tables for data frames
dtable(
data,
y = NULL,
x = NULL,
...,
level = -1,
response = NULL,
flat = TRUE,
total = FALSE,
prop = FALSE,
summary = NULL
)if x is formula or names for data frame then data frame is needed.
name of variable, or fomula, or names of variables on data frame.
name of variable, or fomula, or names of variables on data frame.
Optional additional arguments
1 for all marginal tables, 2 for all 2 by 2 tables, and null for the full table, possible versus group variable
For level=2, only produce tables with columns given by 'response' (index)
produce flat tables
add total counts/proportions
Proportions instead of counts (vector of margins)
summary function
data("sTRACE",package="timereg")
dtable(sTRACE,~status)
#>
#> status
#> 0 7 9
#> 236 5 259
#>
dtable(sTRACE,~status+vf)
#>
#> vf 0 1
#> status
#> 0 225 11
#> 7 5 0
#> 9 241 18
dtable(sTRACE,~status+vf,level=1)
#>
#> status
#> 0 7 9
#> 236 5 259
#>
#> vf
#> 0 1
#> 471 29
#>
dtable(sTRACE,~status+vf,~chf+diabetes)
#> chf: 0
#> diabetes: 0
#>
#> vf 0 1
#> status
#> 0 143 4
#> 7 4 0
#> 9 70 2
#> ------------------------------------------------------------
#> chf: 1
#> diabetes: 0
#>
#> vf 0 1
#> status
#> 0 66 7
#> 7 1 0
#> 9 141 15
#> ------------------------------------------------------------
#> chf: 0
#> diabetes: 1
#>
#> vf 0
#> status
#> 0 8
#> 9 8
#> ------------------------------------------------------------
#> chf: 1
#> diabetes: 1
#>
#> vf 0 1
#> status
#> 0 8 0
#> 9 22 1
dtable(sTRACE,c("*f*","status"),~diabetes)
#> diabetes: 0
#>
#> status 0 7 9
#> chf vf
#> 0 0 143 4 70
#> 1 4 0 2
#> 1 0 66 1 141
#> 1 7 0 15
#> ------------------------------------------------------------
#> diabetes: 1
#>
#> status 0 9
#> chf vf
#> 0 0 8 8
#> 1 0 0
#> 1 0 8 22
#> 1 0 1
dtable(sTRACE,c("*f*","status"),~diabetes, level=2)
#> diabetes: 0
#>
#> chf
#> vf 0 1
#> 0 217 208
#> 1 6 22
#>
#> chf
#> status 0 1
#> 0 147 73
#> 7 4 1
#> 9 72 156
#>
#> vf
#> status 0 1
#> 0 209 11
#> 7 5 0
#> 9 211 17
#>
#> ------------------------------------------------------------
#> diabetes: 1
#>
#> chf
#> vf 0 1
#> 0 16 30
#> 1 0 1
#>
#> chf
#> status 0 1
#> 0 8 8
#> 9 8 23
#>
#> vf
#> status 0 1
#> 0 16 0
#> 9 30 1
#>
dtable(sTRACE,c("*f*","status"),level=1)
#>
#> chf
#> 0 1
#> 239 261
#>
#> vf
#> 0 1
#> 471 29
#>
#> status
#> 0 7 9
#> 236 5 259
#>
dtable(sTRACE,~"*f*"+status,level=1)
#>
#> chf
#> 0 1
#> 239 261
#>
#> vf
#> 0 1
#> 471 29
#>
#> status
#> 0 7 9
#> 236 5 259
#>
dtable(sTRACE,~"*f*"+status+I(wmi>1.4)|age>60,level=2)
#>
#> chf
#> vf 0 1
#> 0 145 209
#> 1 5 16
#>
#> chf
#> status 0 1
#> 0 83 58
#> 7 3 0
#> 9 64 167
#>
#> chf
#> I(wmi > 1.4) 0 1
#> FALSE 57 149
#> TRUE 93 76
#>
#> vf
#> status 0 1
#> 0 135 6
#> 7 3 0
#> 9 216 15
#>
#> vf
#> I(wmi > 1.4) 0 1
#> FALSE 191 15
#> TRUE 163 6
#>
#> status
#> I(wmi > 1.4) 0 7 9
#> FALSE 53 0 153
#> TRUE 88 3 78
#>
dtable(sTRACE,"*f*"+status~I(wmi>0.5)|age>60,level=1)
#> I(wmi > 0.5): FALSE
#>
#> chf
#> 1
#> 3
#>
#> vf
#> 0 1
#> 2 1
#>
#> status
#> 0 9
#> 1 2
#>
#> ------------------------------------------------------------
#> I(wmi > 0.5): TRUE
#>
#> chf
#> 0 1
#> 150 222
#>
#> vf
#> 0 1
#> 352 20
#>
#> status
#> 0 7 9
#> 140 3 229
#>
dtable(sTRACE,status~dcut(age))
#> dcut(age): [28.1,60]
#>
#> status
#> 0 7 9
#> 95 2 28
#>
#> ------------------------------------------------------------
#> dcut(age): (60,68.7]
#>
#> status
#> 0 7 9
#> 66 2 57
#>
#> ------------------------------------------------------------
#> dcut(age): (68.7,76]
#>
#> status
#> 0 7 9
#> 55 1 69
#>
#> ------------------------------------------------------------
#> dcut(age): (76,92.1]
#>
#> status
#> 0 9
#> 20 105
#>
dtable(sTRACE,~status+vf+sex|age>60)
#>
#> sex 0 1
#> status vf
#> 0 0 52 83
#> 1 3 3
#> 7 0 0 3
#> 1 0 0
#> 9 0 80 136
#> 1 6 9
dtable(sTRACE,status+vf+sex~+1|age>60, level=2)
#>
#> status
#> vf 0 7 9
#> 0 135 3 216
#> 1 6 0 15
#>
#> status
#> sex 0 7 9
#> 0 55 0 86
#> 1 86 3 145
#>
#> vf
#> sex 0 1
#> 0 132 9
#> 1 222 12
#>
dtable(sTRACE,.~status+vf+sex|age>60,level=1)
#> status: 0
#> vf: 0
#> sex: 0
#>
#> no
#> 64 207 295 313 385 386 672 762 775 879 977 979 1171 1483 1599 2457
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 2520 2549 2712 2820 2850 2927 2952 3587 3832 3872 3902 3970 3999 4049 4189 4295
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 4419 4515 4522 4623 4868 4911 4955 5032 5192 5305 5363 5470 5643 5783 5997 6150
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 6231 6258 6309 6549
#> 1 1 1 1
#>
#> wmi
#> 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2
#> 1 2 1 6 2 3 4 4 7 5 9 5 3
#>
#> chf
#> 0 1
#> 30 22
#>
#> age
#> 60.422 60.918 61.242 61.42 61.755 61.782 62.182 62.997 63.38 64.354 65.461
#> 1 1 1 1 1 1 1 1 1 1 1
#> 65.546 67.389 67.77 68.31 68.507 68.663 68.869 69.842 70.059 70.791 70.999
#> 1 1 1 1 1 1 1 1 1 1 1
#> 71.183 71.227 71.273 71.326 71.411 71.942 72.326 73.829 73.996 74.174 74.193
#> 1 1 1 1 1 1 1 1 1 1 1
#> 74.3 74.777 74.986 75.117 75.194 75.597 75.964 76.249 76.551 76.691 76.803
#> 1 1 1 1 1 1 1 1 1 1 1
#> 77.703 78.004 80.222 80.288 80.529 82.021 82.437 86.163
#> 1 1 1 1 1 1 1 1
#>
#> diabetes
#> 0 1
#> 50 2
#>
#> time
#> 6.124 6.146 6.149 6.151 6.162 6.187 6.272 6.323 6.343 6.406 6.45 6.499 6.505
#> 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 6.511 6.521 6.526 6.56 6.601 6.62 6.628 6.631 6.666 6.71 6.721 6.74 6.831
#> 1 2 1 1 1 1 1 1 1 1 1 1 1
#> 6.875 6.91 6.943 7.009 7.011 7.063 7.118 7.126 7.261 7.294 7.34 7.346 7.406
#> 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 7.422 7.458 7.505 7.562 7.598 7.604 7.619 7.683 7.702 7.743 7.872 8.033
#> 1 1 1 1 1 1 1 1 1 1 1 1
#>
#> ------------------------------------------------------------
#> status: 7
#> vf: 0
#> sex: 0
#> NULL
#> ------------------------------------------------------------
#> status: 9
#> vf: 0
#> sex: 0
#>
#> no
#> 27 312 454 476 565 707 728 784 796 808 914 999 1085 1554 1563 1592
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 1611 1620 1654 1748 1973 2239 2255 2386 2570 2729 2867 2902 2938 3035 3039 3127
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 3234 3245 3286 3333 3372 3623 3742 3756 3857 3985 4006 4021 4239 4399 4641 4776
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 4802 4827 4847 4894 4914 4933 5003 5072 5080 5249 5277 5514 5589 5603 5647 5716
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 5740 5764 5857 5866 6044 6045 6054 6180 6193 6268 6311 6317 6523 6542 6564 6628
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#>
#> wmi
#> 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1
#> 1 4 8 3 3 12 3 3 7 4 8 8 6 3 6 1
#>
#> chf
#> 0 1
#> 19 61
#>
#> age
#> 60.477 63.005 63.057 63.737 64.474 65.382 65.442 65.618 66.393 66.539 66.884
#> 1 1 1 1 1 1 1 1 1 1 1
#> 67.608 67.964 69.352 69.502 70.207 70.5 71.422 71.671 71.767 71.811 72.628
#> 1 1 1 1 1 1 1 1 1 1 1
#> 72.839 73.258 73.406 74.048 74.147 74.163 75.347 75.358 75.419 75.666 76.907
#> 1 1 1 1 1 1 1 1 1 1 1
#> 77.031 77.119 77.297 77.385 77.434 77.914 78.081 78.185 78.221 78.687 78.72
#> 1 1 1 1 1 1 1 1 1 1 1
#> 78.753 78.827 79.537 79.542 79.997 80.121 80.576 80.888 81.047 81.892 82.3
#> 1 1 1 1 1 1 1 1 1 1 1
#> 82.626 82.676 82.706 82.961 82.988 83.282 83.405 83.52 83.764 84.269 84.529
#> 1 1 1 1 1 1 1 1 1 1 1
#> 84.562 84.825 85.141 85.404 85.763 85.867 86.1 86.561 87.175 88.348 88.828
#> 1 1 1 1 1 1 1 1 1 1 1
#> 88.847 90.673 92.11
#> 1 1 1
#>
#> diabetes
#> 0 1
#> 68 12
#>
#> time
#> 0.00924501924891956 0.0102543342947029 0.0127033231498208 0.0148339297396597
#> 1 1 1 1
#> 0.0244941983071622 0.0291877593353856 0.0449010478444397 0.0491303009549156
#> 1 1 1 1
#> 0.061 0.0812215200138744 0.103132670026505 0.106090152188204
#> 1 1 1 1
#> 0.124 0.135 0.145 0.175
#> 1 1 1 1
#> 0.196 0.217822634588927 0.233 0.381
#> 1 1 1 1
#> 0.48 0.493 0.534 0.551569005857687
#> 1 1 1 1
#> 0.554 0.567 0.642 0.787
#> 1 1 1 1
#> 0.795 0.913 0.959 0.998
#> 1 1 1 1
#> 1.121 1.179 1.25 1.337
#> 1 1 1 1
#> 1.412 1.51 1.603 1.752
#> 1 1 1 1
#> 1.801 1.893 1.968 2.05902000734583
#> 1 1 1 1
#> 2.392 2.47266312449542 2.554 2.773
#> 1 1 1 1
#> 2.795 2.937 3.261 3.39589819746953
#> 1 1 1 1
#> 3.593 3.894 3.943 4.08
#> 1 1 1 1
#> 4.176 4.338 4.559 4.595
#> 1 1 1 1
#> 4.814 4.859 4.883 4.904
#> 1 1 1 1
#> 4.943 5.151 5.359 5.571
#> 1 1 1 1
#> 5.767 5.927 5.954 5.95500826347712
#> 1 1 1 1
#> 6.02 6.108 6.362 6.579
#> 1 1 1 1
#> 6.836 7.222 7.261 7.379
#> 1 1 1 1
#>
#> ------------------------------------------------------------
#> status: 0
#> vf: 1
#> sex: 0
#>
#> no
#> 1881 3847 5248
#> 1 1 1
#>
#> wmi
#> 1.4 1.6 1.7
#> 1 1 1
#>
#> chf
#> 1
#> 3
#>
#> age
#> 60.688 66.119 78.498
#> 1 1 1
#>
#> diabetes
#> 0
#> 3
#>
#> time
#> 6.031 6.447 6.496
#> 1 1 1
#>
#> ------------------------------------------------------------
#> status: 7
#> vf: 1
#> sex: 0
#> NULL
#> ------------------------------------------------------------
#> status: 9
#> vf: 1
#> sex: 0
#>
#> no
#> 965 1787 5378 5481 5841 6487
#> 1 1 1 1 1 1
#>
#> wmi
#> 0.7 1 1.2 1.3 1.5
#> 1 1 2 1 1
#>
#> chf
#> 0 1
#> 1 5
#>
#> age
#> 62.912 64.31 70.846 73.352 75.646 77.28
#> 1 1 1 1 1 1
#>
#> diabetes
#> 0 1
#> 5 1
#>
#> time
#> 0.00723927922639996 0.0130957318809815 0.0159947743292432 0.044
#> 1 1 1 1
#> 0.302 0.411
#> 1 1
#>
#> ------------------------------------------------------------
#> status: 0
#> vf: 0
#> sex: 1
#>
#> no
#> 22 23 25 137 236 244 366 369 384 427 473 636 680 774 804 899
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 929 1052 1062 1246 1285 1306 1328 1354 1466 1519 1694 1749 1993 2172 2228 2230
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 2263 2297 2311 2358 2382 2411 2458 2550 2889 2897 3137 3323 3350 3384 3460 3522
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 3585 3650 3661 4280 4468 4516 4711 4723 4855 4936 5173 5234 5434 5478 5479 5519
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 5565 5619 5664 5709 5750 5766 5851 5896 5906 6049 6075 6153 6175 6195 6254 6414
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 6436 6525 6553
#> 1 1 1
#>
#> wmi
#> 0.4 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.2
#> 1 3 1 2 1 3 7 4 5 5 3 9 13 11 3 11 1
#>
#> chf
#> 0 1
#> 50 33
#>
#> age
#> 60.047 60.208 60.302 60.803 60.96 61.036 61.491 61.897 61.919 62.319 62.492
#> 1 1 1 1 1 1 1 1 1 1 1
#> 62.827 62.84 62.912 62.928 63.287 63.298 63.885 63.893 64.005 64.186 64.329
#> 1 1 1 1 1 1 1 1 1 1 1
#> 64.373 64.606 65.368 65.428 65.746 65.798 65.878 66.064 66.459 67.06 67.194
#> 1 1 1 1 1 1 1 1 1 1 1
#> 67.367 67.597 67.655 67.701 67.885 68.003 68.151 68.154 68.211 68.318 68.324
#> 1 1 1 1 1 1 1 1 1 1 1
#> 68.345 68.913 69.036 69.236 69.343 69.933 70.182 70.314 70.654 70.7 70.917
#> 1 1 1 1 1 1 1 1 1 1 1
#> 71.046 71.32 71.811 72.195 72.595 72.759 72.869 73.141 73.195 73.236 74.07
#> 1 1 1 1 1 1 1 1 1 1 1
#> 74.404 74.437 74.618 74.816 74.988 75.027 75.068 75.191 75.358 75.663 77.025
#> 1 1 1 1 1 1 1 1 1 1 1
#> 77.171 78.511 79.09 79.578 81.67 83.4
#> 1 1 1 1 1 1
#>
#> diabetes
#> 0 1
#> 79 4
#>
#> time
#> 5.998 6.003 6.004 6.034 6.069 6.077 6.11 6.151 6.156 6.162 6.219 6.28 6.283
#> 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 6.302 6.316 6.346 6.348 6.359 6.384 6.392 6.401 6.433 6.436 6.463 6.467 6.496
#> 1 1 1 1 1 1 1 1 2 1 1 1 1
#> 6.502 6.554 6.592 6.601 6.611 6.658 6.71 6.732 6.768 6.773 6.776 6.795 6.803
#> 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 6.823 6.836 6.847 6.979 6.992 7.028 7.074 7.091 7.096 7.102 7.209 7.217 7.239
#> 1 1 1 1 1 1 2 1 1 1 1 1 2
#> 7.261 7.302 7.326 7.335 7.345 7.352 7.364 7.493 7.494 7.571 7.579 7.625 7.652
#> 1 1 1 1 1 1 1 1 2 1 1 1 1
#> 7.746 7.809 7.811 7.817 7.828 7.861 7.863 7.897 7.97 7.976 8.011 8.099 8.157
#> 1 1 1 1 1 1 2 1 1 1 1 1 1
#>
#> ------------------------------------------------------------
#> status: 7
#> vf: 0
#> sex: 1
#>
#> no
#> 792 4441 6242
#> 1 1 1
#>
#> wmi
#> 1.7 1.9
#> 2 1
#>
#> chf
#> 0
#> 3
#>
#> age
#> 63.241 66.089 73.645
#> 1 1 1
#>
#> diabetes
#> 0
#> 3
#>
#> time
#> 0.02 0.028
#> 2 1
#>
#> ------------------------------------------------------------
#> status: 9
#> vf: 0
#> sex: 1
#>
#> no
#> 48 125 181 219 235 267 275 277 335 436 477 483 489 506 509 535
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 649 656 695 727 921 969 983 1029 1044 1064 1077 1089 1116 1157 1166 1173
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 1214 1225 1260 1280 1301 1337 1456 1490 1615 1671 1703 1723 1739 1757 1813 1924
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 1933 1939 1944 1946 2041 2210 2320 2345 2349 2585 2648 2672 2703 2907 2971 3025
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 3045 3093 3103 3214 3242 3256 3301 3320 3349 3373 3414 3428 3517 3541 3544 3552
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 3627 3647 3685 3793 3809 3946 4018 4051 4143 4228 4247 4369 4417 4479 4511 4524
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 4532 4538 4621 4687 4727 4777 4784 4786 4996 5009 5073 5106 5177 5201 5232 5279
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 5281 5318 5412 5438 5449 5459 5475 5587 5721 5723 5868 5977 5985 6011 6057 6121
#> 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
#> 6297 6377 6476 6482 6502 6605 6639 6645
#> 1 1 1 1 1 1 1 1
#>
#> wmi
#> 0.4 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.7
#> 1 6 8 6 10 13 16 15 14 7 8 6 6 10 4 5 1
#>
#> chf
#> 0 1
#> 43 93
#>
#> age
#> 60.258 60.573 60.592 60.628 61.291 61.823 62.191 62.437 62.478 62.541 64.036
#> 1 1 1 1 1 1 1 1 1 2 1
#> 64.074 64.17 64.403 64.562 64.685 64.847 65.242 65.379 65.439 65.459 65.461
#> 1 1 1 1 1 1 1 1 1 1 1
#> 65.681 66.023 66.909 67.265 67.271 67.293 67.323 67.389 67.581 67.644 67.668
#> 1 1 1 1 1 1 1 1 1 1 1
#> 67.753 68 68.025 68.345 68.568 68.691 68.902 68.943 69.121 69.204 69.7
#> 2 1 1 1 1 1 1 1 1 1 1
#> 70.026 70.032 70.073 70.075 70.081 70.319 70.402 71.687 71.827 72.049 72.74
#> 1 1 1 1 1 1 1 1 1 1 1
#> 72.762 72.847 72.886 73.086 73.099 73.453 73.508 73.714 74.177 74.377 74.615
#> 1 1 1 1 1 1 1 1 1 1 1
#> 74.829 74.843 74.873 74.999 75.134 75.224 75.263 75.284 75.306 75.408 75.485
#> 1 1 1 1 1 1 1 1 1 1 1
#> 75.55 75.594 75.652 76.016 76.101 76.164 76.189 76.247 76.255 76.258 76.376
#> 1 1 1 1 2 1 1 1 1 1 1
#> 76.817 77.001 77.047 77.272 77.395 77.574 77.829 77.947 78.045 78.169 78.256
#> 1 1 1 1 1 1 1 1 1 1 1
#> 78.385 78.41 78.476 78.563 78.613 78.769 78.923 79.024 79.197 79.602 79.611
#> 1 1 1 1 1 1 1 1 1 1 1
#> 79.66 80.713 80.913 81.034 82.169 82.396 82.654 82.939 83.375 83.422 83.542
#> 1 1 1 1 1 1 1 1 1 1 1
#> 83.781 84.255 84.34 84.661 84.839 84.924 85.683 85.988 86.72 87.682 89.746
#> 1 1 1 1 1 1 1 1 1 1 1
#> 91.515
#> 1
#>
#> diabetes
#> 0 1
#> 118 18
#>
#> time
#> 0.00068749 0.00479720664164051 0.005 0.0147687892620452
#> 1 1 1 1
#> 0.0148054198783357 0.0150148906719405 0.0155063371912111 0.0157959215559531
#> 1 1 1 1
#> 0.019 0.0234311041657347 0.0246992394567933 0.0294018010152504
#> 1 1 1 1
#> 0.0320110500110313 0.0335205551215913 0.033717549782712 0.043362094122218
#> 1 1 1 1
#> 0.0455668172480073 0.048 0.0513728010684717 0.0569486366831698
#> 1 1 1 1
#> 0.064 0.066 0.096 0.103118983768858
#> 1 1 1 1
#> 0.115 0.121 0.14 0.16
#> 1 1 1 1
#> 0.171 0.189 0.206 0.211
#> 1 1 1 1
#> 0.215 0.25 0.255 0.311
#> 1 1 1 1
#> 0.339372734833974 0.398 0.403 0.415
#> 1 1 1 1
#> 0.474 0.538 0.674 0.743
#> 1 1 1 1
#> 0.773 0.801 0.858 0.968
#> 1 1 1 1
#> 0.984 1.055 1.06 1.085
#> 1 1 1 1
#> 1.091 1.132 1.157 1.173
#> 1 1 1 1
#> 1.264 1.28 1.327 1.334
#> 1 1 1 1
#> 1.338 1.345 1.354 1.37
#> 1 1 1 1
#> 1.467 1.475 1.505 1.65
#> 1 1 1 1
#> 1.809 1.839 1.85956658420642 1.912
#> 1 1 1 1
#> 1.946 2.088 2.099 2.17698150922544
#> 1 1 1 1
#> 2.209 2.214 2.225 2.249
#> 1 1 1 1
#> 2.266 2.293 2.296 2.327
#> 1 1 1 1
#> 2.42 2.423 2.661 2.694
#> 1 1 1 1
#> 2.735 2.801 2.875 2.902
#> 1 1 1 1
#> 2.932 2.971 3.001 3.006
#> 1 1 1 1
#> 3.025 3.069 3.07071981293638 3.162
#> 1 1 1 1
#> 3.168 3.282 3.65 3.855
#> 1 1 1 1
#> 3.976 4.143 4.20126902716421 4.332
#> 1 1 1 1
#> 4.53260631947941 4.557 4.694 4.732
#> 1 1 1 1
#> 4.737 4.778 4.803 4.828
#> 1 1 1 1
#> 5.014 5.094 5.102 5.247
#> 1 1 1 1
#> 5.351 5.441 5.691 5.727
#> 1 1 1 1
#> 5.82 5.943 6.086 6.132
#> 1 1 1 1
#> 6.206 6.414 6.496 6.521
#> 1 1 1 1
#> 6.641 6.672 6.809 6.877
#> 1 1 1 1
#>
#> ------------------------------------------------------------
#> status: 0
#> vf: 1
#> sex: 1
#>
#> no
#> 1983 5559 5751
#> 1 1 1
#>
#> wmi
#> 1.4 1.6 1.7
#> 1 1 1
#>
#> chf
#> 0
#> 3
#>
#> age
#> 62.722 67.339 70.435
#> 1 1 1
#>
#> diabetes
#> 0
#> 3
#>
#> time
#> 7.751 7.828 7.924
#> 1 1 1
#>
#> ------------------------------------------------------------
#> status: 7
#> vf: 1
#> sex: 1
#> NULL
#> ------------------------------------------------------------
#> status: 9
#> vf: 1
#> sex: 1
#>
#> no
#> 1207 1245 1296 2677 2890 3018 4082 6376 6416
#> 1 1 1 1 1 1 1 1 1
#>
#> wmi
#> 0.4 0.7 0.8 1 1.3 1.4 1.9
#> 1 2 1 2 1 1 1
#>
#> chf
#> 0 1
#> 1 8
#>
#> age
#> 61.431 64.123 68.666 70.303 71.929 72.392 73.491 77.173 81.883
#> 1 1 1 1 1 1 1 1 1
#>
#> diabetes
#> 0
#> 9
#>
#> time
#> 0.0131395697484259 0.0200790603328496 0.0269757455710787 0.0466610295798164
#> 1 1 1 1
#> 0.0473181052301079 0.086709953642916 0.245226208094042 1.765
#> 1 1 1 1
#> 1.773
#> 1
#>
dtable(sTRACE,status+vf+sex~diabetes|age>60)
#> diabetes: 0
#>
#> sex 0 1
#> status vf
#> 0 0 50 79
#> 1 3 3
#> 7 0 0 3
#> 1 0 0
#> 9 0 68 118
#> 1 5 9
#> ------------------------------------------------------------
#> diabetes: 1
#>
#> sex 0 1
#> status vf
#> 0 0 2 4
#> 1 0 0
#> 9 0 12 18
#> 1 1 0
dtable(sTRACE,status+vf+sex~diabetes|age>60, flat=FALSE)
#> diabetes: 0
#>
#> , , sex = 0
#>
#> vf
#> status 0 1
#> 0 50 3
#> 7 0 0
#> 9 68 5
#>
#> , , sex = 1
#>
#> vf
#> status 0 1
#> 0 79 3
#> 7 3 0
#> 9 118 9
#>
#> ------------------------------------------------------------
#> diabetes: 1
#>
#> , , sex = 0
#>
#> vf
#> status 0 1
#> 0 2 0
#> 9 12 1
#>
#> , , sex = 1
#>
#> vf
#> status 0 1
#> 0 4 0
#> 9 18 0
#>
dtable(sTRACE,status+vf+sex~diabetes|age>60, level=1)
#> diabetes: 0
#>
#> status
#> 0 7 9
#> 135 3 200
#>
#> vf
#> 0 1
#> 318 20
#>
#> sex
#> 0 1
#> 126 212
#>
#> ------------------------------------------------------------
#> diabetes: 1
#>
#> status
#> 0 9
#> 6 31
#>
#> vf
#> 0 1
#> 36 1
#>
#> sex
#> 0 1
#> 15 22
#>
dtable(sTRACE,status+vf+sex~diabetes|age>60, level=2)
#> diabetes: 0
#>
#> status
#> vf 0 7 9
#> 0 129 3 186
#> 1 6 0 14
#>
#> status
#> sex 0 7 9
#> 0 53 0 73
#> 1 82 3 127
#>
#> vf
#> sex 0 1
#> 0 118 8
#> 1 200 12
#>
#> ------------------------------------------------------------
#> diabetes: 1
#>
#> status
#> vf 0 9
#> 0 6 30
#> 1 0 1
#>
#> status
#> sex 0 9
#> 0 2 13
#> 1 4 18
#>
#> vf
#> sex 0 1
#> 0 14 1
#> 1 22 0
#>
dtable(sTRACE,status+vf+sex~diabetes|age>60, level=2, prop=1, total=TRUE)
#> diabetes: 0
#>
#> status
#> vf 0 7 9 Sum
#> 0 0.405660377 0.009433962 0.584905660 1.000000000
#> 1 0.300000000 0.000000000 0.700000000 1.000000000
#>
#> status
#> sex 0 7 9 Sum
#> 0 0.42063492 0.00000000 0.57936508 1.00000000
#> 1 0.38679245 0.01415094 0.59905660 1.00000000
#>
#> vf
#> sex 0 1 Sum
#> 0 0.93650794 0.06349206 1.00000000
#> 1 0.94339623 0.05660377 1.00000000
#>
#> ------------------------------------------------------------
#> diabetes: 1
#>
#> status
#> vf 0 9 Sum
#> 0 0.1666667 0.8333333 1.0000000
#> 1 0.0000000 1.0000000 1.0000000
#>
#> status
#> sex 0 9 Sum
#> 0 0.1333333 0.8666667 1.0000000
#> 1 0.1818182 0.8181818 1.0000000
#>
#> vf
#> sex 0 1 Sum
#> 0 0.93333333 0.06666667 1.00000000
#> 1 1.00000000 0.00000000 1.00000000
#>
dtable(sTRACE,status+vf+sex~diabetes|age>60, level=2, prop=2, total=TRUE)
#> diabetes: 0
#>
#> status
#> vf 0 7 9
#> 0 0.95555556 1.00000000 0.93000000
#> 1 0.04444444 0.00000000 0.07000000
#> Sum 1.00000000 1.00000000 1.00000000
#>
#> status
#> sex 0 7 9
#> 0 0.3925926 0.0000000 0.3650000
#> 1 0.6074074 1.0000000 0.6350000
#> Sum 1.0000000 1.0000000 1.0000000
#>
#> vf
#> sex 0 1
#> 0 0.3710692 0.4000000
#> 1 0.6289308 0.6000000
#> Sum 1.0000000 1.0000000
#>
#> ------------------------------------------------------------
#> diabetes: 1
#>
#> status
#> vf 0 9
#> 0 1.00000000 0.96774194
#> 1 0.00000000 0.03225806
#> Sum 1.00000000 1.00000000
#>
#> status
#> sex 0 9
#> 0 0.3333333 0.4193548
#> 1 0.6666667 0.5806452
#> Sum 1.0000000 1.0000000
#>
#> vf
#> sex 0 1
#> 0 0.3888889 1.0000000
#> 1 0.6111111 0.0000000
#> Sum 1.0000000 1.0000000
#>
dtable(sTRACE,status+vf+sex~diabetes|age>60, level=2, prop=1:2, summary=summary)
#> diabetes: 0
#>
#> status
#> vf 0 7 9
#> 0 0.38165680 0.00887574 0.55029586
#> 1 0.01775148 0.00000000 0.04142012
#> Number of cases in table: 1
#> Number of factors: 2
#> Test for independence of all factors:
#> Chisq = 0.003361, df = 2, p-value = 0.9983
#> Chi-squared approximation may be incorrect
#>
#> status
#> sex 0 7 9
#> 0 0.15680473 0.00000000 0.21597633
#> 1 0.24260355 0.00887574 0.37573964
#> Number of cases in table: 1
#> Number of factors: 2
#> Test for independence of all factors:
#> Chisq = 0.006099, df = 2, p-value = 0.997
#> Chi-squared approximation may be incorrect
#>
#> vf
#> sex 0 1
#> 0 0.34911243 0.02366864
#> 1 0.59171598 0.03550296
#> Number of cases in table: 1
#> Number of factors: 2
#> Test for independence of all factors:
#> Chisq = 0.00019928, df = 1, p-value = 0.9887
#> Chi-squared approximation may be incorrect
#>
#> ------------------------------------------------------------
#> diabetes: 1
#>
#> status
#> vf 0 9
#> 0 0.16216216 0.81081081
#> 1 0.00000000 0.02702703
#> Number of cases in table: 1
#> Number of factors: 2
#> Test for independence of all factors:
#> Chisq = 0.005376, df = 1, p-value = 0.9415
#> Chi-squared approximation may be incorrect
#>
#> status
#> sex 0 9
#> 0 0.05405405 0.35135135
#> 1 0.10810811 0.48648649
#> Number of cases in table: 1
#> Number of factors: 2
#> Test for independence of all factors:
#> Chisq = 0.004171, df = 1, p-value = 0.9485
#> Chi-squared approximation may be incorrect
#>
#> vf
#> sex 0 1
#> 0 0.37837838 0.02702703
#> 1 0.59459459 0.00000000
#> Number of cases in table: 1
#> Number of factors: 2
#> Test for independence of all factors:
#> Chisq = 0.04074, df = 1, p-value = 0.84
#> Chi-squared approximation may be incorrect
#>