getData.lme.RdIf present in the calling sequence used to produce object, the
data frame used to fit the model is obtained.
# S3 method for class 'lme'
getData(object)if a data argument is present in the calling sequence that
produced object, the corresponding data frame (with
na.action and subset applied to it, if also present in
the call that produced object) is returned;
else, NULL is returned.
Note that as from version 3.1-102, this only omits rows omitted in the
fit if na.action = na.omit, and does not omit at all if
na.action = na.exclude. That is generally what is wanted for
plotting, the main use of this function.
fm1 <- lme(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), data = Ovary,
random = ~ sin(2*pi*Time))
getData(fm1)
#> Grouped Data: follicles ~ Time | Mare
#> Mare Time follicles
#> 1 1 -0.13636360 20
#> 2 1 -0.09090910 15
#> 3 1 -0.04545455 19
#> 4 1 0.00000000 16
#> 5 1 0.04545455 13
#> 6 1 0.09090910 10
#> 7 1 0.13636360 12
#> 8 1 0.18181820 14
#> 9 1 0.22727270 13
#> 10 1 0.27272730 20
#> 11 1 0.31818180 22
#> 12 1 0.36363640 15
#> 13 1 0.40909090 18
#> 14 1 0.45454550 17
#> 15 1 0.50000000 14
#> 16 1 0.54545450 18
#> 17 1 0.59090910 14
#> 18 1 0.63636360 16
#> 19 1 0.68181820 17
#> 20 1 0.72727270 18
#> 21 1 0.77272730 18
#> 22 1 0.81818180 17
#> 23 1 0.86363640 14
#> 24 1 0.90909090 12
#> 25 1 0.95454550 12
#> 26 1 1.00000000 14
#> 27 1 1.04545500 10
#> 28 1 1.09090900 11
#> 29 1 1.13636400 16
#> 30 2 -0.15000000 6
#> 31 2 -0.10000000 6
#> 32 2 -0.05000000 8
#> 33 2 0.00000000 7
#> 34 2 0.05000000 16
#> 35 2 0.10000000 10
#> 36 2 0.15000000 13
#> 37 2 0.20000000 9
#> 38 2 0.25000000 7
#> 39 2 0.30000000 6
#> 40 2 0.35000000 8
#> 41 2 0.40000000 8
#> 42 2 0.45000000 6
#> 43 2 0.50000000 8
#> 44 2 0.55000000 7
#> 45 2 0.60000000 9
#> 46 2 0.65000000 6
#> 47 2 0.70000000 4
#> 48 2 0.75000000 5
#> 49 2 0.80000000 8
#> 50 2 0.85000000 11
#> 51 2 0.90000000 13
#> 52 2 0.95000000 10
#> 53 2 1.00000000 6
#> 54 2 1.05000000 7
#> 55 2 1.10000000 6
#> 56 2 1.15000000 5
#> 57 3 -0.15789470 13
#> 58 3 -0.10526320 11
#> 59 3 -0.05263158 10
#> 60 3 0.00000000 6
#> 61 3 0.05263158 8
#> 62 3 0.10526320 6
#> 63 3 0.15789470 9
#> 64 3 0.21052630 9
#> 65 3 0.26315790 10
#> 66 3 0.31578950 8
#> 67 3 0.36842110 14
#> 68 3 0.42105260 13
#> 69 3 0.47368420 14
#> 70 3 0.52631580 16
#> 71 3 0.57894740 20
#> 72 3 0.63157900 21
#> 73 3 0.68421050 25
#> 74 3 0.73684210 23
#> 75 3 0.78947370 19
#> 76 3 0.84210530 22
#> 77 3 0.89473680 16
#> 78 3 0.94736840 21
#> 79 3 1.00000000 19
#> 80 3 1.05263200 20
#> 81 3 1.10526300 17
#> 82 3 1.15789500 24
#> 83 4 -0.13636360 9
#> 84 4 -0.09090910 9
#> 85 4 -0.04545455 7
#> 86 4 0.00000000 6
#> 87 4 0.04545455 7
#> 88 4 0.09090910 6
#> 89 4 0.13636360 1
#> 90 4 0.18181820 1
#> 91 4 0.22727270 1
#> 92 4 0.27272730 5
#> 93 4 0.31818180 6
#> 94 4 0.36363640 3
#> 95 4 0.40909090 5
#> 96 4 0.45454550 3
#> 97 4 0.50000000 6
#> 98 4 0.54545450 8
#> 99 4 0.59090910 6
#> 100 4 0.63636360 5
#> 101 4 0.68181820 6
#> 102 4 0.72727270 8
#> 103 4 0.77272730 11
#> 104 4 0.81818180 14
#> 105 4 0.86363640 8
#> 106 4 0.90909090 9
#> 107 4 0.95454550 10
#> 108 4 1.00000000 7
#> 109 4 1.04545500 7
#> 110 4 1.09090900 6
#> 111 4 1.13636400 11
#> 112 5 -0.13636360 10
#> 113 5 -0.09090910 12
#> 114 5 -0.04545455 12
#> 115 5 0.00000000 17
#> 116 5 0.04545455 9
#> 117 5 0.09090910 10
#> 118 5 0.13636360 3
#> 119 5 0.18181820 12
#> 120 5 0.22727270 13
#> 121 5 0.27272730 9
#> 122 5 0.31818180 4
#> 123 5 0.36363640 7
#> 124 5 0.40909090 4
#> 125 5 0.45454550 12
#> 126 5 0.50000000 14
#> 127 5 0.54545450 12
#> 128 5 0.59090910 15
#> 129 5 0.63636360 17
#> 130 5 0.68181820 15
#> 131 5 0.72727270 13
#> 132 5 0.77272730 18
#> 133 5 0.81818180 19
#> 134 5 0.86363640 13
#> 135 5 0.90909090 9
#> 136 5 0.95454550 12
#> 137 5 1.00000000 8
#> 138 5 1.04545500 10
#> 139 5 1.09090900 5
#> 140 5 1.13636400 14
#> 141 6 -0.13636360 16
#> 142 6 -0.09090910 17
#> 143 6 -0.04545455 13
#> 144 6 0.00000000 17
#> 145 6 0.04545455 15
#> 146 6 0.09090910 9
#> 147 6 0.13636360 8
#> 148 6 0.18181820 5
#> 149 6 0.22727270 9
#> 150 6 0.27272730 8
#> 151 6 0.31818180 8
#> 152 6 0.36363640 13
#> 153 6 0.40909090 14
#> 154 6 0.45454550 13
#> 155 6 0.50000000 14
#> 156 6 0.54545450 14
#> 157 6 0.59090910 11
#> 158 6 0.63636360 17
#> 159 6 0.68181820 21
#> 160 6 0.72727270 21
#> 161 6 0.77272730 21
#> 162 6 0.81818180 20
#> 163 6 0.86363640 17
#> 164 6 0.90909090 18
#> 165 6 0.95454550 22
#> 166 6 1.00000000 10
#> 167 6 1.04545500 11
#> 168 6 1.09090900 11
#> 169 6 1.13636400 12
#> 170 7 -0.15000000 18
#> 171 7 -0.10000000 13
#> 172 7 -0.05000000 14
#> 173 7 0.00000000 12
#> 174 7 0.05000000 11
#> 175 7 0.10000000 8
#> 176 7 0.15000000 5
#> 177 7 0.20000000 8
#> 178 7 0.25000000 10
#> 179 7 0.30000000 11
#> 180 7 0.35000000 10
#> 181 7 0.40000000 12
#> 182 7 0.45000000 10
#> 183 7 0.50000000 9
#> 184 7 0.55000000 12
#> 185 7 0.60000000 14
#> 186 7 0.65000000 16
#> 187 7 0.70000000 13
#> 188 7 0.75000000 11
#> 189 7 0.80000000 13
#> 190 7 0.85000000 13
#> 191 7 0.90000000 11
#> 192 7 0.95000000 11
#> 193 7 1.00000000 8
#> 194 7 1.05000000 14
#> 195 7 1.10000000 4
#> 196 7 1.15000000 7
#> 197 8 -0.12500000 13
#> 198 8 -0.08333333 9
#> 199 8 -0.04166667 15
#> 200 8 0.00000000 15
#> 201 8 0.04166667 12
#> 202 8 0.08333333 8
#> 203 8 0.12500000 10
#> 204 8 0.16666670 6
#> 205 8 0.20833330 9
#> 206 8 0.25000000 8
#> 207 8 0.29166670 10
#> 208 8 0.33333330 6
#> 209 8 0.37500000 8
#> 210 8 0.41666670 13
#> 211 8 0.45833330 12
#> 212 8 0.50000000 12
#> 213 8 0.54166670 15
#> 214 8 0.58333330 21
#> 215 8 0.62500000 25
#> 216 8 0.66666670 21
#> 217 8 0.70833330 21
#> 218 8 0.75000000 24
#> 219 8 0.79166670 20
#> 220 8 0.83333330 20
#> 221 8 0.87500000 18
#> 222 8 0.91666670 20
#> 223 8 0.95833330 20
#> 224 8 1.00000000 19
#> 225 8 1.04166700 12
#> 226 8 1.08333300 7
#> 227 8 1.12500000 8
#> 228 9 -0.16666670 10
#> 229 9 -0.11111110 14
#> 230 9 -0.05555556 12
#> 231 9 0.00000000 10
#> 232 9 0.05555556 7
#> 233 9 0.11111110 12
#> 234 9 0.16666670 10
#> 235 9 0.22222220 8
#> 236 9 0.27777780 10
#> 237 9 0.33333330 15
#> 238 9 0.38888890 15
#> 239 9 0.44444440 12
#> 240 9 0.50000000 19
#> 241 9 0.55555560 15
#> 242 9 0.61111110 16
#> 243 9 0.66666670 15
#> 244 9 0.72222220 17
#> 245 9 0.77777780 14
#> 246 9 0.83333330 16
#> 247 9 0.88888890 15
#> 248 9 0.94444440 11
#> 249 9 1.00000000 10
#> 250 9 1.05555600 7
#> 251 9 1.11111100 4
#> 252 9 1.16666700 8
#> 253 10 -0.13636360 11
#> 254 10 -0.09090910 16
#> 255 10 -0.04545455 15
#> 256 10 0.00000000 12
#> 257 10 0.04545455 11
#> 258 10 0.09090910 6
#> 259 10 0.13636360 11
#> 260 10 0.18181820 12
#> 261 10 0.22727270 11
#> 262 10 0.27272730 16
#> 263 10 0.31818180 15
#> 264 10 0.36363640 11
#> 265 10 0.40909090 7
#> 266 10 0.45454550 14
#> 267 10 0.50000000 20
#> 268 10 0.54545450 22
#> 269 10 0.59090910 23
#> 270 10 0.63636360 21
#> 271 10 0.68181820 21
#> 272 10 0.72727270 23
#> 273 10 0.77272730 22
#> 274 10 0.81818180 22
#> 275 10 0.86363640 17
#> 276 10 0.90909090 17
#> 277 10 0.95454550 17
#> 278 10 1.00000000 17
#> 279 10 1.04545500 14
#> 280 10 1.09090900 12
#> 281 10 1.13636400 11
#> 282 11 -0.15000000 9
#> 283 11 -0.10000000 8
#> 284 11 -0.05000000 8
#> 285 11 0.00000000 8
#> 286 11 0.05000000 8
#> 287 11 0.10000000 6
#> 288 11 0.15000000 7
#> 289 11 0.20000000 8
#> 290 11 0.25000000 10
#> 291 11 0.30000000 10
#> 292 11 0.35000000 14
#> 293 11 0.40000000 13
#> 294 11 0.45000000 8
#> 295 11 0.50000000 8
#> 296 11 0.55000000 8
#> 297 11 0.60000000 9
#> 298 11 0.65000000 16
#> 299 11 0.70000000 12
#> 300 11 0.75000000 10
#> 301 11 0.80000000 12
#> 302 11 0.85000000 12
#> 303 11 0.90000000 9
#> 304 11 0.95000000 6
#> 305 11 1.00000000 9
#> 306 11 1.05000000 7
#> 307 11 1.10000000 5
#> 308 11 1.15000000 5