Simulation experimental design

Published

April 15, 2025

The simulation has 1920 respondents and 500 runs. The simulation itself took 1.7099153^{4} seconds.

the parameters used for the simulation are:

Statistics and power

Here you see the statistics of your parameters for the 500 runs.

kable(all_designs[["summaryall"]] ,digits = 3) %>% kable_styling()
parname DesignBayesian1.n interaction.n interaFiltereddumm.n interaFiltereddumm2bl.n interaFiltered.n truepar DesignBayesian1.mean interaction.mean interaFiltereddumm.mean interaFiltereddumm2bl.mean interaFiltered.mean DesignBayesian1.sd interaction.sd interaFiltereddumm.sd interaFiltereddumm2bl.sd interaFiltered.sd DesignBayesian1.min interaction.min interaFiltereddumm.min interaFiltereddumm2bl.min interaFiltered.min DesignBayesian1.max interaction.max interaFiltereddumm.max interaFiltereddumm2bl.max interaFiltered.max DesignBayesian1.range interaction.range interaFiltereddumm.range interaFiltereddumm2bl.range interaFiltered.range DesignBayesian1.se interaction.se interaFiltereddumm.se interaFiltereddumm2bl.se interaFiltered.se DesignBayesian1.median DesignBayesian1.skew DesignBayesian1.kurtosis interaction.median interaction.skew interaction.kurtosis interaFiltereddumm.median interaFiltereddumm.skew interaFiltereddumm.kurtosis interaFiltereddumm2bl.median interaFiltereddumm2bl.skew interaFiltereddumm2bl.kurtosis interaFiltered.median interaFiltered.skew interaFiltered.kurtosis
bx12 500 500 500 500 500 -0.250 -0.251 -0.251 -0.249 -0.249 -0.255 0.102 0.060 0.063 0.065 0.063 -0.543 -0.408 -0.455 -0.430 -0.441 0.059 -0.064 -0.054 -0.094 -0.104 0.602 0.344 0.401 0.337 0.337 0.005 0.003 0.003 0.003 0.003 -0.248 -0.035 -0.210 -0.251 0.096 -0.168 -0.246 -0.114 0.091 -0.247 -0.063 -0.228 -0.252 -0.202 -0.034
bx13 500 500 500 500 500 -0.500 -0.498 -0.501 -0.497 -0.494 -0.500 0.092 0.123 0.063 0.065 0.053 -0.788 -0.881 -0.689 -0.707 -0.635 -0.247 -0.122 -0.300 -0.305 -0.329 0.542 0.759 0.389 0.402 0.306 0.004 0.006 0.003 0.003 0.002 -0.499 -0.190 0.127 -0.500 0.093 0.050 -0.495 -0.114 0.021 -0.496 0.030 0.050 -0.501 0.011 -0.322
bx14 500 500 500 500 500 -0.600 -0.596 -0.601 -0.599 -0.601 -0.599 0.097 0.076 0.062 0.051 0.065 -0.849 -0.816 -0.786 -0.789 -0.871 -0.188 -0.374 -0.422 -0.453 -0.357 0.661 0.441 0.364 0.336 0.514 0.004 0.003 0.003 0.002 0.003 -0.591 0.083 0.246 -0.600 0.023 -0.082 -0.599 -0.090 -0.057 -0.598 -0.081 0.208 -0.602 -0.024 0.470
bx15 500 500 500 500 500 -0.700 -0.697 -0.701 -0.697 -0.694 -0.700 0.092 0.085 0.067 0.063 0.075 -0.943 -0.979 -0.966 -0.892 -0.924 -0.411 -0.470 -0.463 -0.520 -0.466 0.532 0.509 0.503 0.372 0.459 0.004 0.004 0.003 0.003 0.003 -0.699 0.174 -0.180 -0.701 -0.117 -0.234 -0.697 -0.026 0.284 -0.689 -0.067 0.010 -0.699 0.075 0.019
bx2 500 500 500 500 500 -0.509 -0.512 -0.509 -0.504 -0.510 -0.510 0.061 0.036 0.047 0.048 0.031 -0.685 -0.627 -0.640 -0.662 -0.601 -0.335 -0.394 -0.349 -0.378 -0.392 0.350 0.234 0.291 0.285 0.209 0.003 0.002 0.002 0.002 0.001 -0.514 0.111 -0.076 -0.509 -0.064 0.077 -0.503 -0.046 0.026 -0.512 -0.010 -0.020 -0.509 0.170 0.323
bx3 500 500 500 500 500 0.362 0.366 0.362 0.361 0.369 0.362 0.072 0.032 0.046 0.051 0.026 0.147 0.264 0.225 0.240 0.291 0.574 0.473 0.515 0.492 0.433 0.427 0.209 0.290 0.252 0.142 0.003 0.001 0.002 0.002 0.001 0.362 0.205 -0.022 0.363 -0.057 0.137 0.363 0.002 0.289 0.367 0.087 -0.298 0.363 0.007 0.000
bx4 500 500 500 500 500 -0.021 -0.021 -0.021 -0.021 -0.021 -0.021 0.001 0.000 0.001 0.001 0.001 -0.023 -0.022 -0.022 -0.022 -0.022 -0.018 -0.019 -0.019 -0.019 -0.019 0.005 0.003 0.003 0.003 0.003 0.000 0.000 0.000 0.000 0.000 -0.021 0.069 0.013 -0.021 -0.073 0.282 -0.021 0.099 -0.139 -0.021 0.158 -0.151 -0.021 -0.014 -0.132
bx1x22 500 500 500 500 500 0.334 0.340 0.333 0.329 0.339 0.337 0.082 0.065 0.066 0.063 0.120 0.049 0.118 0.079 0.153 -0.027 0.591 0.529 0.535 0.519 0.683 0.542 0.411 0.456 0.366 0.711 0.004 0.003 0.003 0.003 0.005 0.343 -0.169 -0.092 0.336 -0.092 0.078 0.329 -0.067 0.358 0.340 0.090 -0.020 0.333 -0.002 -0.045
bx1x23 500 500 500 500 500 0.300 0.306 0.303 0.295 0.298 0.302 0.089 0.074 0.066 0.059 0.062 0.045 0.090 0.127 0.134 0.122 0.594 0.491 0.489 0.483 0.494 0.549 0.401 0.362 0.349 0.372 0.004 0.003 0.003 0.003 0.003 0.306 0.005 -0.028 0.299 -0.032 -0.213 0.295 0.121 -0.241 0.298 0.015 -0.225 0.301 -0.062 -0.073
bx1x24 500 500 500 500 500 0.300 0.302 0.301 0.295 0.304 0.305 0.124 0.084 0.071 0.066 0.092 -0.112 0.051 0.076 0.082 -0.033 0.752 0.607 0.518 0.550 0.536 0.864 0.556 0.442 0.467 0.569 0.006 0.004 0.003 0.003 0.004 0.302 -0.028 -0.012 0.304 0.001 0.435 0.297 -0.086 -0.017 0.306 0.064 0.208 0.305 -0.146 0.281
bx1x25 500 500 500 500 500 0.300 0.303 0.296 0.295 0.300 0.000 0.088 0.091 0.066 0.067 0.000 0.058 -0.026 0.084 0.092 0.000 0.549 0.630 0.489 0.525 0.000 0.491 0.656 0.404 0.433 0.000 0.004 0.004 0.003 0.003 0.000 0.309 -0.054 -0.192 0.294 0.163 0.334 0.292 0.015 0.141 0.297 0.222 -0.016 0.000 NaN NaN
bx1x32 500 500 500 500 500 0.334 0.334 0.339 0.338 0.329 0.337 0.099 0.074 0.065 0.069 0.109 0.033 0.110 0.159 0.121 0.038 0.675 0.566 0.513 0.521 0.637 0.643 0.455 0.354 0.399 0.599 0.004 0.003 0.003 0.003 0.005 0.335 0.119 -0.002 0.337 0.029 -0.121 0.336 0.021 -0.265 0.333 -0.110 0.052 0.335 0.091 -0.223
bx1x33 500 500 500 500 500 0.300 0.296 0.300 0.302 0.291 0.296 0.097 0.110 0.066 0.068 0.069 0.002 0.001 0.094 0.089 0.127 0.597 0.622 0.477 0.500 0.484 0.594 0.621 0.383 0.411 0.357 0.004 0.005 0.003 0.003 0.003 0.298 0.081 0.177 0.296 0.058 -0.198 0.300 -0.101 -0.046 0.288 0.020 -0.274 0.299 0.028 -0.373
bx1x34 500 500 500 500 500 0.300 0.284 0.302 0.303 0.292 0.295 0.164 0.087 0.064 0.067 0.098 -0.209 0.041 0.059 0.094 -0.004 0.760 0.536 0.537 0.475 0.626 0.969 0.495 0.479 0.382 0.630 0.007 0.004 0.003 0.003 0.004 0.292 -0.062 -0.050 0.298 0.036 0.004 0.304 0.012 0.219 0.290 -0.047 -0.096 0.299 -0.053 -0.152
bx1x35 500 500 500 500 500 0.300 0.294 0.305 0.303 0.291 0.300 0.092 0.098 0.075 0.065 0.093 0.055 0.072 -0.031 0.034 0.054 0.628 0.584 0.538 0.453 0.572 0.573 0.512 0.570 0.419 0.518 0.004 0.004 0.003 0.003 0.004 0.293 0.020 -0.096 0.305 0.063 -0.331 0.304 -0.050 0.430 0.293 -0.098 0.084 0.299 0.117 -0.259
bsq 500 500 500 500 500 -1.325 -1.321 -1.323 -1.322 -1.321 -1.327 0.135 0.035 0.054 0.053 0.037 -1.698 -1.422 -1.479 -1.481 -1.444 -0.736 -1.205 -1.166 -1.174 -1.223 0.963 0.217 0.313 0.307 0.220 0.006 0.002 0.002 0.002 0.002 -1.318 0.125 0.239 -1.322 0.022 0.199 -1.321 -0.131 -0.018 -1.321 0.035 -0.104 -1.327 0.042 -0.145
rob_pval0_bx12 500 500 500 500 0 NA 0.075 0.002 0.003 0.004 NaN 0.145 0.015 0.024 0.015 NA 0.000 0.000 0.000 0.000 Inf 0.990 0.270 0.350 0.130 -Inf 0.990 0.270 0.350 0.130 -Inf 0.007 0.001 0.001 0.001 NA 0.010 3.248 12.886 0.000 13.474 229.608 0.000 12.073 164.322 0.000 5.516 35.156 NA NA NA
rob_pval0_bx13 500 500 500 500 0 NA 0.000 0.003 0.000 0.000 NaN 0.000 0.018 0.000 0.000 NA 0.000 0.000 0.000 0.000 Inf 0.010 0.290 0.000 0.000 -Inf 0.010 0.290 0.000 0.000 -Inf 0.000 0.001 0.000 0.000 NA 0.000 22.227 493.012 0.000 10.408 137.124 0.000 NaN NaN 0.000 NaN NaN NA NA NA
rob_pval0_bx14 500 500 500 500 0 NA 0.000 0.000 0.000 0.000 NaN 0.002 0.000 0.000 0.000 NA 0.000 0.000 0.000 0.000 Inf 0.040 0.000 0.000 0.000 -Inf 0.040 0.000 0.000 0.000 -Inf 0.000 0.000 0.000 0.000 NA 0.000 22.227 493.012 0.000 NaN NaN 0.000 NaN NaN 0.000 NaN NaN NA NA NA
rob_pval0_bx15 500 500 500 500 0 NA 0.000 0.000 0.000 0.000 NaN 0.000 0.000 0.000 0.000 NA 0.000 0.000 0.000 0.000 Inf 0.000 0.000 0.000 0.000 -Inf 0.000 0.000 0.000 0.000 -Inf 0.000 0.000 0.000 0.000 NA 0.000 NaN NaN 0.000 NaN NaN 0.000 NaN NaN 0.000 NaN NaN NA NA NA
rob_pval0_bx2 500 500 500 500 0 NA 0.000 0.000 0.000 0.000 NaN 0.000 0.000 0.000 0.000 NA 0.000 0.000 0.000 0.000 Inf 0.000 0.000 0.000 0.000 -Inf 0.000 0.000 0.000 0.000 -Inf 0.000 0.000 0.000 0.000 NA 0.000 NaN NaN 0.000 NaN NaN 0.000 NaN NaN 0.000 NaN NaN NA NA NA
rob_pval0_bx3 500 500 500 500 0 NA 0.000 0.000 0.000 0.000 NaN 0.002 0.000 0.000 0.000 NA 0.000 0.000 0.000 0.000 Inf 0.040 0.000 0.000 0.000 -Inf 0.040 0.000 0.000 0.000 -Inf 0.000 0.000 0.000 0.000 NA 0.000 17.960 352.808 0.000 NaN NaN 0.000 NaN NaN 0.000 NaN NaN NA NA NA
rob_pval0_bx4 500 500 500 500 0 NA 0.000 0.000 0.000 0.000 NaN 0.000 0.000 0.000 0.000 NA 0.000 0.000 0.000 0.000 Inf 0.000 0.000 0.000 0.000 -Inf 0.000 0.000 0.000 0.000 -Inf 0.000 0.000 0.000 0.000 NA 0.000 NaN NaN 0.000 NaN NaN 0.000 NaN NaN 0.000 NaN NaN NA NA NA
rob_pval0_bx1x22 500 500 500 500 0 NA 0.004 0.000 0.001 0.000 NaN 0.030 0.005 0.010 0.001 NA 0.000 0.000 0.000 0.000 Inf 0.560 0.080 0.220 0.020 -Inf 0.560 0.080 0.220 0.020 -Inf 0.001 0.000 0.000 0.000 NA 0.000 14.856 247.270 0.000 14.143 214.776 0.000 19.420 403.166 0.000 17.863 333.781 NA NA NA
rob_pval0_bx1x23 500 500 500 500 0 NA 0.014 0.003 0.001 0.000 NaN 0.051 0.018 0.004 0.002 NA 0.000 0.000 0.000 0.000 Inf 0.600 0.220 0.050 0.030 -Inf 0.600 0.220 0.050 0.030 -Inf 0.002 0.001 0.000 0.000 NA 0.000 6.409 51.275 0.000 8.212 77.475 0.000 8.470 87.184 0.000 10.697 119.682 NA NA NA
rob_pval0_bx1x24 500 500 500 500 0 NA 0.078 0.012 0.003 0.001 NaN 0.153 0.049 0.017 0.012 NA 0.000 0.000 0.000 0.000 Inf 0.930 0.550 0.270 0.230 -Inf 0.930 0.550 0.270 0.230 -Inf 0.007 0.002 0.001 0.001 NA 0.010 2.827 8.374 0.000 6.796 53.143 0.000 10.856 146.378 0.000 15.942 280.724 NA NA NA
rob_pval0_bx1x25 500 500 500 500 0 NA 0.012 0.020 0.002 0.001 NaN 0.044 0.068 0.015 0.008 NA 0.000 0.000 0.000 0.000 Inf 0.480 0.780 0.220 0.150 -Inf 0.480 0.780 0.220 0.150 -Inf 0.002 0.003 0.001 0.000 NA 0.000 6.294 48.790 0.000 7.626 71.412 0.000 10.355 125.449 0.000 15.398 252.588 NA NA NA
rob_pval0_bx1x32 500 500 500 500 0 NA 0.016 0.001 0.000 0.001 NaN 0.055 0.007 0.001 0.005 NA 0.000 0.000 0.000 0.000 Inf 0.760 0.140 0.010 0.080 -Inf 0.760 0.140 0.010 0.080 -Inf 0.002 0.000 0.000 0.000 NA 0.000 7.732 80.712 0.000 15.103 265.905 0.000 11.013 119.517 0.000 10.776 132.162 NA NA NA
rob_pval0_bx1x33 500 500 500 500 0 NA 0.032 0.047 0.001 0.002 NaN 0.093 0.114 0.008 0.012 NA 0.000 0.000 0.000 0.000 Inf 0.980 0.990 0.130 0.210 -Inf 0.980 0.990 0.130 0.210 -Inf 0.004 0.005 0.000 0.001 NA 0.000 5.759 41.212 0.000 4.090 20.316 0.000 12.102 167.312 0.000 12.442 204.501 NA NA NA
rob_pval0_bx1x34 500 500 500 500 0 NA 0.212 0.011 0.001 0.002 NaN 0.256 0.047 0.017 0.012 NA 0.000 0.000 0.000 0.000 Inf 0.980 0.610 0.380 0.190 -Inf 0.980 0.610 0.380 0.190 -Inf 0.011 0.002 0.001 0.001 NA 0.090 1.404 1.003 0.000 7.584 72.371 0.000 21.364 466.431 0.000 10.436 140.865 NA NA NA
rob_pval0_bx1x35 500 500 500 500 0 NA 0.022 0.030 0.004 0.002 NaN 0.061 0.073 0.033 0.028 NA 0.000 0.000 0.000 0.000 Inf 0.550 0.490 0.660 0.610 -Inf 0.550 0.490 0.660 0.610 -Inf 0.003 0.003 0.001 0.001 NA 0.000 4.730 27.522 0.000 3.908 16.775 0.000 17.056 320.628 0.000 20.541 440.673 NA NA NA
rob_pval0_bsq 500 500 500 500 0 NA 0.000 0.000 0.000 0.000 NaN 0.000 0.000 0.000 0.000 NA 0.000 0.000 0.000 0.000 Inf 0.000 0.000 0.000 0.000 -Inf 0.000 0.000 0.000 0.000 -Inf 0.000 0.000 0.000 0.000 NA 0.000 NaN NaN 0.000 NaN NaN 0.000 NaN NaN 0.000 NaN NaN NA NA NA 
all_designs[["powa"]]
$DesignBayesian1

FALSE  TRUE 
   85    15 

$interaction

FALSE  TRUE 
 45.6  54.4 

$interaFiltereddumm

FALSE  TRUE 
  6.6  93.4 

$interaFiltereddumm2bl

FALSE  TRUE 
  6.8  93.2 

$interaFiltered
numeric(0)

$time
NULL

$arguements
NULL

Illustration of simulated parameter values

To facilitate interpretation and judgement of the different designs, you can plot the densities of simulated parameter values from the different experimental designs.

$bx12


$bx13


$bx14


$bx15


$bx2


$bx3


$bx4


$bx1x22


$bx1x23


$bx1x24


$bx1x25


$bx1x32


$bx1x33


$bx1x34


$bx1x35


$bsq


$bl.bx12


$bl.bx13


$bl.bx14


$bl.bx15


$bl.bx2


$bl.bx3


$bl.bx4


$bl.bx1x22


$bl.bx1x23


$bl.bx1x24


$bl.bx1x25


$bl.bx1x32


$bl.bx1x33


$bl.bx1x34


$bl.bx1x35


$bl.bsq