Male Lev+5FU Yes No No
## 871 1 372 Female Obs No No No
## 872 0 1792 Female Obs No No No
## 873 0 986 Male Lev No No Yes
## 874 0 2378 Female Lev+5FU Yes No No
## 875 1 390 Male Obs No Yes Yes
## 876 0 642 Female Lev No No Yes
## 877 0 2345 Male Lev No No No
## 878 0 2254 Male Lev No No No
## 879 0 2118 Female Obs No No No
## 880 0 1831 Female Lev+5FU Yes No No
## 881 0 2167 Female Obs No No No
## 882 0 1198 Male Obs No No No
## 883 0 2050 Male Lev+5FU No No Yes
## 884 0 271 Male Lev+5FU No No Yes
## 885 0 2138 Female Lev No No No
## 886 0 1891 Female Obs Yes No No
## 887 1 1313 Male Obs No No No
## 888 0 1853 Male Lev+5FU No No No
## 889 0 2130 Male Lev Yes No No
## 890 1 150 Male Lev No No No
## 891 1 759 Female Lev No No No
## 892 0 2100 Male Lev No No No
## 893 0 2101 Female Lev+5FU No No No
## 894 0 942 Male Lev No No No
## 895 1 1823 Female Obs No No No
## 896 0 665 Male Obs No No No
## 897 0 1656 Male Obs Yes Yes Yes
## 898 0 1969 Male Lev+5FU No No No
## 899 0 2190 Female Lev No No No
## 900 1 576 Female Obs Yes No No
## 901 1 1103 Male Lev No No No
## 902 0 1046 Male Lev No No Yes
## 903 0 1929 Female Lev+5FU No No No
## 904 1 125 Male Obs No No No
## 905 0 187 Female Obs No No No
## 906 0 939 Male Lev <NA> No No
## 907 1 887 Female Obs No No No
## 908 0 1803 Female Obs No No No
## 909 0 2018 Male Lev+5FU No No No
## 910 1 1509 Female Lev No No Yes
## 911 1 314 Male Lev No No No
## 912 0 1971 Male Lev No No No
## 913 0 1827 Male Lev+5FU Yes Yes Yes
## 914 0 1079 Female Obs Yes No No
## 915 1 2114 Female Lev No No No
## 916 1 1262 Female Obs No No No
## 917 1 259 Female Obs No No No
## 918 1 323 Male Lev No No No
## 919 0 678 Female Lev Yes No Yes
## 920 1 1827 Female Lev+5FU No No Yes
## 921 0 1399 Male Lev Yes No No
## 922 0 1022 Female Lev+5FU No No No
## 923 0 2240 Male Lev+5FU Yes No No
## 924 0 2158 Male Obs Yes No Yes
## 925 0 1875 Male Lev+5FU No No Yes
## 926 0 2154 Female Lev No No No
## 927 0 1018 Male Lev No No Yes
## 928 1 2072 Female Lev+5FU Yes No No
## 929 0 1820 Female Lev Yes No No
## differ.factor extent.factor surg.factor node4.factor status.factor
## 1 Moderate Serosa Short Yes Died
## 2 Moderate Serosa Short No Alive
## 3 Moderate Muscle Short Yes Died
## 4 Moderate Serosa Long Yes Died
## 5 Moderate Serosa Long Yes Died
## 6 Moderate Serosa Short Yes Died
## 7 Moderate Serosa Long Yes Died
## 8 Moderate Serosa Short No Alive
## 9 Moderate Serosa Short No Alive
## 10 Moderate Serosa Long No Alive
## 11 Moderate Serosa Short No Alive
## 12 Poor Serosa Long No Alive
## 13 Moderate Serosa Short No Died
## 14 Moderate Serosa Short No Died
## 15 Moderate Serosa Short No Alive
## 16 Moderate Serosa Long No Alive
## 17 Moderate Serosa Short Yes Died
## 18 Moderate Serosa Long No Died
## 19 Moderate Muscle Short No Died
## 20 Moderate Serosa Short No Alive
## 21 Moderate Serosa Long No Died
## 22 Moderate Serosa Long No Died
## 23 Moderate Serosa Short No Died
## 24 Moderate Muscle Short No Alive
## 25 Moderate Serosa Short No Alive
## 26 Moderate Serosa Short No Died
## 27 Moderate Serosa Short Yes Died
## 28 Moderate Serosa Short No Died
## 29 Poor Serosa Short Yes Died
## 30 Poor Serosa Short No Died
## 31 Moderate Submucosa Short No Alive
## 32 Moderate Serosa Short No Alive
## 33 Moderate Serosa Long No Died
## 34 Moderate Serosa Long No Died
## 35 Moderate Serosa Long No Died
## 36 Poor Serosa Long No Alive
## 37 Moderate Serosa Short Yes Died
## 38 Poor Serosa Short No Alive
## 39 Poor Serosa Short No Alive
## 40 Moderate Serosa Short Yes Died
## 41 Moderate Serosa Long No Died
## 42 Well Serosa Long No Alive
## 43 Moderate Muscle Long No Died
## 44 Moderate Serosa Short No Alive
## 45 Well Serosa Long No Alive
## 46 Moderate Serosa Short No Alive
## 47 Poor Submucosa Short No Alive
## 48 Well Serosa Long No Alive
## 49 Moderate Serosa Short Yes Alive
## 50 Poor Serosa Short Yes Died
## 51 Moderate Serosa Long No Died
## 52 Moderate Serosa Short No Died
## 53 Moderate Serosa Short No Alive
## 54 Moderate Serosa Short No Alive
## 55 Moderate Muscle Long No Alive
## 56 Well Serosa Short No Died
## 57 Moderate Serosa Short No Alive
## 58 Moderate Serosa Long Yes Alive
## 59 Poor Serosa Long Yes Alive
## 60 Poor Serosa Short No Alive
## 61 Moderate Serosa Long No Died
## 62 Well Muscle Long No Alive
## 63 Poor Serosa Short Yes Died
## 64 <NA> Serosa Short No Alive
## 65 Well Serosa Short No Died
## 66 Moderate Serosa Short No Alive
## 67 Poor Serosa Short Yes Alive
## 68 Moderate Serosa Short Yes Died
## 69 Moderate Submucosa Short No Alive
## 70 Moderate Serosa Long No Died
## 71 Moderate Serosa Short No Died
## 72 Moderate Serosa Short Yes Died
## 73 Moderate Serosa Short Yes Alive
## 74 Poor Serosa Short Yes Died
## 75 Moderate Serosa Short Yes Died
## 76 Moderate Serosa Short No Alive
## 77 Moderate Serosa Long Yes Died
## 78 Moderate Serosa Long No Alive
## 79 Moderate Serosa Short No Alive
## 80 Moderate Muscle Short Yes Died
## 81 Moderate Muscle Short No Alive
## 82 Poor Serosa Short No Died
## 83 <NA> Muscle Short No Died
## 84 Moderate Muscle Short No Alive
## 85 Poor Serosa Short Yes Died
## 86 Moderate Serosa Short No Alive
## 87 Moderate Muscle Short No Alive
## 88 Moderate Serosa Short No Died
## 89 Well Serosa <NA> No Alive
## 90 <NA> Serosa Short No Died
## 91 Moderate Serosa Short Yes Died
## 92 Moderate Serosa Short No Died
## 93 Moderate Serosa Short Yes Alive
## 94 Moderate Adjacent structures Long Yes Alive
## 95 Moderate Serosa Short No Alive
## 96 Moderate Adjacent structures Long No Died
## 97 Moderate Adjacent structures Short Yes Died
## 98 Moderate Serosa Short No Died
## 99 Moderate Adjacent structures Short Yes Died
## 100 Moderate Muscle Short Yes Died
## 101 Moderate Serosa Short Yes Died
## 102 Poor Serosa Short Yes Died
## 103 Moderate Serosa Short No Died
## 104 Moderate Serosa Short Yes Died
## 105 Moderate Serosa Short No Alive
## 106 Poor Serosa Short No Died
## 107 Moderate Serosa Long Yes Died
## 108 Moderate Serosa Short No Died
## 109 Moderate Serosa Short Yes Alive
## 110 Poor Serosa Long No Died
## 111 Moderate Serosa Short Yes Alive
## 112 Moderate Serosa Short No Died
## 113 Moderate Submucosa Short No Alive
## 114 Poor Serosa Short Yes Died
## 115 Poor Serosa Short No Died
## 116 Moderate Serosa Long Yes Died
## 117 Moderate Serosa Short No Alive
## 118 Moderate Serosa Short Yes Alive
## 119 Moderate Serosa Long No Alive
## 120 Moderate Serosa Short No Died
## 121 Moderate Serosa Short No Alive
## 122 Poor Serosa Short No Died
## 123 Moderate Serosa Long No Alive
## 124 Moderate Serosa Long No Alive
## 125 Poor Serosa Short Yes Died
## 126 Moderate Muscle Short No Alive
## 127 Moderate Serosa Short No Died
## 128 Poor Serosa Short Yes Died
## 129 Moderate Muscle Short No Died
## 130 Moderate Serosa Short No Died
## 131 Moderate Serosa Short No Died
## 132 Poor Serosa Short No Died
## 133 Poor Muscle Long No Alive
## 134 Moderate Serosa Short No Died
## 135 Moderate Serosa Long No Alive
## 136 Moderate Serosa Short Yes Died
## 137 Moderate Serosa Long No Alive
## 138 Moderate Serosa Short Yes Died
## 139 Moderate Serosa Short No Died
## 140 Moderate Serosa Short Yes Alive
## 141 Moderate Serosa Short No Alive
## 142 Poor Serosa Short Yes Died
## 143 Well Serosa Short No Alive
## 144 Moderate Submucosa Short No Alive
## 145 Poor Serosa Long Yes Died
## 146 Well Serosa Short No Alive
## 147 Moderate Serosa Long No Died
## 148 Well Serosa Short No Died
## 149 Moderate Serosa Short No Died
## 150 Moderate Serosa Long No Alive
## 151 Moderate Serosa Short No Alive
## 152 Moderate Serosa Short Yes Died
## 153 Poor Serosa Long No Died
## 154 Moderate Serosa Short No Died
## 155 Moderate Serosa Long No Died
## 156 Moderate Serosa Short No Alive
## 157 Well Serosa Short Yes Died
## 158 Moderate Serosa Short No Alive
## 159 Moderate Serosa Short No Alive
## 160 Poor Serosa Short No Alive
## 161 <NA> Serosa Short Yes Died
## 162 Moderate Serosa Short No Died
## 163 Moderate Serosa Long Yes Died
## 164 Moderate Serosa Short No Alive
## 165 Moderate Serosa Long No Died
## 166 Moderate Serosa Short No Alive
## 167 Moderate Serosa Short No Died
## 168 Poor Serosa Long No Died
## 169 Moderate Serosa Short No Alive
## 170 Well Serosa Short No Alive
## 171 Moderate Muscle Short No Alive
## 172 Moderate Serosa Long No Died
## 173 Moderate Serosa Long No Died
## 174 Moderate Serosa Short No Died
## 175 Moderate Serosa Long No Died
## 176 Moderate Serosa Long No Alive
## 177 Moderate Submucosa Short No Alive
## 178 Moderate Submucosa Short No Alive
## 179 Well Muscle Short No Alive
## 180 Moderate Serosa Short No Died
## 181 Moderate Serosa Short No Alive
## 182 Moderate Serosa Short No Alive
## 183 Poor Serosa Short No Alive
## 184 Moderate Muscle Short No Alive
## 185 Moderate Serosa Short No Alive
## 186 Well Serosa Long Yes Alive
## 187 Moderate Serosa Long No Alive
## 188 Poor Serosa Short Yes Died
## 189 Moderate Serosa Short Yes Alive
## 190 <NA> Serosa Short No Died
## 191 Moderate Serosa Short No Died
## 192 Moderate Serosa Short No Died
## 193 Moderate Serosa Long No Died
## 194 Moderate Serosa Short No Alive
## 195 Moderate Serosa Short No Alive
## 196 Moderate Serosa Short No Died
## 197 Poor Muscle Short No Alive
## 198 Well Serosa Short No Died
## 199 Poor Serosa Long Yes Died
## 200 <NA> Muscle Long No Alive
## 201 Well Serosa Long No Died
## 202 <NA> Serosa Long Yes Died
## 203 Poor Serosa Short Yes Alive
## 204 Moderate Serosa Short No Died
## 205 Well Submucosa Short No Alive
## 206 Moderate Serosa Short No Alive
## 207 Well Submucosa Short No Alive
## 208 Moderate Serosa Long No Alive
## 209 Moderate Serosa Long No Died
## 210 Well Serosa Short No Alive
## 211 Moderate Serosa Short No Alive
## 212 Moderate Serosa Short Yes Died
## 213 Poor Adjacent structures Long No Alive
## 214 Moderate Muscle Short No Alive
## 215 Moderate Serosa Short Yes Alive
## 216 Moderate Serosa Short Yes Alive
## 217 Moderate Adjacent structures <NA> No Alive
## 218 Moderate Serosa Short Yes Died
## 219 Poor Serosa Short Yes Died
## 220 Moderate Serosa Short No Died
## 221 Poor Serosa Long No Alive
## 222 Moderate Muscle Short No Alive
## 223 Moderate Serosa Long Yes Died
## 224 Moderate Serosa Short No Died
## 225 Moderate Serosa Short No Alive
## 226 Moderate Adjacent structures Long No Died
## 227 Moderate Serosa Short No Alive
## 228 Moderate Serosa Short No Died
## 229 Moderate Serosa Short No Alive
## 230 Moderate Adjacent structures Short No Died
## 231 Moderate Serosa Long No Alive
## 232 Moderate Serosa Short No Alive
## 233 Moderate Muscle Long No Alive
## 234 Well Serosa Short No Alive
## 235 Moderate Muscle Short No Died
## 236 Moderate Serosa Short No Died
## 237 Moderate Serosa Short No Alive
## 238 Moderate Serosa Short No Alive
## 239 Moderate Serosa Short No Alive
## 240 Moderate Serosa Short No Died
## 241 Moderate Adjacent structures <NA> No Alive
## 242 Moderate Muscle Short No Alive
## 243 Moderate Serosa Long No Alive
## 244 <NA> Serosa Short No Alive
## 245 Poor Serosa Short No Died
## 246 Moderate Serosa Long Yes Died
## 247 Moderate Serosa Short Yes Died
## 248 Moderate Serosa Long No Died
## 249 Well Serosa Short No Died
## 250 Moderate Serosa Long No Alive
## 251 Poor Serosa Short No Died
## 252 Moderate Adjacent structures Short No Alive
## 253 Moderate Serosa Short No Alive
## 254 Poor Serosa Short Yes Died
## 255 Moderate Serosa Long No Died
## 256 Moderate Serosa Short No Died
## 257 Moderate Serosa Short Yes Died
## 258 Moderate Muscle Short No Alive
## 259 Moderate Serosa Short No Alive
## 260 Moderate Serosa Short Yes Died
## 261 Moderate Serosa Short No Died
## 262 Moderate Serosa Long No Alive
## 263 Moderate Submucosa Short No Alive
## 264 Well Serosa Short No Alive
## 265 Moderate Serosa Long No Died
## 266 Well Serosa Short No Died
## 267 Moderate Serosa Short No Alive
## 268 Moderate Serosa Long No Alive
## 269 Moderate Serosa Short Yes Died
## 270 Poor Serosa Long No Alive
## 271 Moderate Muscle Short No Alive
## 272 Well Serosa Short No Died
## 273 Well Serosa Short No Died
## 274 Well Serosa Short Yes Died
## 275 Moderate Serosa Short No Died
## 276 Well Serosa Short No Alive
## 277 Moderate Serosa Long No Died
## 278 Moderate Adjacent structures Short Yes Died
## 279 Moderate Muscle Short No Alive
## 280 Moderate Serosa Long No Died
## 281 Moderate Serosa Short No Died
## 282 Poor Serosa Short No Alive
## 283 Moderate Serosa Short Yes Alive
## 284 Moderate Serosa Short No Alive
## 285 Moderate Serosa Short Yes Died
## 286 Moderate Muscle Short No Alive
## 287 Moderate Muscle Long No Died
## 288 Moderate Serosa Short No Alive
## 289 Poor Adjacent structures Short No Died
## 290 Moderate Serosa Short No Alive
## 291 Well Serosa Short No Alive
## 292 Moderate Serosa Long No Alive
## 293 Moderate Serosa Long Yes Alive
## 294 <NA> Serosa Short No Alive
## 295 Moderate Serosa Short No Alive
## 296 Moderate Serosa Short No Died
## 297 Moderate Serosa Short No Died
## 298 Moderate Serosa Short No Died
## 299 Moderate Muscle Short Yes Alive
## 300 Moderate Serosa Short Yes Died
## 301 Moderate Muscle Long No Alive
## 302 Moderate Serosa Long Yes Died
## 303 Moderate Serosa Long Yes Alive
## 304 Poor Serosa Short Yes Died
## 305 Moderate Serosa Short Yes Alive
## 306 Poor Serosa Short No Alive
## 307 Poor Serosa Long No Alive
## 308 Moderate Serosa Long No Alive
## 309 Moderate Serosa Short No Alive
## 310 Poor Serosa Short Yes Died
## 311 Moderate Serosa Long No Alive
## 312 Moderate Muscle Short No Alive
## 313 Well Serosa Short Yes Alive
## 314 Well Submucosa Short No Alive
## 315 Moderate Serosa Short No Alive
## 316 Moderate Serosa Short No Alive
## 317 Moderate Serosa Short No Died
## 318 Moderate Muscle Long No Alive
## 319 Moderate Serosa Long No Alive
## 320 Poor Adjacent structures Short Yes Alive
## 321 Well Muscle Short No Alive
## 322 Moderate Muscle Short No Died
## 323 Moderate Serosa Short Yes Alive
## 324 Moderate Serosa Short Yes Died
## 325 <NA> Adjacent structures Short No Died
## 326 Well Serosa Long No Alive
## 327 Moderate Serosa Long No Alive
## 328 Moderate Muscle Long No Died
## 329 <NA> Serosa Short No Alive
## 330 Moderate Serosa Long Yes Died
## 331 Moderate Serosa <NA> Yes Died
## 332 Poor Serosa Short No Alive
## 333 Moderate Adjacent structures Short No Alive
## 334 Moderate Serosa Short No Died
## 335 Moderate Serosa Short No Alive
## 336 Poor Serosa Short No Died
## 337 Moderate Serosa Short Yes Died
## 338 Poor Serosa Short Yes Died
## 339 Moderate Serosa Short No Died
## 340 Moderate Serosa Long No Alive
## 341 Moderate Serosa Long No Died
## 342 Moderate Muscle Long No Alive
## 343 Moderate Serosa Long Yes Died
## 344 Moderate Serosa Short No Alive
## 345 Poor Serosa Long No Died
## 346 Moderate Serosa Short No Alive
## 347 Moderate Serosa Short No Died
## 348 <NA> Serosa Long No Died
## 349 Poor Serosa Short No Alive
## 350 Moderate Serosa Short Yes Died
## 351 Moderate Serosa Short No Alive
## 352 Moderate Serosa Short No Alive
## 353 Moderate Serosa Short No Alive
## 354 Moderate Serosa Long No Alive
## 355 Moderate Serosa Long No Alive
## 356 Moderate Serosa Short No Died
## 357 Moderate Serosa Short Yes Died
## 358 Moderate Serosa Short Yes Alive
## 359 Moderate Serosa Long Yes Died
## 360 Moderate Serosa Long Yes Died
## 361 Moderate Serosa Short No Died
## 362 Moderate Muscle Short No Alive
## 363 Poor Serosa Long No Died
## 364 Moderate Serosa Short No Died
## 365 Poor Serosa Short Yes Died
## 366 Moderate Serosa Long No Alive
## 367 Moderate Adjacent structures Short No Died
## 368 Poor Serosa Long Yes Died
## 369 Moderate Serosa Short No Died
## 370 Moderate Serosa Long Yes Died
## 371 Moderate Muscle Long No Alive
## 372 Moderate Serosa Long Yes Alive
## 373 Well Muscle Short No Alive
## 374 Moderate Adjacent structures Short No Died
## 375 Poor Serosa Long No Alive
## 376 Moderate Serosa Short No Alive
## 377 Poor Serosa Short No Alive
## 378 Poor Serosa Short No Died
## 379 Well Serosa Long No Alive
## 380 Moderate Serosa Short No Died
## 381 Moderate Muscle Short No Alive
## 382 Moderate Serosa Short Yes Alive
## 383 Moderate Serosa Short Yes Died
## 384 Moderate Serosa Long No Died
## 385 Moderate Serosa Short No Alive
## 386 Moderate Serosa Short Yes Died
## 387 Poor Serosa Short Yes Died
## 388 Poor Serosa Long Yes Died
## 389 Moderate Serosa Long No Died
## 390 Moderate Serosa Short No Died
## 391 Moderate Serosa Short No Died
## 392 Moderate Serosa Short No Alive
## 393 Moderate Serosa Short No Alive
## 394 Poor Serosa Short Yes Died
## 395 Moderate Serosa Short No Alive
## 396 Moderate Serosa Short Yes Died
## 397 Moderate Serosa Long No Alive
## 398 Moderate Serosa Long No Alive
## 399 Moderate Serosa Short Yes Alive
## 400 Moderate Serosa Short No Alive
## 401 Moderate Serosa Short No Alive
## 402 Moderate Serosa Short Yes Died
## 403 Moderate Muscle <NA> Yes Died
## 404 Moderate Serosa Short Yes Alive
## 405 Well Muscle Long Yes Alive
## 406 Moderate Serosa Short No Died
## 407 Well Serosa Short No Alive
## 408 Moderate Serosa Short Yes Alive
## 409 Moderate Serosa Short No Alive
## 410 Moderate Serosa Short No Alive
## 411 Moderate Muscle Short No Died
## 412 Moderate Serosa Short No Alive
## 413 Moderate Serosa Long No Alive
## 414 Well Serosa Short No Died
## 415 Well Serosa Short No Alive
## 416 Moderate Adjacent structures Short No Died
## 417 Moderate Muscle Short No Alive
## 418 Moderate Serosa Short Yes Alive
## 419 Moderate Serosa Short No Died
## 420 Moderate Serosa Short No Died
## 421 Well Serosa Short No Died
## 422 Well Serosa Short Yes Died
## 423 Well Serosa Short Yes Alive
## 424 Moderate Serosa Long No Died
## 425 Well Serosa Short No Alive
## 426 Moderate Muscle Long Yes Died
## 427 Moderate Serosa Short No Died
## 428 Moderate Serosa Short No Alive
## 429 Moderate Serosa Short Yes Died
## 430 <NA> Serosa Short Yes Died
## 431 Moderate Serosa Long No Died
## 432 Well Serosa Short No Alive
## 433 Well Serosa Short No Died
## 434 Moderate Serosa Long Yes Died
## 435 Moderate Serosa Long No Alive
## 436 Moderate Serosa Short No Died
## 437 Moderate Serosa Short No Alive
## 438 Moderate Adjacent structures Short Yes Died
## 439 Well Serosa Short No Died
## 440 Moderate Serosa Short No Alive
## 441 Moderate Adjacent structures Short No Died
## 442 Moderate Serosa Short Yes Died
## 443 Well Serosa Short No Alive
## 444 Moderate Serosa <NA> No Alive
## 445 Moderate Serosa Short Yes Died
## 446 Well Muscle Long No Died
## 447 Moderate Serosa Short No Died
## 448 Poor Serosa Short No Alive
## 449 Moderate Serosa Long No Alive
## 450 Moderate Serosa Short No Died
## 451 Well Serosa Short No Alive
## 452 Moderate Serosa Short Yes Alive
## 453 Moderate Muscle Short No Alive
## 454 Moderate Adjacent structures Short No Alive
## 455 Moderate Serosa Long No Died
## 456 Moderate Serosa Long No Died
## 457 Poor Serosa Short Yes Died
## 458 Well Serosa Long No Alive
## 459 Moderate Serosa Short No Died
## 460 Moderate Serosa Short No Alive
## 461 Well Muscle Short No Alive
## 462 Moderate Serosa Short No Alive
## 463 Poor Serosa Long No Died
## 464 Moderate Serosa Short No Died
## 465 Poor Adjacent structures Short No Died
## 466 Moderate Serosa Short No Alive
## 467 Moderate Serosa Long No Alive
## 468 Well Serosa Short No Died
## 469 Moderate Serosa Short No Alive
## 470 Moderate Adjacent structures Short No Alive
## 471 Moderate Submucosa Short No Alive
## 472 Poor Muscle Short Yes Died
## 473 Poor Serosa Short Yes Died
## 474 Moderate Serosa Short No Died
## 475 Moderate Serosa Long Yes Died
## 476 Poor Muscle Long Yes Died
## 477 Moderate Serosa Short Yes Died
## 478 Moderate Serosa Short No Died
## 479 Moderate Serosa Short No Alive
## 480 Poor Serosa Long No Alive
## 481 Moderate Serosa Short No Died
## 482 Poor Serosa Short Yes Died
## 483 Moderate Serosa Long No Died
## 484 Moderate Serosa Long Yes Died
## 485 Moderate Serosa Short No Alive
## 486 Moderate Serosa Short Yes Died
## 487 Moderate Serosa Short Yes Died
## 488 Poor Serosa Short Yes Died
## 489 Moderate Serosa Short Yes Died
## 490 Moderate Serosa Short No Alive
## 491 Poor Serosa Short No Alive
## 492 Moderate Serosa Short No Alive
## 493 Moderate Serosa Long No Alive
## 494 Poor Muscle Short No Alive
## 495 Moderate Muscle Short No Died
## 496 Moderate Serosa Short No Died
## 497 Moderate Serosa Short No Died
## 498 Moderate Serosa Short No Died
## 499 Moderate Serosa Long No Died
## 500 <NA> Serosa Short No Alive
## 501 Moderate Serosa Short No Alive
## 502 Moderate Serosa Short Yes Died
## 503 Poor Muscle Long Yes Alive
## 504 Moderate Serosa Short No Died
## 505 Poor Muscle Short No Alive
## 506 <NA> Serosa Short No Alive
## 507 Poor Serosa Short Yes Died
## 508 Well Serosa Short No Alive
## 509 Moderate Serosa Short No Died
## 510 Moderate Serosa Short No Alive
## 511 Moderate Serosa Short No Died
## 512 Moderate Muscle Short No Alive
## 513 Moderate Serosa Long No Alive
## 514 Poor Serosa Short No Alive
## 515 Moderate Serosa Short No Alive
## 516 Poor Serosa Short Yes Died
## 517 Moderate Muscle Long No Died
## 518 Moderate Serosa Short No Alive
## 519 Moderate Serosa Short No Alive
## 520 Moderate Serosa Short No Alive
## 521 Moderate Serosa Short No Died
## 522 Moderate Serosa Short Yes Alive
## 523 Poor Adjacent structures Short Yes Alive
## 524 Moderate Serosa Short No Alive
## 525 Moderate Adjacent structures Short No Alive
## 526 Moderate Serosa Short No Alive
## 527 Moderate Serosa Short No Alive
## 528 Poor Serosa Short No Died
## 529 Moderate Serosa Short No Died
## 530 Well Serosa Short Yes Died
## 531 Moderate Serosa Short Yes Alive
## 532 Poor Serosa Short No Alive
## 533 Moderate Muscle Short No Alive
## 534 Moderate Serosa Long Yes Died
## 535 Moderate Muscle Short No Alive
## 536 Well Submucosa Short No Died
## 537 Moderate Serosa Long No Alive
## 538 Moderate Serosa Long No Died
## 539 Moderate Serosa Short No Alive
## 540 Moderate Serosa Short Yes Alive
## 541 Moderate Serosa Short Yes Alive
## 542 Moderate Serosa Long No Alive
## 543 Poor Serosa Short Yes Alive
## 544 Moderate Serosa Short Yes Died
## 545 Moderate Serosa Long No Alive
## 546 Moderate Serosa Short No Alive
## 547 Moderate Serosa Short No Alive
## 548 Moderate Serosa Short No Died
## 549 Poor Serosa Short Yes Died
## 550 Moderate Serosa Short No Alive
## 551 Well Serosa Short No Alive
## 552 Moderate Serosa Long Yes Alive
## 553 Moderate Serosa Long Yes Alive
## 554 Moderate Serosa Short No Died
## 555 Moderate Serosa Short No Died
## 556 Poor Serosa Short Yes Died
## 557 Poor Serosa Long Yes Died
## 558 Moderate Serosa Short Yes Died
## 559 Moderate Muscle Short No Died
## 560 Poor Serosa Short Yes Alive
## 561 Moderate Serosa Short Yes Alive
## 562 Poor Serosa Short No Alive
## 563 Moderate Serosa Short No Alive
## 564 Moderate Serosa Long No Alive
## 565 Well Serosa Long No Died
## 566 Moderate Serosa Short No Alive
## 567 Moderate Adjacent structures Short Yes Died
## 568 Moderate Serosa Short No Alive
## 569 Moderate Serosa Short No Alive
## 570 Moderate Muscle Short No Alive
## 571 Moderate Serosa Short No Alive
## 572 Moderate Serosa Short No Died
## 573 <NA> Adjacent structures Short No Died
## 574 Moderate Serosa Long No Died
## 575 Well Serosa Long No Alive
## 576 Moderate Serosa Short Yes Died
## 577 Moderate Serosa Long No Died
## 578 Moderate Serosa Long No Died
## 579 Moderate Serosa <NA> No Died
## 580 Moderate Serosa Short No Alive
## 581 Moderate Adjacent structures Long No Died
## 582 Moderate Submucosa Long No Alive
## 583 Moderate Serosa Long No Died
## 584 Poor Serosa Short Yes Died
## 585 Moderate Serosa Short No Alive
## 586 Poor Serosa <NA> Yes Alive
## 587 Moderate Serosa Short No Died
## 588 Well Serosa Short No Died
## 589 Poor Serosa Short No Alive
## 590 Moderate Serosa Long Yes Died
## 591 Moderate Serosa Short No Died
## 592 Moderate Serosa Short No Alive
## 593 Moderate Serosa Short No Died
## 594 Moderate Serosa Short No Alive
## 595 Moderate Serosa Long No Alive
## 596 Moderate Serosa Short No Alive
## 597 Well Muscle Short Yes Alive
## 598 Moderate Serosa Long No Alive
## 599 Moderate Serosa Short No Alive
## 600 Moderate Serosa Short Yes Alive
## 601 Moderate Serosa Long No Died
## 602 Moderate Serosa Short Yes Alive
## 603 Moderate Muscle Long Yes Alive
## 604 Moderate Serosa Short No Alive
## 605 Poor Serosa Long No Alive
## 606 Moderate Serosa Short Yes Died
## 607 Poor Serosa Short No Alive
## 608 Moderate Serosa Short No Died
## 609 Poor Submucosa Long Yes Died
## 610 Moderate Serosa <NA> No Died
## 611 Moderate Serosa Short No Alive
## 612 Moderate Serosa Long No Died
## 613 Moderate Serosa Short No Died
## 614 Moderate Serosa Short No Alive
## 615 Moderate Serosa Long No Died
## 616 Moderate Serosa Long Yes Died
## 617 Moderate Serosa Short Yes Alive
## 618 Moderate Serosa Short Yes Died
## 619 Poor Serosa Long Yes Died
## 620 Moderate Serosa Short No Alive
## 621 Moderate Serosa Long No Died
## 622 Moderate Serosa Short No Alive
## 623 Moderate Serosa Short No Alive
## 624 Moderate Serosa Short No Alive
## 625 Poor Serosa Long No Alive
## 626 Well Serosa Short No Alive
## 627 Well Serosa Short No Alive
## 628 <NA> Serosa Short No Alive
## 629 Moderate Muscle Short Yes Died
## 630 Poor Adjacent structures Short No Alive
## 631 Poor Serosa Short Yes Died
## 632 Well Serosa <NA> No Died
## 633 Moderate Serosa Long No Alive
## 634 Moderate Serosa Short No Alive
## 635 Poor Serosa Short No Alive
## 636 Well Serosa Short Yes Alive
## 637 Moderate Serosa Short No Died
## 638 Moderate Serosa Short No Alive
## 639 Poor Serosa Short No Died
## 640 Moderate Muscle Short No Alive
## 641 Moderate Serosa Short Yes Died
## 642 Poor Serosa Short No Died
## 643 Poor Serosa Long No Alive
## 644 Moderate Serosa Short Yes Died
## 645 <NA> Adjacent structures <NA> No Died
## 646 Moderate Muscle Short No Alive
## 647 Well Serosa Short No Died
## 648 Moderate Serosa Short No Died
## 649 Moderate Serosa Short Yes Died
## 650 Moderate Serosa Long Yes Died
## 651 Moderate Serosa Short No Alive
## 652 Moderate Serosa Short No Died
## 653 Moderate Serosa Short No Died
## 654 Moderate Serosa Long No Alive
## 655 Moderate Serosa Short No Died
## 656 Moderate Serosa Short No Died
## 657 Poor Serosa Short No Died
## 658 Well Muscle Long No Alive
## 659 Moderate Serosa Long No Died
## 660 Moderate Serosa Short No Alive
## 661 Moderate Serosa Long No Alive
## 662 Poor Serosa Long No Alive
## 663 Poor Muscle Short No Alive
## 664 Moderate Serosa Short No Alive
## 665 Moderate Muscle Short No Alive
## 666 Moderate Serosa Short No Died
## 667 Moderate Serosa Short Yes Alive
## 668 Poor Serosa Long No Died
## 669 Moderate Serosa Short No Died
## 670 Well Serosa Long No Died
## 671 Poor Serosa Long No Died
## 672 <NA> Muscle Short No Alive
## 673 Moderate Muscle Short Yes Alive
## 674 Moderate Muscle Short No Alive
## 675 Moderate Serosa Short No Alive
## 676 Well Serosa Short No Alive
## 677 Moderate Adjacent structures Short No Alive
## 678 Moderate Serosa Long Yes Died
## 679 Moderate Muscle Long No Alive
## 680 Moderate Serosa Short No Alive
## 681 Moderate Muscle Short No Alive
## 682 Moderate Submucosa Short No Alive
## 683 Moderate Serosa Short No Alive
## 684 Moderate Serosa Long No Died
## 685 Moderate Serosa Short No Alive
## 686 Poor Serosa Short Yes Died
## 687 Moderate Serosa Short No Died
## 688 Moderate Serosa Short No Alive
## 689 Poor Serosa Long No Died
## 690 Moderate Serosa Long No Died
## 691 Moderate Serosa Short Yes Died
## 692 Well Serosa Long No Alive
## 693 <NA> Adjacent structures Short No Died
## 694 Poor Adjacent structures Long No Died
## 695 Moderate Serosa Long No Alive
## 696 Moderate Adjacent structures Short No Died
## 697 Moderate Serosa Short No Died
## 698 Moderate Serosa Long No Died
## 699 Moderate Serosa Short No Alive
## 700 Well Serosa Long No Alive
## 701 Moderate Serosa Short No Alive
## 702 Moderate Serosa Short No Alive
## 703 Moderate Serosa Short No Alive
## 704 Moderate Serosa Long Yes Died
## 705 Moderate Serosa Short No Alive
## 706 Moderate Serosa Short Yes Alive
## 707 Moderate Serosa Short No Alive
## 708 Moderate Serosa Short No Alive
## 709 Well Submucosa Short No Died
## 710 Well Serosa Short No Died
## 711 Moderate Serosa Long No Died
## 712 Moderate Serosa Long No Alive
## 713 Moderate Serosa <NA> No Died
## 714 Poor Serosa Short No Alive
## 715 Moderate Serosa Short No Alive
## 716 Moderate Serosa Long Yes Alive
## 717 Moderate Serosa Long No Died
## 718 Moderate Muscle Short No Alive
## 719 Moderate Serosa Short No Alive
## 720 Moderate Serosa Short No Alive
## 721 Moderate Serosa Short Yes Alive
## 722 Moderate Muscle Short No Alive
## 723 Moderate Adjacent structures Short No Died
## 724 Moderate Serosa Short No Died
## 725 Moderate Serosa Short No Died
## 726 Well Serosa Short Yes Died
## 727 Moderate Serosa Short No Alive
## 728 Well Muscle Short No Died
## 729 Moderate Muscle Long No Alive
## 730 Poor Serosa Short Yes Died
## 731 Poor Serosa Short No Alive
## 732 Moderate Serosa Short No Alive
## 733 Poor Serosa Long No Alive
## 734 Moderate Serosa Short No Alive
## 735 Moderate Serosa Short Yes Alive
## 736 Moderate Serosa Short Yes Alive
## 737 Poor Serosa Short No Alive
## 738 <NA> Serosa Short No Alive
## 739 Moderate Serosa Short Yes Died
## 740 Moderate Muscle Short No Alive
## 741 Moderate Serosa Short Yes Alive
## 742 Moderate Adjacent structures Short Yes Died
## 743 Moderate Serosa Long No Died
## 744 Moderate Serosa Short No Alive
## 745 Moderate Muscle Short No Alive
## 746 Moderate Muscle Short No Alive
## 747 Moderate Serosa Long No Alive
## 748 Moderate Serosa Short Yes Died
## 749 Moderate Serosa Short No Alive
## 750 Moderate Serosa Long No Alive
## 751 Poor Serosa Long No Died
## 752 Moderate Serosa Short No Alive
## 753 Moderate Muscle Long No Alive
## 754 Moderate Muscle Short No Alive
## 755 Moderate Serosa Short Yes Died
## 756 Poor Serosa Short Yes Died
## 757 Moderate Serosa <NA> No Alive
## 758 Moderate Serosa Long Yes Died
## 759 Moderate Serosa Short No Alive
## 760 Poor Serosa Short Yes Alive
## 761 Moderate Serosa Short No Alive
## 762 Moderate Adjacent structures Short No Died
## 763 Well Serosa Long No Died
## 764 Moderate Serosa Long Yes Died
## 765 Poor Serosa Short No Alive
## 766 Moderate Serosa Short Yes Died
## 767 Well Muscle Short No Died
## 768 Moderate Serosa Short No Alive
## 769 Moderate Serosa <NA> No Alive
## 770 Poor Serosa Short Yes Alive
## 771 Poor Serosa Long Yes Died
## 772 Moderate Serosa Short No Alive
## 773 Moderate Serosa Short No Died
## 774 Moderate Serosa Short No Alive
## 775 Well Serosa Short No Alive
## 776 Well Serosa Short Yes Died
## 777 Poor Serosa Short Yes Died
## 778 Poor Muscle Short Yes Died
## 779 Poor Serosa Long Yes Alive
## 780 Moderate Serosa Short No Alive
## 781 Moderate Adjacent structures Short Yes Died
## 782 Poor Serosa Long No Died
## 783 Well Serosa Short No Died
## 784 Moderate Serosa Short No Died
## 785 Poor Serosa Long No Alive
## 786 Moderate Serosa Short No Alive
## 787 Moderate Serosa Short Yes Died
## 788 Moderate Submucosa Short No Alive
## 789 Poor Serosa Long No Died
## 790 Moderate Serosa Short Yes Died
## 791 Moderate Serosa Short No Died
## 792 Moderate Serosa Short No Alive
## 793 Moderate Serosa Long No Alive
## 794 Moderate Serosa Short Yes Died
## 795 Moderate Muscle Short Yes Died
## 796 Well Serosa Short No Died
## 797 Moderate Serosa Long No Died
## 798 Moderate Serosa Short No Alive
## 799 Moderate Muscle Long No Alive
## 800 Moderate Serosa Short No Alive
## 801 Moderate Serosa Short Yes Died
## 802 Moderate Serosa Long No Died
## 803 Moderate Muscle Short Yes Died
## 804 Moderate Serosa Long Yes Alive
## 805 Moderate Serosa Long Yes Died
## 806 Moderate Serosa Long No Alive
## 807 Moderate Serosa Short No Alive
## 808 Moderate Serosa Short No Alive
## 809 Moderate Serosa Long Yes Died
## 810 Moderate Adjacent structures Short No Died
## 811 Moderate Muscle Long No Died
## 812 Moderate Serosa Short Yes Alive
## 813 Moderate Serosa Short Yes Died
## 814 Moderate Serosa Long No Alive
## 815 <NA> Submucosa Short No Alive
## 816 Poor Serosa Short Yes Died
## 817 Well Muscle Short Yes Died
## 818 Well Serosa Short No Alive
## 819 Well Serosa Long Yes Died
## 820 Moderate Serosa Short Yes Alive
## 821 Moderate Serosa Long No Died
## 822 Moderate Adjacent structures Long Yes Died
## 823 Moderate Serosa Short No Alive
## 824 Moderate Serosa Short No Alive
## 825 Moderate Serosa Short No Alive
## 826 Moderate Serosa Long Yes Died
## 827 Well Serosa Long No Died
## 828 Poor Serosa Short Yes Alive
## 829 Poor Serosa Short Yes Died
## 830 Moderate Serosa Short No Died
## 831 Moderate Muscle Short No Alive
## 832 Well Serosa Short No Alive
## 833 Poor Serosa Short Yes Died
## 834 Poor Serosa Short Yes Died
## 835 Moderate Serosa Long No Died
## 836 Moderate Serosa Short No Alive
## 837 Well Serosa Long No Died
## 838 Moderate Serosa Long No Died
## 839 Poor Serosa Long Yes Died
## 840 Moderate Serosa Short No Alive
## 841 Moderate Serosa Short No Alive
## 842 Moderate Muscle Long Yes Died
## 843 Poor Serosa Short No Died
## 844 Moderate Serosa Short No Alive
## 845 Moderate Serosa <NA> No Alive
## 846 Moderate Serosa Long No Alive
## 847 Moderate Serosa Short No Died
## 848 Poor Muscle Short No Alive
## 849 Moderate Serosa Short No Died
## 850 Moderate Serosa Short No Died
## 851 Moderate Serosa Short Yes Died
## 852 Moderate Serosa Short No Alive
## 853 Poor Muscle Short No Died
## 854 Moderate Serosa Short Yes Alive
## 855 Well Serosa Short No Alive
## 856 Moderate Muscle Short Yes Died
## 857 <NA> Muscle Short No Alive
## 858 Moderate Serosa Short No Died
## 859 Moderate Serosa Short No Alive
## 860 Well Serosa Short No Alive
## 861 Moderate Serosa Long Yes Died
## 862 Well Serosa Long No Died
## 863 Poor Muscle Short No Died
## 864 Moderate Serosa Short Yes Alive
## 865 Moderate Serosa Short No Died
## 866 Moderate Adjacent structures Short No Died
## 867 Moderate Serosa <NA> Yes Alive
## 868 Well Serosa Short No Died
## 869 Moderate Muscle Short No Alive
## 870 Moderate Serosa Short No Alive
## 871 Poor Serosa Short Yes Died
## 872 Moderate Submucosa Long No Alive
## 873 Moderate Serosa Short No Died
## 874 Moderate Serosa Short No Alive
## 875 Moderate Serosa Short Yes Died
## 876 Moderate Muscle Long No Died
## 877 Moderate Serosa Short No Alive
## 878 Moderate Muscle Short No Alive
## 879 Moderate Serosa Short No Alive
## 880 Moderate Serosa Short No Died
## 881 Poor Serosa Short No Alive
## 882 Moderate Serosa Short No Died
## 883 Moderate Serosa Short No Alive
## 884 Poor Serosa Short No Died
## 885 Moderate Muscle Long No Alive
## 886 Moderate Serosa Short No Alive
## 887 Moderate Serosa Short Yes Died
## 888 Moderate Serosa Long No Alive
## 889 Poor Serosa Short No Alive
## 890 Moderate Serosa Short Yes Died
## 891 Moderate Serosa Short Yes Died
## 892 Moderate Serosa Long No Alive
## 893 Moderate Serosa Short No Alive
## 894 Moderate Serosa Short No Died
## 895 Moderate Serosa Short Yes Alive
## 896 Poor Submucosa Long No Died
## 897 Moderate Serosa <NA> No Died
## 898 Moderate Serosa Short No Alive
## 899 Poor Adjacent structures Short No Alive
## 900 Moderate Serosa Short Yes Died
## 901 Moderate Serosa Short Yes Died
## 902 Poor Serosa Long No Died
## 903 Moderate Serosa Short No Alive
## 904 Well Serosa Short Yes Died
## 905 Well Serosa Long No Died
## 906 Moderate Serosa Short No Died
## 907 Poor Serosa Long Yes Died
## 908 Moderate Serosa Short No Alive
## 909 Moderate Serosa Short No Alive
## 910 Moderate Serosa Short Yes Died
## 911 Moderate Serosa Short Yes Died
## 912 Well Serosa Long No Alive
## 913 Moderate Serosa Short No Alive
## 914 Moderate Muscle Short No Died
## 915 Well Serosa Short Yes Alive
## 916 Moderate Serosa Long Yes Died
## 917 Poor Serosa Short Yes Died
## 918 Moderate Muscle Short Yes Died
## 919 Moderate Muscle Short No Died
## 920 Moderate Muscle Short Yes Alive
## 921 Moderate Adjacent structures Short No Died
## 922 Moderate Serosa Short No Died
## 923 Poor Serosa Short No Alive
## 924 Poor Serosa Short No Alive
## 925 Moderate Serosa Short No Alive
## 926 Moderate Serosa Short No Alive
## 927 Poor Serosa Short No Died
## 928 Moderate Serosa Long Yes Alive
## 929 Moderate Serosa Short No Alive
## age.factor loccomp loccomp.factor time.years mort_5yr age.10 mort_5yr.num
## 1 40-59 years NA <NA> 4.16712329 Died 4.3 2
## 2 60+ years 0 No 8.45753425 Alive 6.3 1
## 3 60+ years 1 Yes 2.63835616 Died 7.1 2
## 4 60+ years 1 Yes 0.80273973 Died 6.6 2
## 5 60+ years 0 No 1.80547945 Died 6.9 2
## 6 40-59 years 0 No 4.84109589 Died 5.7 2
## 7 60+ years 0 No 1.15068493 Died 7.7 2
## 8 40-59 years 0 No 8.74520548 Alive 5.4 1
## 9 40-59 years 1 Yes 8.69315068 Alive 4.6 1
## 10 60+ years 0 No 9.06301370 Alive 6.8 1
## 11 40-59 years 1 Yes 7.96712329 Alive 4.7 1
## 12 40-59 years 0 No 9.06575342 Alive 5.2 1
## 13 60+ years 0 No 5.71232877 Alive 6.4 1
## 14 60+ years 1 Yes 7.97260274 Alive 6.8 1
## 15 40-59 years 1 Yes 7.54520548 Alive 4.6 1
## 16 60+ years 0 No 8.80547945 Alive 6.8 1
## 17 60+ years 1 Yes 1.11232877 Died 6.2 2
## 18 60+ years 1 Yes 1.43013699 Died 7.9 2
## 19 <40 years 1 Yes 2.43013699 Died 3.4 2
## 20 40-59 years 1 Yes 9.12054795 Alive 5.0 1
## 21 60+ years NA <NA> 7.64109589 Alive 6.4 1
## 22 40-59 years 1 Yes 2.02465753 Died 5.6 2
## 23 60+ years 0 No 1.94246575 Died 6.1 2
## 24 40-59 years 0 No 8.13424658 Alive 5.0 1
## 25 60+ years 0 No 7.91506849 Alive 7.0 1
## 26 60+ years 0 No 4.85479452 Died 7.3 2
## 27 60+ years 1 Yes 1.05205479 Died 7.0 2
## 28 60+ years 0 No 2.65205479 Died 6.8 2
## 29 40-59 years 1 Yes 0.59726027 Died 5.6 2
## 30 60+ years 0 No 0.36438356 Died 8.0 2
## 31 60+ years 0 No 8.87123288 Alive 6.4 1
## 32 <40 years 1 Yes 8.27123288 Alive 3.3 1
## 33 40-59 years 0 No 4.78082192 Died 4.9 2
## 34 40-59 years 0 No 6.92328767 Alive 4.7 1
## 35 40-59 years 0 No 3.80000000 Died 5.6 2
## 36 60+ years 1 Yes 8.28493151 Alive 7.2 1
## 37 60+ years 0 No 1.56164384 Died 7.9 2
## 38 60+ years 0 No 7.71232877 Alive 6.4 1
## 39 60+ years 0 No 7.94794521 Alive 6.1 1
## 40 40-59 years 0 No 1.51506849 Died 5.8 2
## 41 60+ years 0 No 2.47945205 Died 7.5 2
## 42 <40 years 1 Yes 8.30136986 Alive 3.9 1
## 43 60+ years 1 Yes 1.87671233 Died 7.1 2
## 44 40-59 years 1 Yes 7.50684932 Alive 5.8 1
## 45 40-59 years 0 No 7.94246575 Alive 4.0 1
## 46 60+ years 1 Yes 7.11780822 Alive 6.3 1
## 47 40-59 years 0 No 7.78082192 Alive 5.9 1
## 48 40-59 years 1 Yes 7.67671233 Alive 5.9 1
## 49 40-59 years 0 No 7.61917808 Alive 5.9 1
## 50 60+ years 0 No 2.28219178 Died 6.0 2
## 51 60+ years 0 No 3.53424658 Died 6.8 2
## 52 60+ years 0 No 4.43835616 Died 7.0 2
## 53 60+ years 0 No 7.57534247 Alive 7.6 1
## 54 40-59 years 0 No 7.41917808 Alive 4.5 1
## 55 60+ years 0 No 7.49863014 Alive 6.1 1
## 56 60+ years 0 No 3.22739726 Died 7.6 2
## 57 40-59 years 0 No 7.57534247 Alive 5.3 1
## 58 60+ years 0 No 7.89863014 Alive 6.3 1
## 59 60+ years 0 No 7.33972603 Alive 6.5 1
## 60 40-59 years 1 Yes 8.01369863 Alive 5.7 1
## 61 60+ years 1 Yes 1.29315068 Died 8.0 2
## 62 40-59 years 0 No 7.59452055 Alive 5.8 1
## 63 40-59 years 0 No 1.29863014 Died 5.3 2
## 64 40-59 years 1 Yes 7.50410959 Alive 5.3 1
## 65 60+ years 0 No 1.00000000 Died 7.1 2
## 66 60+ years 0 No 7.26849315 Alive 6.6 1
## 67 40-59 years 0 No 7.46849315 Alive 4.9 1
## 68 60+ years 0 No 2.12054795 Died 6.0 2
## 69 60+ years 0 No 8.43287671 Alive 7.0 1
## 70 40-59 years 0 No 5.84383562 Alive 4.0 1
## 71 40-59 years 0 No 5.82739726 Alive 5.5 1
## 72 40-59 years 0 No 1.09589041 Died 5.6 2
## 73 40-59 years 0 No 8.72602740 Alive 5.4 1
## 74 40-59 years 1 Yes 3.38904110 Died 4.9 2
## 75 60+ years 0 No 3.33972603 Died 7.1 2
## 76 60+ years 0 No 8.26575342 Alive 6.7 1
## 77 60+ years 0 No 2.20821918 Died 6.8 2
## 78 60+ years 0 No 8.17808219 Alive 6.3 1
## 79 40-59 years 1 Yes 8.13424658 Alive 5.0 1
## 80 40-59 years 0 No 5.46575342 Alive 4.5 1
## 81 60+ years 0 No 8.10410959 Alive 6.6 1
## 82 40-59 years 0 No 3.10410959 Died 4.6 2
## 83 60+ years 0 No 4.24109589 Died 7.0 2
## 84 60+ years 1 Yes 8.45205479 Alive 6.3 1
## 85 40-59 years 0 No 2.01643836 Died 4.5 2
## 86 40-59 years 0 No 7.64109589 Alive 4.9 1
## 87 60+ years 0 No 9.10958904 Alive 6.2 1
## 88 40-59 years 0 No 1.04383562 Died 5.9 2
## 89 60+ years NA <NA> 7.46301370 Alive 8.0 1
## 90 60+ years 1 Yes 2.73150685 Died 7.3 2
## 91 40-59 years 0 No 1.13150685 Died 4.6 2
## 92 60+ years 0 No 1.93972603 Died 6.4 2
## 93 40-59 years 0 No 7.57534247 Alive 4.5 1
## 94 <40 years 1 Yes 7.86027397 Alive 2.6 1
## 95 60+ years NA <NA> 7.99452055 Alive 6.6 1
## 96 60+ years 1 Yes 6.73424658 Alive 6.7 1
## 97 60+ years 0 No 1.25753425 Died 6.5 2
## 98 60+ years 1 Yes 6.35068493 Alive 7.4 1
## 99 60+ years 1 Yes 1.55890411 Died 7.1 2
## 100 40-59 years 1 Yes 5.69041096 Alive 5.8 1
## 101 40-59 years 0 No 3.33150685 Died 5.9 2
## 102 60+ years NA <NA> 0.46849315 Died 6.1 2
## 103 40-59 years 0 No 1.95068493 Died 4.9 2
## 104 40-59 years 0 No 1.68219178 Died 5.0 2
## 105 60+ years 0 No 7.80547945 Alive 7.5 1
## 106 60+ years 0 No 4.19178082 Died 6.8 2
## 107 60+ years 1 Yes 1.10136986 Died 6.0 2
## 108 60+ years 1 Yes 4.13972603 Died 6.5 2
## 109 60+ years 0 No 7.74794521 Alive 7.4 1
## 110 40-59 years 0 No 0.06301370 Died 5.2 2
## 111 60+ years 1 Yes 8.05753425 Alive 6.4 1
## 112 40-59 years 1 Yes 2.06849315 Died 4.7 2
## 113 40-59 years 0 No 7.71232877 Alive 4.5 1
## 114 60+ years 1 Yes 2.08493151 Died 6.1 2
## 115 40-59 years 0 No 5.03835616 Alive 5.3 1
## 116 60+ years 1 Yes 6.44109589 Alive 6.0 1
## 117 60+ years 0 No 7.56164384 Alive 6.0 1
## 118 40-59 years 0 No 8.08493151 Alive 5.1 1
## 119 60+ years 1 Yes 7.72602740 Alive 6.0 1
## 120 60+ years 0 No 3.63561644 Died 6.4 2
## 121 40-59 years 0 No 7.33698630 Alive 5.2 1
## 122 60+ years 0 No 0.61917808 Died 6.5 2
## 123 60+ years 0 No 7.98082192 Alive 7.0 1
## 124 40-59 years 0 No 7.84109589 Alive 5.5 1
## 125 60+ years 0 No 1.24383562 Died 7.1 2
## 126 <40 years 0 No 7.51506849 Alive 3.0 1
## 127 40-59 years 0 No 4.60000000 Died 4.0 2
## 128 <40 years 1 Yes 2.53150685 Died 3.1 2
## 129 40-59 years 0 No 1.97534247 Died 5.3 2
## 130 60+ years 0 No 1.94246575 Died 6.7 2
## 131 40-59 years 0 No 2.63287671 Died 5.8 2
## 132 60+ years 1 Yes 0.89315068 Died 7.9 2
## 133 40-59 years 0 No 7.40547945 Alive 5.5 1
## 134 60+ years 1 Yes 0.79178082 Died 6.3 2
## 135 40-59 years 1 Yes 7.95890411 Alive 5.5 1
## 136 40-59 years 1 Yes 0.56438356 Died 4.2 2
## 137 40-59 years 0 No 7.17260274 Alive 5.6 1
## 138 60+ years 0 No 0.77534247 Died 6.4 2
## 139 40-59 years 1 Yes 7.44657534 Alive 5.5 1
## 140 <40 years 1 Yes 7.74246575 Alive 2.5 1
## 141 40-59 years 0 No 7.98904110 Alive 5.9 1
## 142 <40 years 0 No 1.36712329 Died 2.8 2
## 143 40-59 years 0 No 8.08219178 Alive 4.9 1
## 144 40-59 years 0 No 7.94246575 Alive 5.2 1
## 145 60+ years 0 No 1.84383562 Died 6.4 2
## 146 <40 years 1 Yes 8.21917808 Alive 3.3 1
## 147 60+ years 0 No 6.25753425 Alive 7.6 1
## 148 <40 years 0 No 0.99178082 Died 3.8 2
## 149 40-59 years 1 Yes 5.89589041 Alive 5.3 1
## 150 60+ years 1 Yes 7.01917808 Alive 7.2 1
## 151 40-59 years 0 No 7.47945205 Alive 4.6 1
## 152 60+ years 0 No 2.19726027 Died 6.9 2
## 153 40-59 years 1 Yes 3.19452055 Died 4.3 2
## 154 60+ years 1 Yes 3.26849315 Died 7.2 2
## 155 60+ years 1 Yes 0.12328767 Died 7.3 2
## 156 60+ years 0 No 7.06027397 Alive 6.8 1
## 157 40-59 years 1 Yes 3.11232877 Died 5.2 2
## 158 60+ years 1 Yes 6.84109589 Alive 7.3 1
## 159 60+ years 1 Yes 7.25479452 Alive 6.6 1
## 160 60+ years 0 No 6.73424658 Alive 7.5 1
## 161 40-59 years 1 Yes 3.10958904 Died 4.3 2
## 162 40-59 years 0 No 1.58904110 Died 5.7 2
## 163 60+ years 1 Yes 1.32876712 Died 7.4 2
## 164 60+ years 0 No 7.27671233 Alive 6.7 1
## 165 60+ years 1 Yes 2.20821918 Died 6.6 2
## 166 40-59 years 1 Yes 6.67123288 Alive 5.7 1
## 167 60+ years 0 No 3.94246575 Died 8.1 2
## 168 40-59 years 0 No 1.96438356 Died 5.0 2
## 169 60+ years 1 Yes 7.03561644 Alive 6.2 1
## 170 40-59 years 0 No 7.20821918 Alive 4.8 1
## 171 40-59 years 0 No 4.03835616 <NA> 4.5 NA
## 172 40-59 years 1 Yes 7.10410959 Alive 4.6 1
## 173 60+ years 0 No 4.24657534 Died 7.2 2
## 174 40-59 years 0 No 1.83561644 Died 5.5 2
## 175 60+ years 1 Yes 1.17808219 Died 6.7 2
## 176 40-59 years 0 No 7.72876712 Alive 4.1 1
## 177 40-59 years 0 No 7.32054795 Alive 5.6 1
## 178 40-59 years 0 No 7.39452055 Alive 5.0 1
## 179 60+ years 0 No 8.01917808 Alive 6.5 1
## 180 60+ years 1 Yes 2.72054795 Died 7.4 2
## 181 60+ years 0 No 7.06849315 Alive 7.4 1
## 182 40-59 years 0 No 7.18082192 Alive 5.8 1
## 183 40-59 years 0 No 7.61369863 Alive 5.6 1
## 184 60+ years 0 No 7.65479452 Alive 7.5 1
## 185 60+ years 0 No 7.27671233 Alive 6.7 1
## 186 40-59 years 0 No 6.88493151 Alive 5.8 1
## 187 40-59 years 0 No 6.81643836 Alive 5.8 1
## 188 40-59 years 0 No 3.04657534 Died 4.1 2
## 189 60+ years 0 No 7.17260274 Alive 7.2 1
## 190 40-59 years 1 Yes 2.17808219 Died 4.8 2
## 191 60+ years 0 No 0.99452055 Died 6.9 2
## 192 40-59 years 1 Yes 2.60000000 Died 5.7 2
## 193 40-59 years 1 Yes 0.34794521 Died 4.5 2
## 194 60+ years 0 No 7.86575342 Alive 7.6 1
## 195 40-59 years 1 Yes 7.00821918 Alive 5.9 1
## 196 60+ years 0 No 5.70684932 Alive 6.6 1
## 197 60+ years 0 No 7.52602740 Alive 6.5 1
## 198 60+ years 0 No 3.02739726 Died 6.9 2
## 199 <40 years 0 No 1.34246575 Died 3.2 2
## 200 40-59 years 0 No 6.86849315 Alive 5.6 1
## 201 60+ years 0 No 2.63287671 Died 7.1 2
## 202 60+ years 0 No 5.14794521 Alive 7.5 1
## 203 40-59 years 0 No 7.10136986 Alive 5.8 1
## 204 40-59 years 0 No 6.99178082 Alive 4.0 1
## 205 <40 years 0 No 6.77808219 Alive 3.9 1
## 206 40-59 years 0 No 6.43561644 Alive 4.2 1
## 207 40-59 years 0 No 7.76712329 Alive 5.3 1
## 208 40-59 years 0 No 7.56438356 Alive 4.3 1
## 209 40-59 years 0 No 1.12602740 Died 5.1 2
## 210 60+ years 0 No 7.45205479 Alive 7.7 1
## 211 60+ years 1 Yes 6.83561644 Alive 6.7 1
## 212 40-59 years 0 No 1.26575342 Died 4.1 2
## 213 60+ years 1 Yes 6.84109589 Alive 6.3 1
## 214 60+ years 1 Yes 6.41917808 Alive 6.3 1
## 215 60+ years 0 No 7.20547945 Alive 6.3 1
## 216 40-59 years 1 Yes 6.74246575 Alive 5.8 1
## 217 60+ years 0 No 7.52602740 Alive 6.7 1
## 218 40-59 years 1 Yes 6.80000000 Alive 5.5 1
## 219 60+ years 1 Yes 1.58904110 Died 6.3 2
## 220 60+ years 1 Yes 3.32876712 Died 7.7 2
## 221 40-59 years 1 Yes 6.91780822 Alive 4.3 1
## 222 60+ years 0 No 7.78630137 Alive 7.8 1
## 223 40-59 years 1 Yes 3.48493151 Died 5.1 2
## 224 60+ years 1 Yes 1.20000000 Died 6.7 2
## 225 60+ years 0 No 6.63835616 Alive 6.6 1
## 226 60+ years 1 Yes 1.64109589 Died 6.4 2
## 227 60+ years 1 Yes 7.41369863 Alive 7.5 1
## 228 40-59 years 0 No 7.35068493 Alive 5.3 1
## 229 40-59 years 1 Yes 7.46027397 Alive 4.8 1
## 230 40-59 years 1 Yes 3.36986301 Died 5.9 2
## 231 60+ years 0 No 7.48219178 Alive 6.0 1
## 232 40-59 years 0 No 6.33698630 Alive 4.2 1
## 233 60+ years 0 No 6.80547945 Alive 6.0 1
## 234 40-59 years NA <NA> 7.54520548 Alive 5.8 1
## 235 40-59 years NA <NA> 7.46575342 Alive 5.9 1
## 236 60+ years 0 No 3.54794521 Died 7.0 2
## 237 60+ years 0 No 6.86575342 Alive 7.5 1
## 238 60+ years 0 No 7.43287671 Alive 7.3 1
## 239 60+ years 0 No 7.38356164 Alive 7.6 1
## 240 60+ years 0 No 3.49589041 Died 6.8 2
## 241 60+ years 0 No 7.12328767 Alive 6.1 1
## 242 60+ years NA <NA> 6.44383562 Alive 7.6 1
## 243 40-59 years 1 Yes 7.60273973 Alive 5.6 1
## 244 40-59 years 1 Yes 6.69041096 Alive 5.5 1
## 245 60+ years 1 Yes 1.19726027 Died 6.0 2
## 246 60+ years 0 No 4.68219178 Died 7.2 2
## 247 60+ years 1 Yes 4.40273973 Died 7.4 2
## 248 60+ years 0 No 4.48493151 Died 6.2 2
## 249 60+ years 0 No 3.06027397 Died 7.6 2
## 250 60+ years 0 No 7.48493151 Alive 7.2 1
## 251 40-59 years 0 No 0.60821918 Died 5.7 2
## 252 <40 years 0 No 7.36438356 Alive 3.9 1
## 253 60+ years 0 No 6.90410959 Alive 6.1 1
## 254 60+ years 0 No 1.63013699 Died 6.2 2
## 255 60+ years 0 No 0.93972603 Died 7.0 2
## 256 60+ years 0 No 2.39452055 Died 7.0 2
## 257 40-59 years 1 Yes 0.63561644 Died 5.7 2
## 258 60+ years 0 No 7.00821918 Alive 6.5 1
## 259 60+ years 0 No 7.42739726 Alive 6.5 1
## 260 60+ years 0 No 0.30958904 Died 7.1 2
## 261 60+ years 1 Yes 1.76164384 Died 7.0 2
## 262 <40 years 0 No 6.61095890 Alive 3.6 1
## 263 40-59 years 0 No 6.87397260 Alive 4.8 1
## 264 40-59 years 0 No 6.45479452 Alive 5.3 1
## 265 40-59 years 0 No 3.50410959 Died 5.4 2
## 266 40-59 years 0 No 2.56986301 Died 5.8 2
## 267 60+ years 0 No 7.56438356 Alive 6.7 1
## 268 40-59 years 1 Yes 6.53698630 Alive 5.9 1
## 269 60+ years 1 Yes 1.18630137 Died 6.7 2
## 270 60+ years 1 Yes 6.69863014 Alive 6.0 1
## 271 60+ years 0 No 6.24657534 Alive 7.0 1
## 272 60+ years 0 No 0.85205479 Died 7.6 2
## 273 60+ years 1 Yes 2.67671233 Died 6.0 2
## 274 60+ years 1 Yes 2.28219178 Died 6.7 2
## 275 40-59 years 0 No 1.59452055 Died 5.3 2
## 276 60+ years 0 No 6.96164384 Alive 7.6 1
## 277 60+ years 0 No 0.65205479 Died 7.4 2
## 278 40-59 years 1 Yes 6.18356164 Alive 5.6 1
## 279 60+ years 0 No 6.85205479 Alive 6.5 1
## 280 60+ years 0 No 4.92602740 Died 6.3 2
## 281 40-59 years 0 No 2.41917808 Died 5.6 2
## 282 60+ years 1 Yes 6.98082192 Alive 7.0 1
## 283 40-59 years 0 No 6.92328767 Alive 4.8 1
## 284 40-59 years 1 Yes 6.20000000 Alive 4.5 1
## 285 60+ years 0 No 1.93424658 Died 6.8 2
## 286 40-59 years 0 No 7.09041096 Alive 5.7 1
## 287 60+ years 0 No 6.96438356 Alive 7.0 1
## 288 <40 years 0 No 3.50410959 <NA> 3.9 NA
## 289 40-59 years 1 Yes 3.57260274 Died 4.6 2
## 290 60+ years 1 Yes 6.36712329 Alive 7.7 1
## 291 40-59 years NA <NA> 6.81643836 Alive 5.9 1
## 292 40-59 years 0 No 7.20000000 Alive 5.8 1
## 293 40-59 years 0 No 7.67123288 Alive 5.6 1
## 294 60+ years 0 No 6.72876712 Alive 6.8 1
## 295 40-59 years 1 Yes 6.85753425 Alive 5.7 1
## 296 40-59 years 0 No 3.96164384 Died 4.4 2
## 297 40-59 years 1 Yes 1.75616438 Died 5.6 2
## 298 60+ years 0 No 4.89863014 Died 6.7 2
## 299 60+ years 0 No 6.31232877 Alive 6.2 1
## 300 60+ years 0 No 2.58630137 Died 6.8 2
## 301 60+ years 0 No 7.33972603 Alive 6.1 1
## 302 40-59 years 1 Yes 1.53150685 Died 4.4 2
## 303 40-59 years 0 No 7.29589041 Alive 5.2 1
## 304 40-59 years 1 Yes 1.77260274 Died 5.1 2
## 305 40-59 years 0 No 7.38904110 Alive 5.9 1
## 306 60+ years 0 No 6.95342466 Alive 6.1 1
## 307 40-59 years 0 No 6.07945205 Alive 5.7 1
## 308 60+ years 0 No 6.81369863 Alive 6.5 1
## 309 60+ years 1 Yes 7.42191781 Alive 7.3 1
## 310 60+ years 0 No 2.30136986 Died 6.9 2
## 311 60+ years 0 No 6.21095890 Alive 6.3 1
## 312 60+ years 0 No 6.69589041 Alive 7.5 1
## 313 60+ years 0 No 6.55616438 Alive 6.4 1
## 314 40-59 years 0 No 6.12876712 Alive 5.6 1
## 315 60+ years 0 No 7.98630137 Alive 6.9 1
## 316 60+ years 0 No 6.75890411 Alive 6.4 1
## 317 60+ years 1 Yes 2.99178082 Died 7.4 2
## 318 60+ years 0 No 7.46849315 Alive 7.2 1
## 319 40-59 years 1 Yes 7.57260274 Alive 5.8 1
## 320 60+ years 1 Yes 7.10136986 Alive 7.4 1
## 321 60+ years 0 No 7.47945205 Alive 6.1 1
## 322 60+ years NA <NA> 6.26575342 Alive 7.4 1
## 323 60+ years 0 No 5.80000000 Alive 6.4 1
## 324 60+ years 0 No 4.56986301 Died 7.1 2
## 325 60+ years 1 Yes 1.44657534 Died 6.6 2
## 326 40-59 years 1 Yes 7.26301370 Alive 5.3 1
## 327 60+ years 1 Yes 7.33150685 Alive 7.6 1
## 328 60+ years 1 Yes 5.16438356 Alive 7.5 1
## 329 60+ years 0 No 6.43835616 Alive 6.4 1
## 330 60+ years 0 No 1.30136986 Died 6.5 2
## 331 40-59 years 0 No 3.41369863 Died 5.7 2
## 332 60+ years 1 Yes 6.03835616 Alive 6.5 1
## 333 40-59 years 0 No 7.44109589 Alive 5.3 1
## 334 60+ years 0 No 2.18356164 Died 7.4 2
## 335 60+ years 0 No 6.92328767 Alive 7.4 1
## 336 60+ years 1 Yes 5.53698630 Alive 7.4 1
## 337 40-59 years 0 No 1.36438356 Died 4.8 2
## 338 40-59 years 0 No 2.42465753 Died 5.8 2
## 339 60+ years 0 No 2.19726027 Died 7.4 2
## 340 60+ years 0 No 7.32602740 Alive 7.1 1
## 341 40-59 years 0 No 2.03561644 Died 5.4 2
## 342 60+ years 0 No 6.89589041 Alive 8.0 1
## 343 60+ years 1 Yes 0.95616438 Died 7.0 2
## 344 60+ years 1 Yes 7.46027397 Alive 7.0 1
## 345 60+ years NA <NA> 2.12328767 Died 7.0 2
## 346 60+ years 0 No 6.37260274 Alive 7.1 1
## 347 40-59 years 0 No 3.10684932 Died 5.9 2
## 348 40-59 years 0 No 1.64931507 Died 4.7 2
## 349 60+ years 0 No 6.97808219 Alive 6.3 1
## 350 60+ years 0 No 2.57534247 Died 6.9 2
## 351 60+ years 0 No 6.83835616 Alive 7.3 1
## 352 60+ years 0 No 7.20000000 Alive 6.7 1
## 353 40-59 years 0 No 6.44657534 Alive 5.5 1
## 354 40-59 years 0 No 5.98356164 Alive 4.5 1
## 355 60+ years 1 Yes 6.07945205 Alive 7.8 1
## 356 60+ years 0 No 0.52328767 Died 8.0 2
## 357 40-59 years 0 No 1.15342466 Died 5.5 2
## 358 60+ years 1 Yes 6.47123288 Alive 6.4 1
## 359 60+ years 1 Yes 2.60821918 Died 6.0 2
## 360 60+ years 0 No 2.49589041 Died 7.4 2
## 361 60+ years 0 No 5.07123288 Alive 6.1 1
## 362 60+ years 0 No 6.63835616 Alive 6.4 1
## 363 40-59 years 1 Yes 1.27123288 Died 4.8 2
## 364 60+ years 0 No 1.21369863 Died 7.6 2
## 365 60+ years 0 No 0.50958904 Died 7.6 2
## 366 40-59 years 0 No 6.97260274 Alive 5.0 1
## 367 40-59 years 0 No 0.97534247 Died 5.6 2
## 368 40-59 years 0 No 1.32602740 Died 4.2 2
## 369 60+ years 0 No 1.04657534 Died 7.2 2
## 370 60+ years 1 Yes 2.79726027 Died 6.8 2
## 371 40-59 years 0 No 6.77260274 Alive 4.9 1
## 372 60+ years 0 No 6.44383562 Alive 6.4 1
## 373 60+ years NA <NA> 6.81095890 Alive 7.0 1
## 374 40-59 years 1 Yes 0.88767123 Died 5.0 2
## 375 60+ years 1 Yes 6.89589041 Alive 7.4 1
## 376 <40 years 0 No 7.15890411 Alive 3.7 1
## 377 60+ years NA <NA> 6.71232877 Alive 7.5 1
## 378 40-59 years 0 No 2.10958904 Died 5.6 2
## 379 60+ years 0 No 6.82191781 Alive 7.4 1
## 380 60+ years 0 No 4.24109589 Died 6.3 2
## 381 40-59 years 0 No 6.70958904 Alive 5.6 1
## 382 40-59 years 0 No 6.29863014 Alive 4.2 1
## 383 60+ years 0 No 3.43013699 Died 6.3 2
## 384 60+ years 0 No 2.00000000 Died 6.2 2
## 385 <40 years 0 No 6.73972603 Alive 3.3 1
## 386 40-59 years 0 No 1.36712329 Died 5.0 2
## 387 60+ years 0 No 0.35342466 Died 7.3 2
## 388 60+ years 0 No 0.14246575 Died 6.1 2
## 389 60+ years 1 Yes 5.94794521 Alive 7.0 1
## 390 <40 years 0 No 3.22739726 Died 3.8 2
## 391 60+ years 1 Yes 5.24657534 Alive 6.4 1
## 392 <40 years 0 No 7.04657534 Alive 3.9 1
## 393 40-59 years 0 No 7.09589041 Alive 4.7 1
## 394 60+ years 1 Yes 0.58904110 Died 7.6 2
## 395 60+ years 0 No 6.36986301 Alive 6.5 1
## 396 40-59 years 1 Yes 2.63287671 Died 4.3 2
## 397 60+ years 0 No 7.37260274 Alive 7.2 1
## 398 <40 years 0 No 7.05205479 Alive 3.3 1
## 399 60+ years 0 No 6.95890411 Alive 6.6 1
## 400 60+ years 0 No 6.47671233 Alive 7.4 1
## 401 40-59 years 0 No 6.77260274 Alive 5.4 1
## 402 40-59 years 0 No 1.12054795 Died 4.4 2
## 403 60+ years 1 Yes 2.63287671 Died 7.5 2
## 404 40-59 years 0 No 6.70958904 Alive 5.8 1
## 405 40-59 years 0 No 6.90410959 Alive 4.8 1
## 406 60+ years 0 No 2.50958904 Died 6.4 2
## 407 40-59 years NA <NA> 6.10136986 Alive 4.9 1
## 408 40-59 years 0 No 6.55890411 Alive 5.5 1
## 409 60+ years 0 No 5.55890411 Alive 6.0 1
## 410 60+ years 0 No 6.81369863 Alive 6.7 1
## 411 60+ years 0 No 5.62191781 Alive 7.9 1
## 412 40-59 years 0 No 7.36986301 Alive 5.7 1
## 413 <40 years 0 No 6.12054795 Alive 2.2 1
## 414 40-59 years 1 Yes 1.47123288 Died 5.9 2
## 415 60+ years 1 Yes 6.23835616 Alive 6.6 1
## 416 40-59 years 1 Yes 1.99726027 Died 5.4 2
## 417 40-59 years 0 No 6.01095890 Alive 5.8 1
## 418 <40 years 1 Yes 6.98904110 Alive 3.6 1
## 419 40-59 years 0 No 4.63561644 Died 5.2 2
## 420 60+ years 0 No 2.07671233 Died 6.1 2
## 421 60+ years 0 No 5.69589041 Alive 7.6 1
## 422 40-59 years 1 Yes 1.97260274 Died 5.8 2
## 423 40-59 years 0 No 6.52054795 Alive 5.2 1
## 424 60+ years 0 No 2.31506849 Died 7.2 2
## 425 60+ years 0 No 6.61917808 Alive 7.4 1
## 426 60+ years 0 No 2.36438356 Died 6.2 2
## 427 40-59 years 1 Yes 3.73424658 Died 4.6 2
## 428 60+ years 0 No 6.92602740 Alive 6.6 1
## 429 40-59 years 0 No 3.13698630 Died 5.2 2
## 430 <40 years 0 No 1.36712329 Died 3.8 2
## 431 60+ years 0 No 0.66301370 Died 6.1 2
## 432 60+ years 0 No 6.28493151 Alive 6.0 1
## 433 60+ years 1 Yes 2.35068493 Died 6.8 2
## 434 40-59 years 0 No 0.33424658 Died 5.3 2
## 435 40-59 years 0 No 7.34794521 Alive 5.8 1
## 436 60+ years 0 No 4.98082192 Died 6.4 2
## 437 60+ years 1 Yes 6.93698630 Alive 6.8 1
## 438 60+ years 1 Yes 0.90684932 Died 6.2 2
## 439 60+ years 0 No 2.87123288 Died 7.0 2
## 440 40-59 years 0 No 6.88493151 Alive 5.7 1
## 441 60+ years 1 Yes 0.93150685 Died 6.6 2
## 442 40-59 years NA <NA> 5.06849315 Alive 5.9 1
## 443 60+ years 0 No 6.38904110 Alive 7.5 1
## 444 60+ years 0 No 6.24383562 Alive 7.7 1
## 445 40-59 years 0 No 2.85205479 Died 5.7 2
## 446 60+ years 0 No 4.90410959 Died 7.2 2
## 447 60+ years 1 Yes 0.83287671 Died 6.4 2
## 448 <40 years 0 No 6.89589041 Alive 3.3 1
## 449 60+ years 0 No 5.90684932 Alive 6.2 1
## 450 60+ years 0 No 3.80273973 Died 7.0 2
## 451 40-59 years 1 Yes 6.96986301 Alive 5.5 1
## 452 <40 years 1 Yes 5.07397260 Alive 3.2 1
## 453 60+ years 1 Yes 5.81369863 Alive 6.4 1
## 454 40-59 years 0 No 7.06027397 Alive 4.8 1
## 455 60+ years 1 Yes 5.54246575 Alive 6.8 1
## 456 40-59 years 0 No 3.29041096 Died 5.9 2
## 457 60+ years 1 Yes 2.46849315 Died 6.8 2
## 458 40-59 years 1 Yes 6.53424658 Alive 5.0 1
## 459 40-59 years 1 Yes 1.81643836 Died 4.1 2
## 460 60+ years 1 Yes 6.86575342 Alive 6.9 1
## 461 40-59 years 0 No 6.38904110 Alive 4.6 1
## 462 40-59 years 0 No 5.96164384 Alive 4.3 1
## 463 60+ years 0 No 3.32054795 Died 6.8 2
## 464 60+ years 0 No 2.43835616 Died 7.3 2
## 465 60+ years 1 Yes 0.82739726 Died 6.6 2
## 466 60+ years 1 Yes 6.56438356 Alive 6.0 1
## 467 60+ years 0 No 6.79726027 Alive 7.4 1
## 468 60+ years 0 No 0.86575342 Died 6.8 2
## 469 60+ years 1 Yes 6.15068493 Alive 6.0 1
## 470 60+ years 1 Yes 6.70410959 Alive 7.1 1
## 471 60+ years 0 No 6.06301370 Alive 7.6 1
## 472 40-59 years 0 No 2.93150685 Died 5.7 2
## 473 <40 years 0 No 1.20273973 Died 3.3 2
## 474 40-59 years 0 No 2.47945205 Died 5.4 2
## 475 60+ years 0 No 4.72054795 Died 6.8 2
## 476 60+ years 0 No 0.66027397 Died 7.0 2
## 477 60+ years 0 No 3.60000000 Died 6.6 2
## 478 40-59 years 1 Yes 1.20000000 Died 4.5 2
## 479 60+ years 0 No 5.42739726 Alive 6.1 1
## 480 60+ years 1 Yes 6.01369863 Alive 7.4 1
## 481 40-59 years 1 Yes 3.01643836 Died 4.7 2
## 482 40-59 years 1 Yes 0.21643836 Died 5.8 2
## 483 60+ years 0 No 2.67397260 Died 7.3 2
## 484 60+ years 0 No 1.81917808 Died 6.1 2
## 485 40-59 years 0 No 6.29863014 Alive 4.4 1
## 486 40-59 years 0 No 0.76438356 Died 5.6 2
## 487 60+ years 0 No 2.84109589 Died 6.6 2
## 488 <40 years 0 No 1.89589041 Died 3.0 2
## 489 60+ years 1 Yes 5.95616438 Alive 6.7 1
## 490 60+ years 0 No 5.87397260 Alive 7.4 1
## 491 60+ years 1 Yes 5.63835616 Alive 7.4 1
## 492 40-59 years 0 No 6.80821918 Alive 5.6 1
## 493 60+ years 0 No 6.60273973 Alive 6.0 1
## 494 40-59 years 1 Yes 7.02739726 Alive 5.4 1
## 495 60+ years 0 No 2.42191781 Died 7.4 2
## 496 40-59 years 0 No 1.06575342 Died 4.5 2
## 497 60+ years 0 No 1.89589041 Died 8.1 2
## 498 60+ years 1 Yes 1.75890411 Died 7.3 2
## 499 60+ years 1 Yes 2.31780822 Died 7.1 2
## 500 60+ years 0 No 6.03561644 Alive 7.0 1
## 501 60+ years 0 No 5.92876712 Alive 6.6 1
## 502 60+ years 0 No 3.48767123 Died 7.1 2
## 503 40-59 years 0 No 6.55616438 Alive 4.8 1
## 504 40-59 years 0 No 2.36164384 Died 5.5 2
## 505 60+ years 0 No 6.38630137 Alive 7.2 1
## 506 40-59 years 0 No 6.20273973 Alive 5.7 1
## 507 40-59 years 0 No 0.39452055 Died 5.7 2
## 508 <40 years 0 No 6.65479452 Alive 3.8 1
## 509 40-59 years 1 Yes 1.98082192 Died 5.2 2
## 510 40-59 years 0 No 6.93150685 Alive 5.7 1
## 511 <40 years 0 No 4.29589041 Died 3.3 2
## 512 <40 years 0 No 6.27945205 Alive 3.9 1
## 513 60+ years 0 No 6.16986301 Alive 6.1 1
## 514 60+ years 0 No 6.59726027 Alive 7.1 1
## 515 40-59 years 0 No 7.00000000 Alive 5.8 1
## 516 60+ years 0 No 0.75616438 Died 6.6 2
## 517 40-59 years 0 No 5.19452055 Alive 5.9 1
## 518 40-59 years 1 Yes 5.88219178 Alive 4.3 1
## 519 60+ years 0 No 6.21643836 Alive 6.6 1
## 520 40-59 years 0 No 6.55068493 Alive 4.8 1
## 521 60+ years 0 No 3.90136986 Died 6.8 2
## 522 60+ years 0 No 6.18356164 Alive 7.2 1
## 523 60+ years NA <NA> 6.52328767 Alive 7.7 1
## 524 60+ years 1 Yes 5.76164384 Alive 6.8 1
## 525 40-59 years 1 Yes 6.05479452 Alive 4.4 1
## 526 60+ years 0 No 6.93150685 Alive 6.3 1
## 527 60+ years 0 No 6.53698630 Alive 6.6 1
## 528 40-59 years 0 No 0.60000000 Died 5.0 2
## 529 60+ years 0 No 1.33150685 Died 7.2 2
## 530 40-59 years 0 No 3.41369863 Died 4.0 2
## 531 40-59 years 0 No 5.85753425 Alive 4.9 1
## 532 40-59 years 0 No 6.68219178 Alive 5.6 1
## 533 60+ years 0 No 6.11232877 Alive 6.1 1
## 534 60+ years 0 No 1.05205479 Died 6.5 2
## 535 60+ years 0 No 6.86301370 Alive 6.5 1
## 536 60+ years 0 No 4.52602740 Died 7.2 2
## 537 60+ years 1 Yes 6.68767123 Alive 6.8 1
## 538 40-59 years 0 No 1.88219178 Died 5.9 2
## 539 40-59 years 0 No 5.96986301 Alive 5.9 1
## 540 60+ years 1 Yes 5.99726027 Alive 7.1 1
## 541 40-59 years 0 No 6.77260274 Alive 4.9 1
## 542 60+ years 0 No 5.78356164 Alive 7.0 1
## 543 40-59 years 0 No 5.53424658 Alive 5.5 1
## 544 40-59 years 1 Yes 3.18082192 Died 4.6 2
## 545 60+ years 0 No 6.11232877 Alive 7.7 1
## 546 40-59 years 0 No 6.30136986 Alive 5.7 1
## 547 60+ years 0 No 6.55068493 Alive 6.8 1
## 548 60+ years 1 Yes 2.07945205 Died 6.2 2
## 549 40-59 years 0 No 0.45479452 Died 4.4 2
## 550 40-59 years 1 Yes 6.36438356 Alive 5.8 1
## 551 60+ years 0 No 6.35890411 Alive 7.5 1
## 552 60+ years 1 Yes 5.41369863 Alive 7.0 1
## 553 60+ years 0 No 6.10684932 Alive 8.2 1
## 554 60+ years 0 No 4.57808219 Died 6.1 2
## 555 40-59 years 0 No 5.22465753 Alive 5.2 1
## 556 40-59 years 0 No 4.88493151 Died 4.7 2
## 557 60+ years 0 No 1.87397260 Died 6.1 2
## 558 <40 years 0 No 1.20821918 Died 3.9 2
## 559 60+ years 0 No 2.47123288 Died 6.9 2
## 560 40-59 years 0 No 6.14794521 Alive 5.5 1
## 561 40-59 years 1 Yes 5.94520548 Alive 5.6 1
## 562 60+ years 0 No 5.12328767 Alive 8.0 1
## 563 40-59 years 0 No 5.66027397 Alive 4.3 1
## 564 60+ years 0 No 5.56164384 Alive 8.3 1
## 565 60+ years 0 No 0.69315068 Died 8.5 2
## 566 60+ years 0 No 5.60821918 Alive 6.1 1
## 567 40-59 years 0 No 4.84383562 Died 4.7 2
## 568 60+ years 0 No 5.59726027 Alive 7.6 1
## 569 40-59 years 0 No 5.92328767 Alive 5.8 1
## 570 40-59 years 0 No 5.73424658 Alive 5.9 1
## 571 60+ years 0 No 6.32876712 Alive 6.0 1
## 572 <40 years 0 No 5.83013699 Alive 3.2 1
## 573 40-59 years 0 No 5.16164384 Alive 5.6 1
## 574 60+ years 0 No 0.60000000 Died 7.5 2
## 575 60+ years 0 No 6.32602740 Alive 6.2 1
## 576 60+ years 0 No 0.85753425 Died 6.9 2
## 577 60+ years 1 Yes 1.49589041 Died 7.2 2
## 578 40-59 years 0 No 6.06301370 Alive 5.4 1
## 579 60+ years 0 No 5.08493151 Alive 7.2 1
## 580 <40 years 0 No 3.89315068 <NA> 2.7 NA
## 581 60+ years 0 No 1.26027397 Died 6.2 2
## 582 <40 years 0 No 5.95342466 Alive 3.9 1
## 583 60+ years 0 No 0.77534247 Died 6.0 2
## 584 40-59 years 1 Yes 0.09315068 Died 5.5 2
## 585 60+ years 0 No 6.00273973 Alive 6.4 1
## 586 60+ years 0 No 5.98904110 Alive 6.8 1
## 587 60+ years 0 No 3.17534247 Died 6.5 2
## 588 60+ years 1 Yes 1.68767123 Died 6.6 2
## 589 <40 years 0 No 6.21917808 Alive 3.9 1
## 590 40-59 years 1 Yes 2.90684932 Died 5.4 2
## 591 <40 years 1 Yes 1.61917808 Died 3.4 2
## 592 60+ years 0 No 5.65753425 Alive 7.4 1
## 593 60+ years 1 Yes 0.56986301 Died 8.1 2
## 594 <40 years 0 No 6.46575342 Alive 3.8 1
## 595 40-59 years 0 No 6.33424658 Alive 5.9 1
## 596 60+ years 0 No 5.21095890 Alive 6.2 1
## 597 60+ years 1 Yes 4.96986301 <NA> 6.1 NA
## 598 40-59 years 1 Yes 5.78356164 Alive 4.6 1
## 599 40-59 years 0 No 6.38356164 Alive 5.5 1
## 600 40-59 years 0 No 6.03287671 Alive 5.7 1
## 601 <40 years 0 No 3.54794521 Died 3.8 2
## 602 60+ years 1 Yes 5.25479452 Alive 6.9 1
## 603 60+ years 1 Yes 5.66027397 Alive 7.9 1
## 604 60+ years 0 No 5.85205479 Alive 7.1 1
## 605 60+ years 0 No 6.27123288 Alive 7.4 1
## 606 <40 years 1 Yes 1.57808219 Died 3.0 2
## 607 60+ years 0 No 6.11506849 Alive 7.2 1
## 608 60+ years NA <NA> 2.83287671 Died 6.8 2
## 609 60+ years 1 Yes 1.59726027 Died 6.6 2
## 610 60+ years 0 No 1.14246575 Died 6.3 2
## 611 40-59 years 1 Yes 5.21917808 Alive 5.2 1
## 612 60+ years 0 No 2.39726027 Died 6.4 2
## 613 60+ years 0 No 1.84657534 Died 6.8 2
## 614 60+ years 0 No 5.98630137 Alive 7.4 1
## 615 <40 years 0 No 3.15342466 Died 3.2 2
## 616 60+ years 1 Yes 0.93698630 Died 6.0 2
## 617 <40 years 0 No 5.99178082 Alive 3.9 1
## 618 60+ years 1 Yes 3.92876712 Died 7.6 2
## 619 60+ years 0 No 1.17808219 Died 6.2 2
## 620 40-59 years 1 Yes 6.40821918 Alive 4.1 1
## 621 <40 years 1 Yes 3.73972603 Died 3.5 2
## 622 40-59 years 0 No 6.33698630 Alive 5.9 1
## 623 40-59 years 0 No 5.89863014 Alive 5.2 1
## 624 60+ years 0 No 5.92876712 Alive 6.5 1
## 625 60+ years 0 No 5.97260274 Alive 6.1 1
## 626 60+ years 0 No 5.78082192 Alive 6.1 1
## 627 40-59 years 0 No 5.86027397 Alive 5.9 1
## 628 40-59 years 0 No 5.80821918 Alive 5.9 1
## 629 60+ years 0 No 6.01917808 Alive 7.1 1
## 630 <40 years 0 No 1.24109589 <NA> 3.9 NA
## 631 60+ years 0 No 2.54246575 Died 6.5 2
## 632 <40 years 1 Yes 1.84931507 Died 3.4 2
## 633 40-59 years 1 Yes 5.94520548 Alive 5.1 1
## 634 40-59 years 0 No 5.85753425 Alive 5.5 1
## 635 60+ years 1 Yes 6.17808219 Alive 6.5 1
## 636 60+ years 0 No 6.27397260 Alive 7.1 1
## 637 60+ years 1 Yes 2.89041096 Died 6.8 2
## 638 40-59 years 0 No 6.43013699 Alive 5.9 1
## 639 60+ years 0 No 1.56986301 Died 6.6 2
## 640 60+ years 0 No 6.02739726 Alive 6.2 1
## 641 40-59 years 0 No 1.50684932 Died 4.0 2
## 642 60+ years 0 No 3.84931507 Died 6.4 2
## 643 40-59 years 1 Yes 6.45205479 Alive 4.0 1
## 644 60+ years 0 No 3.24931507 Died 7.0 2
## 645 60+ years 1 Yes 4.21917808 Died 6.6 2
## 646 60+ years 1 Yes 6.10684932 Alive 7.3 1
## 647 60+ years 0 No 2.65479452 Died 6.9 2
## 648 40-59 years 0 No 1.27397260 Died 5.8 2
## 649 40-59 years 0 No 1.65205479 Died 5.5 2
## 650 40-59 years 1 Yes 2.73150685 Died 5.3 2
## 651 40-59 years 0 No 6.23013699 Alive 5.2 1
## 652 60+ years 0 No 1.54246575 Died 6.2 2
## 653 60+ years 1 Yes 3.92876712 Died 6.1 2
## 654 60+ years 0 No 6.34520548 Alive 6.9 1
## 655 40-59 years 1 Yes 1.89589041 Died 4.1 2
## 656 60+ years 0 No 3.96438356 Died 6.4 2
## 657 40-59 years 0 No 1.17260274 Died 5.9 2
## 658 60+ years 0 No 5.89589041 Alive 6.5 1
## 659 60+ years 0 No 2.33972603 Died 6.6 2
## 660 60+ years 0 No 5.73424658 Alive 6.0 1
## 661 40-59 years 1 Yes 6.02191781 Alive 4.3 1
## 662 60+ years 0 No 5.82465753 Alive 7.4 1
## 663 60+ years 0 No 5.99726027 Alive 6.7 1
## 664 40-59 years 1 Yes 5.86849315 Alive 4.6 1
## 665 40-59 years 0 No 6.24109589 Alive 4.7 1
## 666 60+ years 1 Yes 1.70410959 Died 6.6 2
## 667 <40 years 1 Yes 6.00547945 Alive 3.6 1
## 668 60+ years 1 Yes 1.13150685 Died 6.2 2
## 669 60+ years 0 No 3.26301370 Died 6.9 2
## 670 60+ years 0 No 3.12054795 Died 7.6 2
## 671 <40 years 1 Yes 0.45205479 Died 3.6 2
## 672 60+ years 1 Yes 6.05479452 Alive 7.3 1
## 673 60+ years 0 No 6.10136986 Alive 7.2 1
## 674 60+ years 0 No 5.68767123 Alive 6.1 1
## 675 40-59 years 0 No 5.84109589 Alive 5.8 1
## 676 40-59 years 1 Yes 5.70958904 Alive 5.2 1
## 677 60+ years 0 No 5.21917808 Alive 6.6 1
## 678 40-59 years 0 No 1.66575342 Died 4.3 2
## 679 60+ years 0 No 5.66027397 Alive 6.0 1
## 680 60+ years 0 No 5.49589041 Alive 6.1 1
## 681 60+ years 0 No 5.98082192 Alive 6.1 1
## 682 40-59 years 0 No 5.75068493 Alive 4.6 1
## 683 60+ years 0 No 5.14794521 Alive 7.3 1
## 684 60+ years 1 Yes 0.72328767 Died 6.5 2
## 685 60+ years 1 Yes 5.77260274 Alive 6.1 1
## 686 60+ years 0 No 2.03561644 Died 6.5 2
## 687 60+ years 0 No 2.64657534 Died 6.8 2
## 688 60+ years 0 No 5.68767123 Alive 6.3 1
## 689 60+ years 1 Yes 0.06575342 Died 7.2 2
## 690 60+ years 1 Yes 1.22739726 Died 7.4 2
## 691 40-59 years 0 No 2.49041096 Died 4.5 2
## 692 60+ years 0 No 5.99452055 Alive 6.6 1
## 693 <40 years NA <NA> 1.28493151 Died 3.8 2
## 694 40-59 years 1 Yes 1.62739726 Died 4.6 2
## 695 40-59 years 0 No 5.50136986 Alive 5.1 1
## 696 60+ years 0 No 3.49589041 Died 6.5 2
## 697 40-59 years 0 No 2.62191781 Died 5.5 2
## 698 40-59 years 0 No 5.34246575 Alive 5.8 1
## 699 60+ years 0 No 7.30958904 Alive 6.5 1
## 700 40-59 years 1 Yes 6.16438356 Alive 4.6 1
## 701 40-59 years 0 No 6.00273973 Alive 5.7 1
## 702 60+ years 1 Yes 6.47945205 Alive 6.7 1
## 703 60+ years 0 No 6.38630137 Alive 7.5 1
## 704 60+ years 1 Yes 3.45753425 Died 6.4 2
## 705 60+ years 0 No 4.21095890 <NA> 6.3 NA
## 706 60+ years 0 No 6.53972603 Alive 6.4 1
## 707 40-59 years 0 No 6.12328767 Alive 5.9 1
## 708 60+ years 0 No 5.42465753 Alive 7.8 1
## 709 60+ years 0 No 1.58356164 Died 6.3 2
## 710 40-59 years 0 No 2.96712329 Died 5.7 2
## 711 40-59 years 0 No 5.13698630 Alive 5.2 1
## 712 40-59 years 0 No 6.53150685 Alive 5.0 1
## 713 <40 years 1 Yes 1.54246575 Died 3.6 2
## 714 40-59 years 0 No 5.68767123 Alive 5.0 1
## 715 40-59 years 0 No 5.54794521 Alive 5.3 1
## 716 40-59 years 0 No 5.63013699 Alive 4.8 1
## 717 40-59 years 0 No 3.76712329 Died 5.5 2
## 718 40-59 years 0 No 6.43835616 Alive 4.7 1
## 719 60+ years 1 Yes 6.02739726 Alive 7.4 1
## 720 40-59 years 1 Yes 6.08767123 Alive 5.3 1
## 721 40-59 years 0 No 5.88767123 Alive 5.5 1
## 722 40-59 years 0 No 6.30958904 Alive 5.3 1
## 723 60+ years 1 Yes 0.88219178 Died 6.7 2
## 724 40-59 years 0 No 2.09315068 Died 5.6 2
## 725 <40 years 1 Yes 2.09589041 Died 3.0 2
## 726 40-59 years 0 No 0.25479452 Died 5.6 2
## 727 40-59 years 1 Yes 5.25479452 Alive 4.6 1
## 728 60+ years 0 No 5.29315068 Alive 6.0 1
## 729 60+ years 0 No 6.24109589 Alive 6.0 1
## 730 40-59 years 1 Yes 0.39726027 Died 5.7 2
## 731 40-59 years 0 No 5.24109589 Alive 4.2 1
## 732 40-59 years 0 No 5.96164384 Alive 5.8 1
## 733 40-59 years 0 No 5.46575342 Alive 5.3 1
## 734 60+ years 1 Yes 5.54246575 Alive 7.3 1
## 735 60+ years 0 No 5.30136986 Alive 7.3 1
## 736 40-59 years 0 No 6.00273973 Alive 5.7 1
## 737 60+ years 0 No 6.00273973 Alive 7.7 1
## 738 60+ years 0 No 5.08493151 Alive 6.0 1
## 739 60+ years 0 No 1.72054795 Died 7.4 2
## 740 60+ years 0 No 5.41369863 Alive 7.0 1
## 741 40-59 years 0 No 4.98356164 <NA> 5.3 NA
## 742 60+ years 1 Yes 0.38630137 Died 6.8 2
## 743 40-59 years 1 Yes 1.15616438 Died 5.9 2
## 744 <40 years 1 Yes 5.49589041 Alive 2.9 1
## 745 40-59 years 0 No 5.78904110 Alive 5.7 1
## 746 60+ years 0 No 4.99452055 <NA> 6.1 NA
## 747 60+ years 1 Yes 5.94520548 Alive 6.8 1
## 748 40-59 years 0 No 4.96438356 Died 4.9 2
## 749 60+ years 0 No 5.03561644 Alive 7.0 1
## 750 40-59 years 1 Yes 5.08219178 Alive 5.3 1
## 751 40-59 years 1 Yes 0.73698630 Died 5.7 2
## 752 60+ years 0 No 6.61369863 Alive 7.6 1
## 753 40-59 years 1 Yes 5.95616438 Alive 5.9 1
## 754 40-59 years 0 No 6.20000000 Alive 5.6 1
## 755 <40 years 0 No 4.09589041 Died 3.8 2
## 756 60+ years 0 No 0.86027397 Died 6.1 2
## 757 40-59 years 0 No 6.19452055 Alive 4.9 1
## 758 60+ years 0 No 1.96164384 Died 6.9 2
## 759 40-59 years 0 No 6.00000000 Alive 5.3 1
## 760 60+ years 0 No 6.38630137 Alive 7.2 1
## 761 40-59 years 0 No 5.99178082 Alive 5.7 1
## 762 60+ years 1 Yes 1.64931507 Died 7.3 2
## 763 40-59 years 1 Yes 1.82465753 Died 5.8 2
## 764 60+ years 0 No 0.37808219 Died 6.9 2
## 765 60+ years 1 Yes 5.48219178 Alive 6.9 1
## 766 40-59 years 0 No 2.43013699 Died 4.7 2
## 767 60+ years 1 Yes 3.30684932 Died 8.0 2
## 768 60+ years 0 No 5.47123288 Alive 6.7 1
## 769 40-59 years 0 No 5.10684932 Alive 5.4 1
## 770 60+ years 1 Yes 6.63561644 Alive 6.3 1
## 771 60+ years 1 Yes 1.21643836 Died 6.5 2
## 772 60+ years 1 Yes 6.50684932 Alive 6.5 1
## 773 40-59 years 1 Yes 1.96712329 Died 4.8 2
## 774 40-59 years 0 No 6.03835616 Alive 5.2 1
## 775 60+ years 1 Yes 5.80821918 Alive 6.7 1
## 776 60+ years 1 Yes 2.09863014 Died 7.0 2
## 777 40-59 years 1 Yes 1.00273973 Died 5.1 2
## 778 <40 years 0 No 4.80000000 Died 3.2 2
## 779 60+ years 1 Yes 5.98082192 Alive 6.3 1
## 780 60+ years 1 Yes 5.21095890 Alive 8.1 1
## 781 60+ years 0 No 0.70958904 Died 6.6 2
## 782 60+ years 1 Yes 1.66849315 Died 6.0 2
## 783 60+ years 1 Yes 2.27945205 Died 8.1 2
## 784 60+ years 1 Yes 0.44931507 Died 6.6 2
## 785 60+ years 1 Yes 5.00821918 Alive 7.8 1
## 786 40-59 years 0 No 5.88219178 Alive 4.6 1
## 787 40-59 years 0 No 0.55068493 Died 5.7 2
## 788 40-59 years 0 No 6.08493151 Alive 5.7 1
## 789 60+ years 0 No 1.37808219 Died 6.7 2
## 790 60+ years 0 No 1.03013699 Died 6.8 2
## 791 <40 years 0 No 2.22191781 Died 3.8 2
## 792 60+ years 0 No 5.43835616 Alive 7.0 1
## 793 60+ years 0 No 5.68767123 Alive 6.6 1
## 794 60+ years 0 No 3.16164384 Died 6.3 2
## 795 60+ years 0 No 2.31232877 Died 7.2 2
## 796 60+ years 1 Yes 2.82465753 Died 6.1 2
## 797 40-59 years 0 No 3.56712329 Died 4.6 2
## 798 <40 years 1 Yes 5.94246575 Alive 3.6 1
## 799 60+ years 0 No 5.28493151 Alive 6.9 1
## 800 60+ years 0 No 4.93150685 <NA> 7.5 NA
## 801 60+ years 0 No 0.97260274 Died 6.4 2
## 802 60+ years 0 No 1.83287671 Died 7.7 2
## 803 40-59 years NA <NA> 1.27397260 Died 5.1 2
## 804 <40 years 0 No 5.90958904 Alive 3.6 1
## 805 40-59 years 0 No 2.54520548 Died 5.6 2
## 806 60+ years 0 No 6.14246575 Alive 6.3 1
## 807 60+ years 0 No 6.06027397 Alive 6.4 1
## 808 40-59 years 0 No 5.88493151 Alive 4.4 1
## 809 60+ years 1 Yes 0.46849315 Died 7.3 2
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## 811 40-59 years 0 No 5.01095890 Alive 4.4 1
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## 813 60+ years 0 No 1.44931507 Died 6.5 2
## 814 60+ years 1 Yes 5.83561644 Alive 6.8 1
## 815 40-59 years 0 No 5.45205479 Alive 5.6 1
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## 818 40-59 years 0 No 5.92328767 Alive 5.7 1
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## 824 60+ years 0 No 4.96986301 <NA> 6.1 NA
## 825 60+ years 1 Yes 5.92054795 Alive 7.7 1
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## 827 60+ years 0 No 4.06027397 Died 7.7 2
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## 872 40-59 years 0 No 4.90958904 <NA> 5.9 NA
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## 892 60+ years 0 No 5.75342466 Alive 6.2 1
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## 895 40-59 years 0 No 4.99452055 <NA> 5.1 NA
## 896 60+ years 0 No 1.82191781 Died 7.4 2
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## 898 60+ years 0 No 5.39452055 Alive 7.3 1
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## 900 60+ years 1 Yes 1.57808219 Died 7.0 2
## 901 60+ years 0 No 3.02191781 Died 6.8 2
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## 904 60+ years 0 No 0.34246575 Died 7.1 2
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## 906 60+ years NA <NA> 2.57260274 Died 8.2 2
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## 909 60+ years 0 No 5.52876712 Alive 7.1 1
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## 917 60+ years 0 No 0.70958904 Died 7.1 2
## 918 40-59 years 0 No 0.88493151 Died 5.0 2
## 919 60+ years 1 Yes 1.85753425 Died 7.0 2
## 920 60+ years 1 Yes 5.00547945 Alive 7.0 1
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## 922 60+ years 0 No 2.80000000 Died 7.0 2
## 923 40-59 years 1 Yes 6.13698630 Alive 5.5 1
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## 925 60+ years 1 Yes 5.13698630 Alive 7.1 1
## 926 60+ years 0 No 5.90136986 Alive 7.2 1
## 927 60+ years 1 Yes 2.78904110 Died 7.6 2
## 928 40-59 years 1 Yes 5.67671233 Alive 4.8 1
## 929 60+ years 1 Yes 4.98630137 <NA> 6.6 NA
## hospital
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## 762 hospital_5
## 763 hospital_4
## 764 hospital_5
## 765 hospital_1
## 766 hospital_5
## 767 hospital_2
## 768 hospital_1
## 769 hospital_1
## 770 hospital_3
## 771 hospital_4
## 772 hospital_4
## 773 hospital_5
## 774 hospital_1
## 775 hospital_1
## 776 hospital_5
## 777 hospital_5
## 778 hospital_5
## 779 hospital_1
## 780 hospital_1
## 781 hospital_3
## 782 hospital_4
## 783 hospital_5
## 784 hospital_2
## 785 hospital_2
## 786 hospital_2
## 787 hospital_4
## 788 hospital_1
## 789 hospital_2
## 790 hospital_5
## 791 hospital_2
## 792 hospital_1
## 793 hospital_1
## 794 hospital_4
## 795 hospital_5
## 796 hospital_2
## 797 hospital_5
## 798 hospital_2
## 799 hospital_2
## 800 hospital_2
## 801 hospital_5
## 802 hospital_1
## 803 hospital_3
## 804 hospital_4
## 805 hospital_5
## 806 hospital_3
## 807 hospital_2
## 808 hospital_1
## 809 hospital_5
## 810 hospital_3
## 811 hospital_2
## 812 hospital_2
## 813 hospital_5
## 814 hospital_2
## 815 hospital_1
## 816 hospital_3
## 817 hospital_4
## 818 hospital_1
## 819 hospital_5
## 820 hospital_4
## 821 hospital_5
## 822 hospital_5
## 823 hospital_1
## 824 hospital_1
## 825 hospital_4
## 826 hospital_5
## 827 hospital_2
## 828 hospital_3
## 829 hospital_5
## 830 hospital_3
## 831 hospital_2
## 832 hospital_1
## 833 hospital_5
## 834 hospital_5
## 835 hospital_5
## 836 hospital_4
## 837 hospital_5
## 838 hospital_5
## 839 hospital_5
## 840 hospital_1
## 841 hospital_1
## 842 hospital_5
## 843 hospital_3
## 844 hospital_4
## 845 hospital_1
## 846 hospital_4
## 847 hospital_5
## 848 hospital_1
## 849 hospital_2
## 850 hospital_5
## 851 hospital_5
## 852 hospital_1
## 853 hospital_5
## 854 hospital_4
## 855 hospital_2
## 856 hospital_4
## 857 hospital_2
## 858 hospital_5
## 859 hospital_3
## 860 hospital_3
## 861 hospital_5
## 862 hospital_3
## 863 hospital_3
## 864 hospital_2
## 865 hospital_4
## 866 hospital_4
## 867 hospital_2
## 868 hospital_5
## 869 hospital_1
## 870 hospital_4
## 871 hospital_4
## 872 hospital_4
## 873 hospital_5
## 874 hospital_4
## 875 hospital_5
## 876 hospital_5
## 877 hospital_3
## 878 hospital_4
## 879 hospital_1
## 880 hospital_5
## 881 hospital_2
## 882 hospital_4
## 883 hospital_2
## 884 hospital_4
## 885 hospital_1
## 886 hospital_3
## 887 hospital_5
## 888 hospital_3
## 889 hospital_1
## 890 hospital_5
## 891 hospital_5
## 892 hospital_3
## 893 hospital_1
## 894 hospital_5
## 895 hospital_4
## 896 hospital_5
## 897 hospital_5
## 898 hospital_1
## 899 hospital_3
## 900 hospital_5
## 901 hospital_5
## 902 hospital_5
## 903 hospital_1
## 904 hospital_5
## 905 hospital_2
## 906 hospital_2
## 907 hospital_4
## 908 hospital_2
## 909 hospital_1
## 910 hospital_5
## 911 hospital_5
## 912 hospital_1
## 913 hospital_2
## 914 hospital_5
## 915 hospital_4
## 916 hospital_5
## 917 hospital_4
## 918 hospital_3
## 919 hospital_5
## 920 hospital_4
## 921 hospital_5
## 922 hospital_4
## 923 hospital_4
## 924 hospital_1
## 925 hospital_4
## 926 hospital_2
## 927 hospital_2
## 928 hospital_2
## 929 hospital_2
dim(colon_s)## [1] 929 32
names(colon_s)## [1] "id" "rx" "sex" "age"
## [5] "obstruct" "perfor" "adhere" "nodes"
## [9] "status" "differ" "extent" "surg"
## [13] "node4" "time" "sex.factor" "rx.factor"
## [17] "obstruct.factor" "perfor.factor" "adhere.factor" "differ.factor"
## [21] "extent.factor" "surg.factor" "node4.factor" "status.factor"
## [25] "age.factor" "loccomp" "loccomp.factor" "time.years"
## [29] "mort_5yr" "age.10" "mort_5yr.num" "hospital"
str(colon_s)## 'data.frame': 929 obs. of 32 variables:
## $ id : num 1 2 3 4 5 6 7 8 9 10 ...
## $ rx : Factor w/ 3 levels "Obs","Lev","Lev+5FU": 3 3 1 3 1 3 2 1 2 3 ...
## $ sex : num 1 1 0 0 1 0 1 1 1 0 ...
## $ age : num 43 63 71 66 69 57 77 54 46 68 ...
## ..- attr(*, "label")= chr "Age (years)"
## $ obstruct : num NA 0 0 1 0 0 0 0 0 0 ...
## $ perfor : num 0 0 0 0 0 0 0 0 0 0 ...
## $ adhere : num 0 0 1 0 0 0 0 0 1 0 ...
## $ nodes : num 5 1 7 6 22 9 5 1 2 1 ...
## $ status : num 1 0 1 1 1 1 1 0 0 0 ...
## $ differ : num 2 2 2 2 2 2 2 2 2 2 ...
## $ extent : num 3 3 2 3 3 3 3 3 3 3 ...
## $ surg : num 0 0 0 1 1 0 1 0 0 1 ...
## $ node4 : num 1 0 1 1 1 1 1 0 0 0 ...
## $ time : num 1521 3087 963 293 659 ...
## $ sex.factor : Factor w/ 2 levels "Female","Male": 2 2 1 1 2 1 2 2 2 1 ...
## ..- attr(*, "label")= chr "Sex"
## $ rx.factor : Factor w/ 3 levels "Obs","Lev","Lev+5FU": 3 3 1 3 1 3 2 1 2 3 ...
## ..- attr(*, "label")= chr "Treatment"
## $ obstruct.factor: Factor w/ 2 levels "No","Yes": NA 1 1 2 1 1 1 1 1 1 ...
## ..- attr(*, "label")= chr "Obstruction"
## $ perfor.factor : Factor w/ 2 levels "No","Yes": 1 1 1 1 1 1 1 1 1 1 ...
## ..- attr(*, "label")= chr "Perforation"
## $ adhere.factor : Factor w/ 2 levels "No","Yes": 1 1 2 1 1 1 1 1 2 1 ...
## ..- attr(*, "label")= chr "Adherence"
## $ differ.factor : Factor w/ 3 levels "Well","Moderate",..: 2 2 2 2 2 2 2 2 2 2 ...
## ..- attr(*, "label")= chr "Differentiation"
## $ extent.factor : Factor w/ 4 levels "Submucosa","Muscle",..: 3 3 2 3 3 3 3 3 3 3 ...
## ..- attr(*, "label")= chr "Extent of spread"
## $ surg.factor : Factor w/ 2 levels "Short","Long": 1 1 1 2 2 1 2 1 1 2 ...
## ..- attr(*, "label")= chr "Time from surgery"
## $ node4.factor : Factor w/ 2 levels "No","Yes": 2 1 2 2 2 2 2 1 1 1 ...
## ..- attr(*, "label")= chr ">4 positive nodes"
## $ status.factor : Factor w/ 2 levels "Alive","Died": 2 1 2 2 2 2 2 1 1 1 ...
## ..- attr(*, "label")= chr "Status"
## $ age.factor : Factor w/ 3 levels "<40 years","40-59 years",..: 2 3 3 3 3 2 3 2 2 3 ...
## ..- attr(*, "label")= chr "Age"
## $ loccomp : num NA 0 1 1 0 0 0 0 1 0 ...
## $ loccomp.factor : Factor w/ 2 levels "No","Yes": NA 1 2 2 1 1 1 1 2 1 ...
## ..- attr(*, "label")= chr "Local complications"
## $ time.years : num 4.167 8.458 2.638 0.803 1.805 ...
## ..- attr(*, "label")= chr "Time (years)"
## $ mort_5yr : Factor w/ 2 levels "Alive","Died": 2 1 2 2 2 2 2 1 1 1 ...
## ..- attr(*, "label")= chr "Mortality 5 year"
## $ age.10 : num 4.3 6.3 7.1 6.6 6.9 5.7 7.7 5.4 4.6 6.8 ...
## $ mort_5yr.num : num 2 1 2 2 2 2 2 1 1 1 ...
## $ hospital : Factor w/ 5 levels "hospital_1","hospital_2",..: 5 3 5 4 5 4 2 2 2 2 ...
tibble::glimpse(colon_s)## Rows: 929
## Columns: 32
## $ id <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, ...
## $ rx <fct> Lev+5FU, Lev+5FU, Obs, Lev+5FU, Obs, Lev+5FU, Lev, ...
## $ sex <dbl> 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, ...
## $ age <dbl> 43, 63, 71, 66, 69, 57, 77, 54, 46, 68, 47, 52, 64,...
## $ obstruct <dbl> NA, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1,...
## $ perfor <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ adhere <dbl> 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, ...
## $ nodes <dbl> 5, 1, 7, 6, 22, 9, 5, 1, 2, 1, 1, 2, 1, 3, 4, 1, 6,...
## $ status <dbl> 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, ...
## $ differ <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 2, 2, ...
## $ extent <dbl> 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
## $ surg <dbl> 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, ...
## $ node4 <dbl> 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, ...
## $ time <dbl> 1521, 3087, 963, 293, 659, 1767, 420, 3192, 3173, 3...
## $ sex.factor <fct> Male, Male, Female, Female, Male, Female, Male, Mal...
## $ rx.factor <fct> Lev+5FU, Lev+5FU, Obs, Lev+5FU, Obs, Lev+5FU, Lev, ...
## $ obstruct.factor <fct> NA, No, No, Yes, No, No, No, No, No, No, No, No, No...
## $ perfor.factor <fct> No, No, No, No, No, No, No, No, No, No, No, No, No,...
## $ adhere.factor <fct> No, No, Yes, No, No, No, No, No, Yes, No, Yes, No, ...
## $ differ.factor <fct> Moderate, Moderate, Moderate, Moderate, Moderate, M...
## $ extent.factor <fct> Serosa, Serosa, Muscle, Serosa, Serosa, Serosa, Ser...
## $ surg.factor <fct> Short, Short, Short, Long, Long, Short, Long, Short...
## $ node4.factor <fct> Yes, No, Yes, Yes, Yes, Yes, Yes, No, No, No, No, N...
## $ status.factor <fct> Died, Alive, Died, Died, Died, Died, Died, Alive, A...
## $ age.factor <fct> 40-59 years, 60+ years, 60+ years, 60+ years, 60+ y...
## $ loccomp <dbl> NA, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1,...
## $ loccomp.factor <fct> NA, No, Yes, Yes, No, No, No, No, Yes, No, Yes, No,...
## $ time.years <dbl> 4.1671233, 8.4575342, 2.6383562, 0.8027397, 1.80547...
## $ mort_5yr <fct> Died, Alive, Died, Died, Died, Died, Died, Alive, A...
## $ age.10 <dbl> 4.3, 6.3, 7.1, 6.6, 6.9, 5.7, 7.7, 5.4, 4.6, 6.8, 4...
## $ mort_5yr.num <dbl> 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, ...
## $ hospital <fct> hospital_5, hospital_3, hospital_5, hospital_4, hos...
blog post: “Five Steps for missing data with ‘finalfit’ “ by Ewen Harris
smokin_mcarSmoking missing completely at random, same rate of missing-ness regardless of any other variablessmoking_marSmoking missing conditional on patient sex, different rates of missing-ness dependant on sex
set.seed(1)
colon_s <- colon_s %>%
dplyr::group_by(sex.factor) %>%
dplyr::mutate(smoking_mcar = dplyr::case_when(sex.factor == "Female" ~ sample(c("Smoker", "Non-smoker", NA),
size = n(),
replace = TRUE,
prob = c(0.15, 0.75, 0.10)),
sex.factor == "Male" ~ sample(c("Smoker", "Non-smoker", NA),
size = n(),
replace = TRUE,
prob = c(0.25, 0.65, 0.10)))) %>%
dplyr::mutate(smoking_mar = dplyr::case_when(sex.factor == "Female" ~ sample(c("Smoker", "Non-smoker", NA),
size = n(),
replace = TRUE,
prob = c(0.1, 0.5, 0.4)),
sex.factor == "Male" ~ sample(c("Smoker", "Non-smoker", NA),
size = n(),
replace = TRUE,
prob = c(0.15, 0.75, 0.1)))) %>%
dplyr::ungroup() %>%
dplyr::mutate_at(vars(starts_with("smoking")),
as.factor)Missing rate are the same for both genders.
colon_s %>%
dplyr::group_by(sex.factor, smoking_mcar) %>%
dplyr::tally() %>%
dplyr::group_by(sex.factor) %>%
dplyr::mutate(prop = n/sum(n)) %>%
dplyr::ungroup() %>%
ggplot(aes(x = sex.factor,
y = prop,
group = smoking_mcar,
fill = smoking_mcar)) +
geom_col(position = 'fill') +
geom_text(aes(label = ifelse(prop >= 0.07,
paste0(sprintf("%.0f", prop*100), "%"),
"")),
position = position_stack(vjust=0.5),
colour = "white") 
Missing rate depends on gender.
colon_s %>%
dplyr::group_by(sex.factor, smoking_mar) %>%
dplyr::tally() %>%
dplyr::group_by(sex.factor) %>%
dplyr::mutate(prop = n/sum(n)) %>%
dplyr::ungroup() %>%
ggplot(aes(x = sex.factor,
y = prop,
group = smoking_mar,
fill = smoking_mar)) +
geom_col(position = 'fill') +
geom_text(aes(label = ifelse(prop >= 0.07,
paste0(sprintf("%.0f", prop*100), "%"),
"")),
position = position_stack(vjust=0.5),
colour = "white") 
tibble::glimpse(colon_s)## Rows: 929
## Columns: 34
## $ id <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, ...
## $ rx <fct> Lev+5FU, Lev+5FU, Obs, Lev+5FU, Obs, Lev+5FU, Lev, ...
## $ sex <dbl> 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, ...
## $ age <dbl> 43, 63, 71, 66, 69, 57, 77, 54, 46, 68, 47, 52, 64,...
## $ obstruct <dbl> NA, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1,...
## $ perfor <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...
## $ adhere <dbl> 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, ...
## $ nodes <dbl> 5, 1, 7, 6, 22, 9, 5, 1, 2, 1, 1, 2, 1, 3, 4, 1, 6,...
## $ status <dbl> 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, ...
## $ differ <dbl> 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 2, 2, 2, 2, 2, ...
## $ extent <dbl> 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, ...
## $ surg <dbl> 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 0, 1, 0, ...
## $ node4 <dbl> 1, 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, ...
## $ time <dbl> 1521, 3087, 963, 293, 659, 1767, 420, 3192, 3173, 3...
## $ sex.factor <fct> Male, Male, Female, Female, Male, Female, Male, Mal...
## $ rx.factor <fct> Lev+5FU, Lev+5FU, Obs, Lev+5FU, Obs, Lev+5FU, Lev, ...
## $ obstruct.factor <fct> NA, No, No, Yes, No, No, No, No, No, No, No, No, No...
## $ perfor.factor <fct> No, No, No, No, No, No, No, No, No, No, No, No, No,...
## $ adhere.factor <fct> No, No, Yes, No, No, No, No, No, Yes, No, Yes, No, ...
## $ differ.factor <fct> Moderate, Moderate, Moderate, Moderate, Moderate, M...
## $ extent.factor <fct> Serosa, Serosa, Muscle, Serosa, Serosa, Serosa, Ser...
## $ surg.factor <fct> Short, Short, Short, Long, Long, Short, Long, Short...
## $ node4.factor <fct> Yes, No, Yes, Yes, Yes, Yes, Yes, No, No, No, No, N...
## $ status.factor <fct> Died, Alive, Died, Died, Died, Died, Died, Alive, A...
## $ age.factor <fct> 40-59 years, 60+ years, 60+ years, 60+ years, 60+ y...
## $ loccomp <dbl> NA, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0, 1,...
## $ loccomp.factor <fct> NA, No, Yes, Yes, No, No, No, No, Yes, No, Yes, No,...
## $ time.years <dbl> 4.1671233, 8.4575342, 2.6383562, 0.8027397, 1.80547...
## $ mort_5yr <fct> Died, Alive, Died, Died, Died, Died, Died, Alive, A...
## $ age.10 <dbl> 4.3, 6.3, 7.1, 6.6, 6.9, 5.7, 7.7, 5.4, 4.6, 6.8, 4...
## $ mort_5yr.num <dbl> 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, ...
## $ hospital <fct> hospital_5, hospital_3, hospital_5, hospital_4, hos...
## $ smoking_mcar <fct> Smoker, Smoker, Non-smoker, Non-smoker, NA, Non-smo...
## $ smoking_mar <fct> Non-smoker, Smoker, NA, NA, Non-smoker, NA, Non-smo...
Rubin defined three types of missing data:
MCAR occurs when there is a simple probability that data will be missing, and that probability is unrelated to anything else in your study. For example, a patient can miss a follow up visit because there is an accident on the highway and they simply can't get to the visit.
MAR happens when the missingness is related to information in your study, but all the relevant information to predict missingness is in the existing dataset. An example might be a weight loss study in which people drop out if their trajectory is that they are gaining weight. If you can estimate that trajectory for each person before anyone drops out, and see that those whose slope is positive subsequently drop out, you could take that as MAR.
NMAR is like MAR in that the missingness is related to what is happening in your study, but differs in that the data that are related to the missingness is included in the data that are missing. For instance, if you are studying a treatment for vertigo / 'woozy-ness', but anytime a patient is really woozy, they don't show up for the follow-up visit. Thus, all the high values are missing, and they are missing because they are high!
colon_s %>%
dplyr::group_by(sex.factor) %>%
furniture::table1("Age, years" = age,
"Sex, binary" = sex.factor,
"Number of Nodes" = nodes,
"Extent of spread" = extent.factor,
"Perforation" = perfor.factor,
"Mortality, 5 years" = mort_5yr,
"Smoking (MCAR)" = smoking_mcar,
"Smoking (MAR)" = smoking_mar,
total = TRUE,
na.rm = FALSE,
digits = 2,
output = "markdown")## Using dplyr::group_by() groups: sex.factor
| Total | Female | Male | |
|---|---|---|---|
| n = 929 | n = 445 | n = 484 | |
| Age, years | |||
| 59.75 (11.95) | 59.49 (12.28) | 60.00 (11.64) | |
| Sex, binary | |||
| Female | 445 (47.9%) | 445 (100%) | 0 (0%) |
| Male | 484 (52.1%) | 0 (0%) | 484 (100%) |
| NA | 0 (0%) | 0 (0%) | 0 (0%) |
| Number of Nodes | |||
| 3.66 (3.57) | 3.73 (3.55) | 3.59 (3.59) | |
| Extent of spread | |||
| Submucosa | 21 (2.3%) | 13 (2.9%) | 8 (1.7%) |
| Muscle | 106 (11.4%) | 47 (10.6%) | 59 (12.2%) |
| Serosa | 759 (81.7%) | 366 (82.2%) | 393 (81.2%) |
| Adjacent structures | 43 (4.6%) | 19 (4.3%) | 24 (5%) |
| NA | 0 (0%) | 0 (0%) | 0 (0%) |
| Perforation | |||
| No | 902 (97.1%) | 432 (97.1%) | 470 (97.1%) |
| Yes | 27 (2.9%) | 13 (2.9%) | 14 (2.9%) |
| NA | 0 (0%) | 0 (0%) | 0 (0%) |
| Mortality, 5 years | |||
| Alive | 511 (55%) | 243 (54.6%) | 268 (55.4%) |
| Died | 404 (43.5%) | 194 (43.6%) | 210 (43.4%) |
| NA | 14 (1.5%) | 8 (1.8%) | 6 (1.2%) |
| Smoking (MCAR) | |||
| Non-smoker | 645 (69.4%) | 336 (75.5%) | 309 (63.8%) |
| Smoker | 186 (20%) | 64 (14.4%) | 122 (25.2%) |
| NA | 98 (10.5%) | 45 (10.1%) | 53 (11%) |
| Smoking (MAR) | |||
| Non-smoker | 573 (61.7%) | 236 (53%) | 337 (69.6%) |
| Smoker | 129 (13.9%) | 40 (9%) | 89 (18.4%) |
| NA | 227 (24.4%) | 169 (38%) | 58 (12%) |
colon_s %>%
dplyr::select(age, sex.factor, nodes, extent.factor, perfor.factor, obstruct.factor,
mort_5yr, smoking_mcar, smoking_mar,) %>%
finalfit::ff_glimpse() ## $Continuous
## label var_type n missing_n missing_percent mean sd min
## age Age (years) <dbl> 929 0 0.0 59.8 11.9 18.0
## nodes nodes <dbl> 911 18 1.9 3.7 3.6 0.0
## quartile_25 median quartile_75 max
## age 53.0 61.0 69.0 85.0
## nodes 1.0 2.0 5.0 33.0
##
## $Categorical
## label var_type n missing_n missing_percent
## sex.factor Sex <fct> 929 0 0.0
## extent.factor Extent of spread <fct> 929 0 0.0
## perfor.factor Perforation <fct> 929 0 0.0
## obstruct.factor Obstruction <fct> 908 21 2.3
## mort_5yr Mortality 5 year <fct> 915 14 1.5
## smoking_mcar smoking_mcar <fct> 831 98 10.5
## smoking_mar smoking_mar <fct> 702 227 24.4
## levels_n levels
## sex.factor 2 "Female", "Male"
## extent.factor 4 "Submucosa", "Muscle", "Serosa", "Adjacent structures"
## perfor.factor 2 "No", "Yes"
## obstruct.factor 2 "No", "Yes", "(Missing)"
## mort_5yr 2 "Alive", "Died", "(Missing)"
## smoking_mcar 2 "Non-smoker", "Smoker", "(Missing)"
## smoking_mar 2 "Non-smoker", "Smoker", "(Missing)"
## levels_count levels_percent
## sex.factor 445, 484 48, 52
## extent.factor 21, 106, 759, 43 2.3, 11.4, 81.7, 4.6
## perfor.factor 902, 27 97.1, 2.9
## obstruct.factor 732, 176, 21 78.8, 18.9, 2.3
## mort_5yr 511, 404, 14 55.0, 43.5, 1.5
## smoking_mcar 645, 186, 98 69, 20, 11
## smoking_mar 573, 129, 227 62, 14, 24
colon_s %>%
dplyr::select(age, sex.factor, nodes, extent.factor, perfor.factor, obstruct.factor,
mort_5yr, smoking_mcar, smoking_mar,) %>%
finalfit::missing_plot()
colon_s %>%
dplyr::select(age, sex.factor, nodes, extent.factor, perfor.factor, obstruct.factor,
mort_5yr, smoking_mcar, smoking_mar,) %>%
finalfit::missing_pattern()
## age sex.factor extent.factor perfor.factor mort_5yr nodes obstruct.factor
## 590 1 1 1 1 1 1 1
## 194 1 1 1 1 1 1 1
## 72 1 1 1 1 1 1 1
## 20 1 1 1 1 1 1 1
## 14 1 1 1 1 1 1 0
## 5 1 1 1 1 1 1 0
## 2 1 1 1 1 1 1 0
## 11 1 1 1 1 1 0 1
## 5 1 1 1 1 1 0 1
## 1 1 1 1 1 1 0 1
## 1 1 1 1 1 1 0 1
## 10 1 1 1 1 0 1 1
## 2 1 1 1 1 0 1 1
## 2 1 1 1 1 0 1 1
## 0 0 0 0 14 18 21
## smoking_mcar smoking_mar
## 590 1 1 0
## 194 1 0 1
## 72 0 1 1
## 20 0 0 2
## 14 1 1 1
## 5 1 0 2
## 2 0 1 2
## 11 1 1 1
## 5 1 0 2
## 1 0 1 2
## 1 0 0 3
## 10 1 1 1
## 2 1 0 2
## 2 0 1 2
## 98 227 378
colon_s %>%
dplyr::select(age, sex.factor, nodes, extent.factor, perfor.factor, obstruct.factor,
mort_5yr, smoking_mcar, smoking_mar,) %>%
VIM::aggr(numbers = TRUE, # shows the number to the far right
prop = FALSE) # shows counts instead of proportions
colon_s %>%
dplyr::select(age, sex.factor, nodes, extent.factor, perfor.factor, obstruct.factor,
mort_5yr, smoking_mcar, smoking_mar,) %>%
finalfit::missing_pairs()FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
colon_s %>%
dplyr::select(age, sex.factor, nodes, extent.factor, perfor.factor, obstruct.factor,
mort_5yr, smoking_mcar, smoking_mar,) %>%
finalfit::missing_pairs(position = "fill")FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
FALSE Warning: Removed 18 rows containing non-finite values (stat_boxplot).
The main purpose of this package is to test whether the missing data mechanism, for an incompletely observed data set, is one of missing completely at random (MCAR).
As a by product, however, this package has the capabilities of :
- imputing incomplete data
- performing a test to determine whether data have a multivariate normal distribution
- performing a test of equality of covariances for groups
- obtaining normal-theory maximum likelihood estimates for mean and covariance when data are incomplete.
The test of MCAR follows the methodology proposed by Jamshidian and Jalal (2010). It is based on testing equality of covariances between groups having identical missing data patterns.
The data are imputed, using two options of normality and distribution free, and the test of equality of covariances between groups with identical missing data patterns is performed also with options of assuming normality (Hawkins test) or non-parametrically.
Users can optionally use their own method of data imputation as well.
Multiple imputation is an additional feature of the program that can be used as a diagnostic tool to help identify cases or variables that contribute to rejection of MCAR, when the MCAR test is rejected (See Jamshidian and Jalal, 2010 for details).
As explained in Jamshidian, Jalal, and Jansen (2014), this package can also be used for imputing missing data, test of multivariate normality, and test of equality of covariances between several groups when data are completely observed.
Jamshidian, M. and Bentler, P. M. (1999). “ML estimation of mean and covariance structures with missing data using complete data routines.” Journal of Educational and Behavioral Statistics, 24, 21-41.
Jamshidian, M. and Jalal, S. (2010). “Tests of homoscedasticity, normality, and missing at random for incomplete multivariate data,” Psychometrika, 75, 649-674.
Jamshidian, M. Jalal, S., and Jansen, C. (2014). “ MissMech: An R Package for Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random (MCAR),” Journal of Statistical Software, 56(6), 1-31.
colon_s %>%
dplyr::select(age, sex.factor, nodes, extent.factor, perfor.factor,
mort_5yr, smoking_mcar, smoking_mar) %>%
dplyr::mutate_all(as.numeric) %>% # categorical variables must be changed to numeric
MissMech::TestMCARNormality()## Call:
## MissMech::TestMCARNormality(data = .)
##
## Number of Patterns: 6
##
## Total number of cases used in the analysis: 918
##
## Pattern(s) used:
## age sex.factor nodes extent.factor perfor.factor mort_5yr
## group.1 1 1 1 1 1 1
## group.2 1 1 1 1 1 1
## group.3 1 1 1 1 1 1
## group.4 1 1 NA 1 1 1
## group.5 1 1 1 1 1 NA
## group.6 1 1 1 1 1 1
## smoking_mcar smoking_mar Number of cases
## group.1 1 1 604
## group.2 1 NA 199
## group.3 NA 1 74
## group.4 1 1 11
## group.5 1 1 10
## group.6 NA NA 20
##
##
## Test of normality and Homoscedasticity:
## -------------------------------------------
##
## Hawkins Test:
##
## P-value for the Hawkins test of normality and homoscedasticity: 1.937163e-34
##
## Either the test of multivariate normality or homoscedasticity (or both) is rejected.
## Provided that normality can be assumed, the hypothesis of MCAR is
## rejected at 0.05 significance level.
##
## Non-Parametric Test:
##
## P-value for the non-parametric test of homoscedasticity: 1.789557e-08
##
## Hypothesis of MCAR is rejected at 0.05 significance level.
## The multivariate normality test is inconclusive.
Conclusion: This provides evidence that missing data on the variables included in this test are NOT missing completely at random MCAR by Hawkins test,
"R-function for Little’s test for data missing completely at random" by Eric Stemmler (2020/08/14)
Little’s test basically compares the estimated means of each variable between the different missing patterns. These leads to either the decision to use simple random imputation or to model the missingness mechanism and use that model for imputation. The former is appropriate if one can be certain that the means are not different for different missingness patterns, i.e. a non-significant result of the Little’s test. For a more detailed explanation about the different types of missingness (see Gelman and Hill, 2006).
Little himself “… expect[s] the test to be sensitive to departures from the normality assumption, and even under normality the asymptotic null distribution seems unlikely to be reliable unless the sample size is large.” (Little 1988).
Gelman, Andrew, and Jennifer Hill. 2006. Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge university press.
Little, Roderick JA. 1988. “A Test of Missing Completely at Random for Multivariate Data with Missing Values.” Journal of the American Statistical Association 83 (404). Taylor & Francis: 1198–1202.
Statistical inference based on incomplete data typically involves certain assumptions for the missing data mechanism. The validity of these assumptions requires formal evaluation before any further analysis.
For example, likelihood based inference is valid only if the missing data mechanism is ignorable (Rubin 1976), which usually relies on the missing at random assumption (MAR). MAR assumes that the missingness of the data may depend on the observed data, but is independent of the unobserved data. Therefore testing MAR is in general impossible since it requires unavailable information about the missing data.
Instead, the missing completely at random assumption (MCAR) assumes that the missingness of the data is independent of both the observed and unobserved data, which is stronger than MAR and possible to test using only the observed data.
When missing data mechanism depends on the unobserved data, data are missing not at random (MNAR). Although the likelihood inference only requires the MAR assumption, testing of MCAR is still of interest in real applications, since many simple missing data methods such as complete case analysis are valid only under MCAR (Chapter 3 of Little and Rubin 1987, also see the blood test example in Section 4). Also the maximum likelihood estimation for the multivariate normal model may be more sensitive to the distributional assumption when the data are not MCAR (Little 1988).
GitHub repository: https://github.com/rcst/little-test
devtools::source_url("https://raw.githubusercontent.com/rcst/little-test/master/mcar.R")## SHA-1 hash of file is 294bccdf1f2f0f3c5589b0cbcbb428aab2dcd6d8
littletest_mcar <- colon_s %>%
dplyr::select(age, sex.factor, nodes, extent.factor, perfor.factor, obstruct.factor,
mort_5yr, smoking_mcar, smoking_mar,) %>%
mcar()## Iterations of EM:
## 1...2...3...4...5...6...7...
## this could take a while
littletest_mcar$missing.patterns## [1] 14
littletest_mcar$amount.missing## age sex.factor nodes extent.factor perfor.factor
## Number Missing 0 0 18.00000000 0 0
## Percent Missing 0 0 0.01937567 0 0
## obstruct.factor mort_5yr smoking_mcar smoking_mar
## Number Missing 21.00000000 14.00000000 98.0000000 227.0000000
## Percent Missing 0.02260495 0.01506997 0.1054898 0.2443488
littletest_mcar$chi.square## [1] 171.9229
littletest_mcar$df## [1] 95
littletest_mcar$p.value## [1] 2.309862e-06
Conclusion: This provides evidence that missing data on the variables included in this test are NOT missing completely at random MCAR),
colon_s %>%
finalfit::missing_compare(explanatory = c("age", "sex.factor", "nodes", "extent.factor", "perfor.factor",
"smoking_mcar", "smoking_mar"),
dependent = "mort_5yr")## Missing data analysis: Mortality 5 year Not missing
## Age (years) Mean (SD) 59.8 (11.9)
## Sex Female 437 (98.2)
## Male 478 (98.8)
## nodes Mean (SD) 3.7 (3.6)
## Extent of spread Submucosa 20 (95.2)
## Muscle 103 (97.2)
## Serosa 750 (98.8)
## Adjacent structures 42 (97.7)
## Perforation No 888 (98.4)
## Yes 27 (100.0)
## smoking_mcar Non-smoker 636 (98.6)
## Smoker 183 (98.4)
## smoking_mar Non-smoker 565 (98.6)
## Smoker 125 (96.9)
## Missing p
## 53.9 (12.7) 0.066
## 8 (1.8) 0.669
## 6 (1.2)
## 2.9 (2.8) 0.441
## 1 (4.8) 0.325
## 3 (2.8)
## 9 (1.2)
## 1 (2.3)
## 14 (1.6) 1.000
## 0 (0.0)
## 9 (1.4) 1.000
## 3 (1.6)
## 8 (1.4) 0.330
## 4 (3.1)
Conclusion: There is no evidence that missingness in the five year mortality is associated with any of the variables: age, sex, extent of spread, perforation, and smoking (either varaible),
colon_s %>%
finalfit::missing_compare(explanatory = c("age", "sex.factor", "nodes", "extent.factor", "perfor.factor",
"mort_5yr", "smoking_mar"),
dependent = "smoking_mcar")## Missing data analysis: smoking_mcar Not missing
## Age (years) Mean (SD) 59.7 (12.0)
## Sex Female 400 (89.9)
## Male 431 (89.0)
## nodes Mean (SD) 3.7 (3.6)
## Extent of spread Submucosa 19 (90.5)
## Muscle 92 (86.8)
## Serosa 682 (89.9)
## Adjacent structures 38 (88.4)
## Perforation No 806 (89.4)
## Yes 25 (92.6)
## Mortality 5 year Alive 456 (89.2)
## Died 363 (89.9)
## smoking_mar Non-smoker 510 (89.0)
## Smoker 115 (89.1)
## Missing p
## 60.1 (11.8) 0.768
## 45 (10.1) 0.758
## 53 (11.0)
## 3.6 (3.7) 0.920
## 2 (9.5) 0.801
## 14 (13.2)
## 77 (10.1)
## 5 (11.6)
## 96 (10.6) 0.825
## 2 (7.4)
## 55 (10.8) 0.847
## 41 (10.1)
## 63 (11.0) 1.000
## 14 (10.9)
Conclusion: There is no evidence that missingness in the smoking variable (MCAR version) is associated with any of the variables: age, sex, extent of spread, and perforation,
colon_s %>%
finalfit::missing_compare(explanatory = c("age", "sex.factor", "nodes", "extent.factor", "perfor.factor",
"mort_5yr", "smoking_mcar"),
dependent = "smoking_mar")## Missing data analysis: smoking_mar Not missing Missing
## Age (years) Mean (SD) 59.8 (11.8) 59.7 (12.4)
## Sex Female 276 (62.0) 169 (38.0)
## Male 426 (88.0) 58 (12.0)
## nodes Mean (SD) 3.5 (3.2) 4.2 (4.6)
## Extent of spread Submucosa 16 (76.2) 5 (23.8)
## Muscle 76 (71.7) 30 (28.3)
## Serosa 577 (76.0) 182 (24.0)
## Adjacent structures 33 (76.7) 10 (23.3)
## Perforation No 684 (75.8) 218 (24.2)
## Yes 18 (66.7) 9 (33.3)
## Mortality 5 year Alive 390 (76.3) 121 (23.7)
## Died 300 (74.3) 104 (25.7)
## smoking_mcar Non-smoker 490 (76.0) 155 (24.0)
## Smoker 135 (72.6) 51 (27.4)
## p
## 0.897
## <0.001
##
## 0.007
## 0.806
##
##
##
## 0.387
##
## 0.521
##
## 0.397
##
Conclusion: There is evidence that missingness in the smoking variable (MAR version) is associated with sex,