Creates a matrix suitable for create_analysis_obj(). Creates dummy variables for factors and
allows transformations of covariates specified with a formula.
Usage
create_data_matrix(
data,
outcome,
trt_flag_col,
ext_flag_col,
covariates = NULL,
weight_var = NULL
)Arguments
- data
data.frame. Data containing all variables
- outcome
character. The outcome variable for binary outcomes or the time and censoring variables.
- trt_flag_col
character. The treatment indicator variable.
- ext_flag_col
character. The external cohort indicator.
- covariates
character or formula. The covariates for model adjustment.
- weight_var
character. An optional weight variable.
Value
Invisibly returns a matrix containing all variables to pass to create_analysis_obj().
Prints names of covariates columns to use with add_covariates().
Examples
dat <- survival::diabetic
dat$ext <- dat$trt == 0 & dat$id > 1000
data_mat <- create_data_matrix(
dat,
outcome = c("time", "status"),
trt_flag_col = "trt",
ext_flag_col = "ext",
covariates = ~ age + laser + log(risk)
)
#> Call `add_covariates()` with `covariates = c("age", "laserargon", "log(risk)") `
data_mat
#> time status trt extTRUE age laserargon log(risk)
#> 1 46.23 0 0 0 28 1 2.197225
#> 2 46.23 0 1 0 28 1 2.197225
#> 3 42.50 0 1 0 12 0 2.079442
#> 4 31.30 1 0 0 12 0 1.791759
#> 5 42.27 0 1 0 9 0 2.397895
#> 6 42.27 0 0 0 9 0 2.397895
#> 7 20.60 0 0 0 9 0 2.397895
#> 8 20.60 0 1 0 9 0 2.397895
#> 9 0.30 1 0 0 13 0 2.302585
#> 10 38.77 0 1 0 13 0 2.197225
#> 11 65.23 0 1 0 12 0 2.197225
#> 12 54.27 1 0 0 12 0 2.197225
#> 13 63.50 0 1 0 8 0 2.079442
#> 14 10.80 1 0 0 8 0 1.791759
#> 15 23.17 0 1 0 12 0 2.079442
#> 16 23.17 0 0 0 12 0 2.197225
#> 17 1.47 0 1 0 16 0 2.197225
#> 18 1.47 0 0 0 16 0 2.302585
#> 19 58.07 0 1 0 21 1 2.197225
#> 20 13.83 1 0 0 21 1 2.197225
#> 21 48.53 0 0 0 23 1 2.197225
#> 22 46.43 1 1 0 23 1 2.197225
#> 23 44.40 0 1 0 44 1 2.397895
#> 24 7.90 1 0 0 44 1 2.484907
#> 25 39.57 0 0 0 47 1 1.791759
#> 26 39.57 0 1 0 47 1 2.397895
#> 27 30.83 1 1 0 48 1 1.791759
#> 28 38.57 1 0 0 48 1 2.302585
#> 29 66.27 0 1 0 26 1 2.302585
#> 30 14.10 1 0 0 26 1 2.197225
#> 31 6.90 1 0 0 10 0 2.302585
#> 32 20.17 1 1 0 10 0 2.197225
#> 33 41.40 1 0 0 23 1 2.197225
#> 34 58.43 0 1 0 23 1 2.484907
#> 35 58.20 0 1 0 5 0 2.197225
#> 36 58.20 0 0 0 5 0 2.197225
#> 37 57.43 0 1 0 46 1 1.791759
#> 38 57.43 0 0 0 46 1 2.079442
#> 39 56.03 0 1 0 5 0 2.397895
#> 40 56.03 0 0 0 5 0 2.484907
#> 41 67.53 0 0 0 13 0 2.197225
#> 42 67.53 0 1 0 13 0 2.197225
#> 43 61.40 0 1 0 45 1 2.197225
#> 44 0.60 1 0 0 45 1 2.484907
#> 45 10.27 1 1 0 11 0 2.302585
#> 46 1.63 1 0 0 11 0 2.302585
#> 47 66.20 0 0 0 1 0 2.397895
#> 48 66.20 0 1 0 1 0 2.484907
#> 49 13.83 1 0 0 10 0 2.197225
#> 50 5.67 1 1 0 10 0 2.484907
#> 51 58.83 0 1 0 12 0 2.197225
#> 52 29.97 1 0 0 12 0 2.397895
#> 53 60.27 0 1 0 36 1 2.197225
#> 54 26.37 1 0 0 36 1 2.397895
#> 55 1.33 1 0 0 53 1 2.484907
#> 56 5.77 1 1 0 53 1 2.302585
#> 57 35.53 1 0 0 10 0 2.397895
#> 58 5.90 1 1 0 10 0 2.397895
#> 59 21.90 1 0 0 25 1 2.197225
#> 60 25.63 1 1 0 25 1 2.302585
#> 61 14.80 1 0 0 14 0 2.197225
#> 62 33.90 1 1 0 14 0 2.197225
#> 63 6.20 1 0 0 16 0 2.079442
#> 64 1.73 1 1 0 16 0 2.302585
#> 65 22.00 1 0 0 38 1 2.079442
#> 66 46.90 0 1 0 38 1 2.197225
#> 67 31.13 0 0 0 14 0 2.197225
#> 68 31.13 0 1 0 14 0 2.197225
#> 69 22.00 1 0 0 10 0 2.397895
#> 70 30.20 1 1 0 10 0 2.197225
#> 71 70.90 0 0 0 17 0 2.484907
#> 72 70.90 0 1 0 17 0 2.397895
#> 73 25.80 1 1 0 44 1 2.397895
#> 74 13.87 1 0 0 44 1 2.079442
#> 75 48.30 1 0 0 21 1 2.197225
#> 76 5.73 1 1 0 21 1 2.197225
#> 77 53.43 0 0 0 19 0 2.197225
#> 78 53.43 0 1 0 19 0 2.197225
#> 79 1.90 1 1 0 13 0 2.302585
#> 80 51.10 0 0 0 13 0 2.484907
#> 81 9.90 1 0 0 40 1 2.197225
#> 82 9.90 1 1 0 40 1 2.302585
#> 83 34.20 0 1 0 9 0 2.079442
#> 84 34.20 0 0 0 9 0 2.484907
#> 85 2.67 1 0 0 48 1 2.484907
#> 86 46.73 0 1 0 48 1 2.302585
#> 87 18.73 0 1 0 42 1 2.302585
#> 88 13.83 1 0 0 42 1 2.302585
#> 89 32.03 0 1 0 24 1 2.397895
#> 90 4.27 1 0 0 24 1 2.302585
#> 91 13.90 1 0 0 55 1 2.302585
#> 92 69.87 0 1 0 55 1 2.302585
#> 93 66.80 0 0 0 17 0 2.197225
#> 94 66.80 0 1 0 17 0 2.397895
#> 95 64.73 0 1 0 5 0 2.197225
#> 96 64.73 0 0 0 5 0 2.079442
#> 97 1.70 1 1 0 6 0 2.302585
#> 98 1.70 1 0 0 6 0 1.791759
#> 99 1.77 1 1 0 19 0 2.197225
#> 100 43.03 1 0 0 19 0 2.484907
#> 101 29.03 0 1 0 12 0 2.079442
#> 102 29.03 0 0 0 12 0 2.079442
#> 103 56.57 0 0 0 45 1 2.197225
#> 104 56.57 0 1 0 45 1 2.197225
#> 105 8.30 1 0 0 27 1 2.302585
#> 106 8.30 1 1 0 27 1 2.197225
#> 107 21.57 0 1 0 43 1 2.079442
#> 108 18.43 1 0 0 43 1 2.197225
#> 109 31.57 0 0 0 4 0 2.079442
#> 110 31.57 0 1 0 4 0 2.197225
#> 111 31.63 1 0 0 45 1 2.197225
#> 112 31.63 0 1 0 45 1 2.302585
#> 113 39.77 0 1 0 32 1 2.397895
#> 114 39.77 0 0 0 32 1 2.302585
#> 115 6.53 1 0 0 3 0 2.397895
#> 116 18.70 1 1 0 3 0 2.302585
#> 117 18.90 0 1 0 14 0 2.079442
#> 118 18.90 0 0 0 14 0 2.197225
#> 119 56.80 0 1 0 13 0 2.302585
#> 120 22.23 1 0 0 13 0 2.079442
#> 121 55.60 0 1 0 15 0 2.302585
#> 122 14.00 1 0 0 15 0 2.197225
#> 123 42.17 1 0 0 10 0 2.302585
#> 124 42.17 1 1 0 10 0 2.197225
#> 125 5.33 1 0 0 6 0 2.197225
#> 126 10.70 0 1 0 6 0 2.197225
#> 127 59.80 1 0 0 17 0 2.302585
#> 128 66.33 0 1 0 17 0 2.197225
#> 129 5.83 1 0 0 37 1 2.397895
#> 130 52.33 0 1 0 37 1 2.484907
#> 131 58.17 0 1 0 18 0 2.197225
#> 132 2.17 1 0 0 18 0 2.484907
#> 133 48.43 1 0 0 13 0 2.079442
#> 134 14.30 1 1 0 13 0 2.197225
#> 135 25.83 0 0 0 14 0 2.302585
#> 136 25.83 0 1 0 14 0 2.484907
#> 137 45.40 0 1 0 12 0 2.302585
#> 138 45.40 0 0 0 12 0 2.197225
#> 139 47.60 0 1 0 9 0 1.791759
#> 140 47.60 0 0 0 9 0 2.197225
#> 141 9.60 1 0 0 11 0 2.302585
#> 142 13.33 1 1 0 11 0 2.484907
#> 143 42.10 0 0 0 10 0 2.397895
#> 144 42.10 0 1 0 10 0 2.397895
#> 145 39.93 0 1 0 5 0 2.197225
#> 146 39.93 0 0 0 5 0 1.791759
#> 147 7.60 1 0 0 15 0 2.484907
#> 148 14.27 1 1 0 15 0 2.197225
#> 149 1.80 1 0 0 7 0 2.484907
#> 150 34.57 1 1 0 7 0 2.484907
#> 151 4.30 1 0 0 2 0 2.484907
#> 152 65.80 0 1 0 2 0 2.197225
#> 153 12.20 1 0 0 22 1 1.791759
#> 154 4.10 1 1 0 22 1 2.079442
#> 155 60.93 0 0 0 5 0 2.484907
#> 156 60.93 0 1 0 5 0 2.397895
#> 157 57.20 0 0 0 4 0 2.197225
#> 158 57.20 0 1 0 4 0 2.302585
#> 159 38.07 0 1 0 27 1 2.079442
#> 160 12.73 1 0 0 27 1 2.302585
#> 161 54.10 0 1 0 53 1 2.397895
#> 162 54.10 1 0 0 53 1 2.397895
#> 163 59.27 0 1 0 10 0 2.197225
#> 164 9.40 1 0 0 10 0 2.484907
#> 165 9.90 1 0 0 13 0 2.302585
#> 166 21.57 1 1 0 13 0 2.484907
#> 167 54.10 0 0 0 12 0 2.079442
#> 168 54.10 0 1 0 12 0 2.079442
#> 169 50.47 0 0 0 24 1 2.397895
#> 170 50.47 0 1 0 24 1 2.197225
#> 171 46.17 0 0 0 17 0 2.484907
#> 172 46.17 0 1 0 17 0 2.197225
#> 173 46.30 0 0 0 8 0 2.397895
#> 174 46.30 0 1 0 8 0 2.397895
#> 175 38.83 0 1 0 58 1 2.484907
#> 176 38.83 0 0 0 58 1 2.197225
#> 177 44.60 0 0 0 17 0 2.197225
#> 178 44.60 0 1 0 17 0 2.197225
#> 179 43.07 0 0 0 12 0 2.197225
#> 180 43.07 0 1 0 12 0 2.484907
#> 181 40.03 0 0 0 25 1 2.079442
#> 182 26.23 1 1 0 25 1 2.079442
#> 183 41.60 0 1 0 15 0 2.197225
#> 184 18.03 1 0 0 15 0 2.397895
#> 185 38.07 0 0 0 21 1 2.397895
#> 186 38.07 0 1 0 21 1 2.397895
#> 187 65.23 0 1 0 20 1 2.197225
#> 188 65.23 0 0 0 20 1 2.197225
#> 189 7.07 1 1 0 23 1 2.302585
#> 190 66.77 0 0 0 23 1 2.484907
#> 191 13.77 1 0 0 13 0 2.484907
#> 192 13.77 1 1 0 13 0 2.302585
#> 193 9.63 1 0 0 45 1 2.484907
#> 194 9.63 0 1 0 45 1 2.302585
#> 195 46.23 0 1 0 5 0 2.484907
#> 196 46.23 0 0 0 5 0 2.484907
#> 197 1.50 1 0 0 8 0 2.484907
#> 198 45.73 0 1 0 8 0 2.197225
#> 199 33.63 1 0 0 30 1 2.197225
#> 200 33.63 1 1 0 30 1 2.197225
#> 201 40.17 0 0 0 7 0 1.791759
#> 202 40.17 0 1 0 7 0 2.079442
#> 203 27.60 1 0 0 39 1 2.302585
#> 204 63.33 1 1 0 39 1 2.397895
#> 205 38.47 1 1 0 26 1 2.302585
#> 206 1.63 1 0 0 26 1 2.302585
#> 207 55.23 0 1 0 50 1 1.791759
#> 208 55.23 0 0 0 50 1 2.079442
#> 209 25.30 1 0 0 34 1 2.302585
#> 210 52.77 0 1 0 34 1 1.791759
#> 211 46.20 1 0 0 10 0 2.079442
#> 212 57.17 0 1 0 10 0 1.791759
#> 213 9.87 0 1 0 40 1 2.302585
#> 214 1.70 1 0 0 40 1 2.302585
#> 215 57.90 0 0 0 13 0 2.397895
#> 216 57.90 0 1 0 13 0 2.484907
#> 217 5.90 0 0 0 7 0 2.484907
#> 218 5.90 0 1 0 7 0 2.302585
#> 219 32.20 0 0 0 11 0 2.484907
#> 220 32.20 0 1 0 11 0 2.484907
#> 221 10.33 1 1 0 13 0 2.197225
#> 222 0.83 1 0 0 13 0 2.302585
#> 223 50.90 0 0 0 9 0 2.197225
#> 224 6.13 1 1 0 9 0 2.484907
#> 225 25.93 1 0 0 5 0 2.197225
#> 226 43.67 0 1 0 5 0 2.197225
#> 227 38.30 0 0 0 10 0 2.197225
#> 228 38.30 0 1 0 10 0 2.197225
#> 229 38.77 0 1 0 23 1 2.197225
#> 230 19.40 1 0 0 23 1 2.302585
#> 231 21.97 1 0 0 2 0 2.302585
#> 232 38.07 0 1 0 2 0 2.484907
#> 233 38.30 0 1 0 12 0 2.397895
#> 234 38.30 0 0 0 12 0 2.397895
#> 235 70.03 0 0 0 7 0 2.197225
#> 236 26.20 1 1 0 7 0 2.302585
#> 237 18.03 1 0 1 13 0 2.397895
#> 238 62.57 0 1 0 13 0 2.197225
#> 239 1.57 1 0 1 50 1 2.197225
#> 240 13.83 1 1 0 50 1 2.079442
#> 241 46.50 0 1 0 20 1 2.484907
#> 242 13.37 1 0 1 20 1 2.484907
#> 243 1.97 1 0 1 15 0 2.197225
#> 244 11.07 1 1 0 15 0 2.397895
#> 245 42.47 0 1 0 30 1 2.197225
#> 246 22.20 1 0 1 30 1 2.197225
#> 247 38.73 0 0 1 32 1 2.197225
#> 248 38.73 0 1 0 32 1 2.197225
#> 249 51.13 0 0 1 39 1 2.397895
#> 250 51.13 0 1 0 39 1 2.397895
#> 251 46.50 0 0 1 4 0 2.397895
#> 252 6.10 1 1 0 4 0 2.302585
#> 253 11.30 1 0 1 3 0 2.397895
#> 254 2.10 1 1 0 3 0 2.302585
#> 255 17.73 1 1 0 10 0 2.302585
#> 256 42.30 0 0 1 10 0 2.197225
#> 257 26.47 0 0 1 6 0 2.302585
#> 258 26.47 0 1 0 6 0 2.197225
#> 259 10.77 0 1 0 15 0 2.397895
#> 260 10.77 0 0 1 15 0 2.397895
#> 261 55.33 0 1 0 33 1 2.484907
#> 262 55.33 0 0 1 33 1 2.302585
#> 263 58.67 0 1 0 15 0 2.197225
#> 264 58.67 0 0 1 15 0 2.197225
#> 265 4.97 1 0 1 44 1 2.197225
#> 266 12.93 1 1 0 44 1 2.302585
#> 267 26.47 1 0 1 48 1 2.484907
#> 268 54.20 0 1 0 48 1 2.197225
#> 269 49.57 0 0 1 4 0 2.197225
#> 270 49.57 0 1 0 4 0 2.302585
#> 271 9.87 1 0 1 46 1 2.397895
#> 272 24.43 1 1 0 46 1 2.484907
#> 273 50.23 0 0 1 25 1 2.197225
#> 274 50.23 0 1 0 25 1 2.197225
#> 275 30.40 1 0 1 12 0 2.484907
#> 276 13.97 1 1 0 12 0 2.397895
#> 277 43.33 0 1 0 12 0 1.791759
#> 278 43.33 1 0 1 12 0 2.302585
#> 279 42.23 0 1 0 26 1 2.079442
#> 280 42.23 0 0 1 26 1 2.079442
#> 281 74.93 0 0 1 11 0 2.197225
#> 282 74.93 0 1 0 11 0 2.197225
#> 283 66.93 0 1 0 36 1 2.197225
#> 284 66.93 0 0 1 36 1 2.197225
#> 285 73.43 0 1 0 12 0 2.197225
#> 286 73.43 0 0 1 12 0 2.197225
#> 287 67.47 0 1 0 50 1 2.484907
#> 288 38.57 1 0 1 50 1 2.397895
#> 289 3.67 0 1 0 44 1 2.197225
#> 290 3.67 1 0 1 44 1 2.302585
#> 291 67.03 0 0 1 8 0 2.197225
#> 292 48.87 1 1 0 8 0 2.302585
#> 293 65.60 0 1 0 14 0 2.197225
#> 294 65.60 0 0 1 14 0 2.197225
#> 295 15.83 1 0 1 18 0 2.302585
#> 296 15.83 0 1 0 18 0 2.302585
#> 297 20.07 0 1 0 56 1 2.397895
#> 298 8.83 1 0 1 56 1 2.079442
#> 299 67.43 0 0 1 9 0 2.197225
#> 300 67.43 0 1 0 9 0 2.302585
#> 301 1.47 0 1 0 15 0 2.197225
#> 302 1.47 0 0 1 15 0 1.791759
#> 303 62.93 0 1 0 5 0 2.397895
#> 304 22.13 1 0 1 5 0 2.197225
#> 305 6.30 1 1 0 1 0 2.197225
#> 306 56.97 0 0 1 1 0 2.397895
#> 307 59.70 0 1 0 1 0 2.302585
#> 308 18.93 1 0 1 1 0 2.302585
#> 309 19.00 1 0 1 14 0 2.197225
#> 310 13.80 1 1 0 14 0 2.302585
#> 311 55.13 0 1 0 57 1 1.791759
#> 312 55.13 0 0 1 57 1 1.791759
#> 313 5.43 1 0 1 8 0 2.397895
#> 314 13.57 1 1 0 8 0 2.397895
#> 315 42.20 0 1 0 33 1 2.397895
#> 316 42.20 0 0 1 33 1 2.397895
#> 317 38.27 0 0 1 46 1 2.197225
#> 318 38.27 0 1 0 46 1 2.302585
#> 319 7.10 0 1 0 3 0 2.079442
#> 320 7.10 1 0 1 3 0 2.484907
#> 321 26.17 1 0 1 35 1 2.397895
#> 322 63.63 0 1 0 35 1 2.397895
#> 323 24.73 1 0 1 8 0 2.397895
#> 324 59.00 0 1 0 8 0 2.397895
#> 325 54.37 0 1 0 30 1 2.197225
#> 326 54.37 0 0 1 30 1 2.302585
#> 327 54.60 0 1 0 51 1 2.079442
#> 328 10.97 1 0 1 51 1 2.484907
#> 329 21.10 1 0 1 42 1 2.197225
#> 330 63.87 0 1 0 42 1 2.197225
#> 331 62.37 0 1 0 20 1 2.197225
#> 332 43.70 1 0 1 20 1 2.079442
#> 333 62.80 0 0 1 23 1 2.197225
#> 334 62.80 0 1 0 23 1 2.397895
#> 335 63.33 0 1 0 22 1 2.397895
#> 336 14.37 1 0 1 22 1 2.197225
#> 337 58.53 0 0 1 25 1 2.197225
#> 338 58.53 0 1 0 25 1 2.197225
#> 339 58.07 0 0 1 45 1 2.397895
#> 340 58.07 0 1 0 45 1 2.484907
#> 341 58.50 0 0 1 20 1 2.197225
#> 342 58.50 0 1 0 20 1 2.302585
#> 343 14.37 0 0 1 41 1 2.197225
#> 344 1.50 1 1 0 41 1 2.197225
#> 345 54.73 0 1 0 19 0 2.484907
#> 346 38.40 1 0 1 19 0 2.302585
#> 347 50.63 0 1 0 4 0 2.484907
#> 348 2.83 1 0 1 4 0 2.397895
#> 349 51.10 0 0 1 36 1 2.197225
#> 350 51.10 0 1 0 36 1 2.302585
#> 351 49.93 0 1 0 20 1 2.197225
#> 352 6.57 1 0 1 20 1 2.197225
#> 353 46.27 0 1 0 24 1 2.197225
#> 354 46.27 1 0 1 24 1 2.197225
#> 355 10.60 0 1 0 28 1 2.197225
#> 356 10.60 0 0 1 28 1 2.302585
#> 357 42.77 0 1 0 51 1 2.079442
#> 358 42.77 0 0 1 51 1 2.484907
#> 359 34.37 1 1 0 16 0 2.197225
#> 360 42.27 0 0 1 16 0 2.302585
#> 361 42.07 0 1 0 16 0 2.302585
#> 362 42.07 0 0 1 16 0 2.302585
#> 363 38.77 0 0 1 10 0 2.197225
#> 364 38.77 0 1 0 10 0 2.197225
#> 365 61.83 1 0 1 20 1 2.484907
#> 366 74.97 0 1 0 20 1 2.197225
#> 367 66.97 0 0 1 10 0 2.484907
#> 368 6.57 1 1 0 10 0 2.302585
#> 369 38.87 1 1 0 16 0 1.791759
#> 370 68.30 0 0 1 16 0 1.791759
#> 371 46.63 1 0 1 10 0 2.197225
#> 372 42.43 1 1 0 10 0 2.397895
#> 373 67.07 0 1 0 11 0 2.197225
#> 374 67.07 0 0 1 11 0 2.197225
#> 375 2.70 1 1 0 1 0 2.302585
#> 376 2.70 0 0 1 1 0 2.484907
#> 377 63.80 0 0 1 17 0 2.079442
#> 378 63.80 0 1 0 17 0 1.791759
#> 379 32.63 0 0 1 7 0 2.197225
#> 380 32.63 0 1 0 7 0 2.197225
#> 381 62.00 0 1 0 29 1 2.302585
#> 382 62.00 0 0 1 29 1 2.079442
#> 383 54.80 0 0 1 5 0 2.302585
#> 384 13.10 1 1 0 5 0 2.397895
#> 385 8.00 0 0 1 1 0 2.079442
#> 386 8.00 0 1 0 1 0 2.079442
#> 387 42.33 1 0 1 22 1 2.397895
#> 388 51.60 0 1 0 22 1 2.484907
#> 389 49.97 0 1 0 33 1 2.197225
#> 390 2.90 1 0 1 33 1 2.302585
#> 391 45.90 0 1 0 3 0 2.302585
#> 392 1.43 1 0 1 3 0 2.302585
#> 393 41.93 0 1 0 32 1 2.197225
#> 394 41.93 0 0 1 32 1 2.197225