data_parallel.RdThese data.frames give sample size tables calculated with
sampleN.TOST() for the parallel group design (2 groups).
The data.frames can be accessed by their names.
| data.frame | Description |
| ctSJ.VIII.10 | Multiplicative model, theta1=0.9, theta2=1.1111 (1/theta1), target power=90% |
| approximate power via non-central t-distribution | |
| ctSJ.VIII.20 | Multiplicative model, theta1=0.8, theta2=1.25 (1/theta1), target power=90% |
| approximate power via non-central t-distribution | |
| ctCW.III | Additive model, theta1=–0.2, theta2=+0.2 (BE limits 0.80 – 1.20), exact |
Attention! Julious gives sample size per group.
| data.frame | Origin | Details |
| ctSJ.VIII.10 | Julious | Table VIII (p. 1972), column ‘Level of bioequivalence 10%’ |
| ctSJ.VIII.20 | Julious | Table VIII (p. 1972), column ‘Level of bioequivalence 20%’ |
| ctCW.III | Chow & Wang | Table III (p. 164) |
Seems the last reference is not very reliable (compare to the table in the paper).
Julious SA. Tutorial in Biostatistics. Sample sizes for clinical trials with Normal data. Stat Med. 2004;23(12):1921–86. doi:10.1002/sim.1783
Chow SC, Wang H. On Sample Size Calculation in Bioequivalence Trials. J Pharmacokinet Pharmacodyn. 2001;28(2):155–69. doi:10.1023/A:1011503032353
Scripts for creation of these data.frames can be found in the /tests
sub-directory of the package.
Comparing the results of these scripts to the corresponding data.frames can
be used for validation purposes.
ctSJ.VIII.10
#> CV power R0.95 R1.0 R1.05
#> 1 0.30 0.9 1012 338 924
#> 2 0.35 0.9 1356 452 1240
#> 3 0.40 0.9 1742 582 1592
#> 4 0.45 0.9 2164 722 1976
#> 5 0.50 0.9 2618 872 2390
#> 6 0.55 0.9 3100 1032 2832
#> 7 0.60 0.9 3606 1202 3294
#> 8 0.65 0.9 4132 1376 3774
#> 9 0.70 0.9 4676 1558 4270
#> 10 0.75 0.9 5232 1742 4780
#> 11 0.80 0.9 5800 1932 5298
#> 12 0.85 0.9 6374 2122 5824
ctSJ.VIII.20
#> CV power R0.85 R0.9 R0.95 R1.0 R1.05 R1.1 R1.15 R1.2
#> 1 0.30 0.9 806 216 102 78 100 184 426 1774
#> 2 0.35 0.9 1080 288 138 102 134 244 572 2378
#> 3 0.40 0.9 1386 368 176 132 170 314 734 3054
#> 4 0.45 0.9 1722 458 218 162 212 388 910 3792
#> 5 0.50 0.9 2082 554 262 196 256 470 1102 4590
#> 6 0.55 0.9 2466 654 310 232 302 556 1304 5436
#> 7 0.60 0.9 2868 762 360 270 352 646 1518 6324
#> 8 0.65 0.9 3286 872 414 308 402 742 1738 7246
#> 9 0.70 0.9 3720 988 468 350 454 838 1968 8200
#> 10 0.75 0.9 4162 1104 522 390 508 938 2202 9176
#> 11 0.80 0.9 4614 1224 578 432 564 1040 2440 10172
#> 12 0.85 0.9 5070 1346 636 476 620 1142 2682 11180
ctCW.III
#> CV power R0.0 R0.05 R0.1 R0.15
#> 1 0.10 0.8 12 14 28 102
#> 2 0.12 0.8 14 18 38 144
#> 3 0.14 0.8 20 24 50 196
#> 4 0.16 0.8 24 32 66 256
#> 5 0.18 0.8 30 38 82 322
#> 6 0.20 0.8 36 48 102 398
#> 7 0.22 0.8 44 56 122 482
#> 8 0.24 0.8 52 66 144 572
#> 9 0.26 0.8 60 78 170 672
#> 10 0.28 0.8 70 90 196 778
#> 11 0.30 0.8 80 102 224 892
#> 12 0.32 0.8 90 116 256 1016
#> 13 0.34 0.8 102 132 288 1146
#> 14 0.36 0.8 114 148 322 1284
#> 15 0.38 0.8 126 164 360 1430
#> 16 0.40 0.8 140 182 398 1586
#> 17 0.10 0.9 14 18 36 140
#> 18 0.12 0.9 18 24 52 200
#> 19 0.14 0.9 24 32 70 270
#> 20 0.16 0.9 30 42 90 354
#> 21 0.18 0.9 38 52 114 446
#> 22 0.20 0.9 46 64 140 550
#> 23 0.22 0.9 54 76 168 666
#> 24 0.24 0.9 64 90 200 792
#> 25 0.26 0.9 76 106 234 928
#> 26 0.28 0.9 88 122 270 1076
#> 27 0.30 0.9 100 140 310 1236
#> 28 0.32 0.9 114 158 354 1406
#> 29 0.34 0.9 128 178 398 1586
#> 30 0.36 0.9 142 200 446 1778
#> 31 0.38 0.9 158 222 498 1980
#> 32 0.40 0.9 176 246 550 2194