tables for data frames
Usage
dtable(
data,
y = NULL,
x = NULL,
...,
level = -1,
response = NULL,
flat = TRUE,
total = FALSE,
prop = FALSE,
summary = NULL
)Arguments
- data
if x is formula or names for data frame then data frame is needed.
- y
name of variable, or fomula, or names of variables on data frame.
- x
name of variable, or fomula, or names of variables on data frame.
- ...
Optional additional arguments
- level
1 for all marginal tables, 2 for all 2 by 2 tables, and null for the full table, possible versus group variable
- response
For level=2, only produce tables with columns given by 'response' (index)
- flat
produce flat tables
- total
add total counts/proportions
- prop
Proportions instead of counts (vector of margins)
- summary
summary function
Examples
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
#>