data_2x2x3.RdThese data.frames give sample size tables calculated with
sampleN.TOST() for the 2×2×3 replicate crossover design
(2-treatment 2-sequence 3-period design.
The data.frames can be accessed by their names.
| data.frame | Description |
| ct9.6.2 | Additive model, theta1=–0.2, theta2=+0.2 (BE limits 0.80 – 1.20) |
| approximate power via shifted non-central t-distribution | |
| ct9.6.6 | Multiplicative model, theta1=0.8, theta2=1.25 (1/theta1) |
| approximate power via shifted non-central t-distribution |
Attention! CV is se (standard error) of residuals.
| data.frame | Origin | Details |
| ct9.6.2 | Chow & Liu | Table 9.6.2 (p 292) |
| ct9.6.6 | Chow & Liu | Table 9.6.6 (p 293) |
Chow SC, Liu JP. Design and Analysis of Bioavailability and Bioequivalence Studies. Boca Raton: CRC Press; 3rd edition 2009.
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.
ct9.6.2
#> CV power R0.0 R0.05 R0.1 R0.15
#> 1 0.10 0.8 6 6 12 38
#> 2 0.12 0.8 6 8 16 56
#> 3 0.14 0.8 8 10 20 74
#> 4 0.16 0.8 10 12 26 96
#> 5 0.18 0.8 12 16 32 122
#> 6 0.20 0.8 14 18 38 150
#> 7 0.22 0.8 18 22 46 182
#> 8 0.24 0.8 20 26 56 216
#> 9 0.26 0.8 24 30 64 252
#> 10 0.28 0.8 28 34 74 292
#> 11 0.30 0.8 30 40 86 336
#> 12 0.32 0.8 34 44 96 382
#> 13 0.34 0.8 38 50 108 430
#> 14 0.36 0.8 44 56 122 482
#> 15 0.38 0.8 48 62 136 538
#> 16 0.40 0.8 54 68 150 596
#> 17 0.10 0.9 6 8 14 54
#> 18 0.12 0.9 8 10 20 76
#> 19 0.14 0.9 10 14 28 102
#> 20 0.16 0.9 12 16 34 134
#> 21 0.18 0.9 16 20 44 168
#> 22 0.20 0.9 18 24 54 208
#> 23 0.22 0.9 22 30 64 250
#> 24 0.24 0.9 26 34 76 298
#> 25 0.26 0.9 30 40 88 350
#> 26 0.28 0.9 34 46 102 404
#> 27 0.30 0.9 38 54 118 464
#> 28 0.32 0.9 44 60 134 528
#> 29 0.34 0.9 48 68 150 596
#> 30 0.36 0.9 54 76 168 668
#> 31 0.38 0.9 60 84 188 744
#> 32 0.40 0.9 66 94 208 824
ct9.6.6
#> CV power R0.85 R0.9 R0.95 R1.0 R1.05 R1.1 R1.15 R1.2
#> 1 0.1002505 0.8 28 8 6 4 6 8 16 58
#> 2 0.1204333 0.8 38 12 6 6 6 10 22 82
#> 3 0.1406888 0.8 52 14 8 8 8 12 28 110
#> 4 0.1610295 0.8 66 18 10 8 10 16 36 144
#> 5 0.1814679 0.8 84 24 12 10 12 20 44 182
#> 6 0.2020168 0.8 102 28 14 12 14 24 56 224
#> 7 0.2226890 0.8 124 34 18 14 18 30 66 272
#> 8 0.2434978 0.8 148 40 20 16 20 34 78 322
#> 9 0.2644565 0.8 172 46 24 20 24 40 92 378
#> 10 0.2855787 0.8 200 54 28 22 26 46 106 438
#> 11 0.3068783 0.8 228 62 30 26 30 52 122 502
#> 12 0.3283695 0.8 260 70 34 28 34 60 138 572
#> 13 0.3500668 0.8 294 80 40 32 38 68 156 646
#> 14 0.3719851 0.8 328 88 44 36 42 76 174 722
#> 15 0.3941398 0.8 366 98 48 40 48 84 194 806
#> 16 0.4165464 0.8 406 108 54 44 52 92 216 892
#> 17 0.1002505 0.9 36 12 6 6 6 10 20 78
#> 18 0.1204333 0.9 52 16 8 6 8 14 28 112
#> 19 0.1406888 0.9 70 20 10 8 10 18 38 152
#> 20 0.1610295 0.9 92 26 14 10 12 22 50 200
#> 21 0.1814679 0.9 116 32 16 12 16 28 62 252
#> 22 0.2020168 0.9 142 38 20 16 18 34 76 310
#> 23 0.2226890 0.9 170 46 24 18 22 40 92 374
#> 24 0.2434978 0.9 204 56 28 20 26 48 108 446
#> 25 0.2644565 0.9 238 64 32 24 30 54 126 522
#> 26 0.2855787 0.9 276 74 36 28 36 64 146 606
#> 27 0.3068783 0.9 316 86 42 32 40 72 168 696
#> 28 0.3283695 0.9 360 96 46 36 46 82 192 792
#> 29 0.3500668 0.9 406 108 52 40 52 92 216 892
#> 30 0.3719851 0.9 454 122 58 44 58 104 242 1000
#> 31 0.3941398 0.9 506 136 64 50 64 116 268 1114
#> 32 0.4165464 0.9 562 150 72 54 70 128 298 1236