Computes an IRT version of the "reliable change index" (RCI) proposed by
Jacobson and Traux (1991) but modified to use IRT information about scores
and measurement error (see Jabrayilov, Emons, and Sijtsma (2016)).
Main benefit of the IRT approach is the inclusion
of response pattern information in the pre/post data score estimates, as well
as conditional standard error of measurement information. Models can be specified
as separate unidimensional IRT models fitted via mirt
(or extracted from multipleGroup via extract.group),
or a two-dimensional model where the latent traits correspond to the two
test administrations.
Usage
RCI(
mod_pre,
predat,
postdat,
mod_post = mod_pre,
cutoffs = NULL,
SEM.pre = NULL,
SEM.post = NULL,
Fisher = FALSE,
zero_cor = TRUE,
shiny = FALSE,
main = "Test Scores",
...
)Arguments
- mod_pre
single-group model fitted by
mirt. If not supplied the information will be extracted from the data input objects to compute the classical test theory version of the RCI statistics- predat
a vector (if one individual) or matrix/data.frame of response data to be scored, where each individuals' responses are included in exactly one row
- postdat
same as
predat, but with respect to the post/follow-up measurement. Ignored when a two-dimensional IRT model is included- mod_post
(optional) IRT model for post-test if different from pre-test; otherwise, the pre-test model will be used. Ignored when a two-dimensional model IRT is included
- cutoffs
optional vector of length 2 indicating the type of cut-offs to report (e.g.,
c(-1.96, 1.96)reflects the 95 percent z-score type cut-off)- SEM.pre
standard error of measurement for the pretest. This can be used instead of
rxx.preandSD.pre- SEM.post
(optional) standard error of measurement for the post-test. Using this will create a pooled version of the SEM; otherwise,
SEM.post = SEM.pre- Fisher
logical; use the Fisher/expected information function to compute the SE terms? If
FALSEthe SE information will be extracted from the selectfscoresmethod (default). Only applicable for unidimensional models- zero_cor
logical; when the supplied
mod_preis a two-factor model should the covariance/correlation between the latent traits be forced to be 0?- shiny
logical; launch an interactive shiny applications for real-time scoring of supplied total-scores or response vectors? Only requires
mod_preand (optional)mod_postinputs- main
main label to use when
shiny=TRUE- ...
additional arguments passed to
fscores
References
Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi:10.18637/jss.v048.i06
Jacobson, N. S., & Truax, P. (1991). Clinical significance: A statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting and Clinical Psychology, 59, 12-19.
Jabrayilov, R. , Emons, W. H. M., & Sijtsma, K. (2016). Comparison of Classical Test Theory and Item Response Theory in Individual Change Assessment. Applied Psychological Measurement, 40 (8), 559-572.
Author
Phil Chalmers rphilip.chalmers@gmail.com
Examples
# \donttest{
# simulate some data
N <- 1000
J <- 20 # number of items
a <- matrix(rlnorm(J,.2,.3))
d <- rnorm(J)
theta <- matrix(rnorm(N))
dat_pre <- simdata(a, d, itemtype = '2PL', Theta = theta)
# first 3 cases decrease by 1/2
theta2 <- theta - c(1/2, 1/2, 1/2, numeric(N-3))
dat_post <- simdata(a, d, itemtype = '2PL', Theta = theta2)
mod <- mirt(dat_pre)
#>
Iteration: 1, Log-Lik: -11848.997, Max-Change: 0.48471
Iteration: 2, Log-Lik: -11719.251, Max-Change: 0.21609
Iteration: 3, Log-Lik: -11696.214, Max-Change: 0.10753
Iteration: 4, Log-Lik: -11689.085, Max-Change: 0.06517
Iteration: 5, Log-Lik: -11686.169, Max-Change: 0.04134
Iteration: 6, Log-Lik: -11684.947, Max-Change: 0.02707
Iteration: 7, Log-Lik: -11684.104, Max-Change: 0.00965
Iteration: 8, Log-Lik: -11684.039, Max-Change: 0.00629
Iteration: 9, Log-Lik: -11684.008, Max-Change: 0.00442
Iteration: 10, Log-Lik: -11683.981, Max-Change: 0.00157
Iteration: 11, Log-Lik: -11683.979, Max-Change: 0.00086
Iteration: 12, Log-Lik: -11683.979, Max-Change: 0.00048
Iteration: 13, Log-Lik: -11683.978, Max-Change: 0.00049
Iteration: 14, Log-Lik: -11683.978, Max-Change: 0.00026
Iteration: 15, Log-Lik: -11683.978, Max-Change: 0.00025
Iteration: 16, Log-Lik: -11683.978, Max-Change: 0.00019
Iteration: 17, Log-Lik: -11683.978, Max-Change: 0.00011
Iteration: 18, Log-Lik: -11683.978, Max-Change: 0.00010
Iteration: 19, Log-Lik: -11683.978, Max-Change: 0.00007
# all changes using fitted model from pre data
RCI(mod, predat=dat_pre, postdat=dat_post)
#> pre.score post.score converged diff SE z p
#> 1 0.785 -0.266 TRUE -1.051 0.529 -1.986 0.047
#> 2 -1.019 -2.281 TRUE -1.261 0.708 -1.782 0.075
#> 3 -1.230 -1.577 TRUE -0.346 0.633 -0.547 0.584
#> 4 -0.749 -1.150 TRUE -0.401 0.556 -0.722 0.47
#> 5 -1.119 -0.949 TRUE 0.170 0.566 0.301 0.763
#> 6 -0.892 -0.725 TRUE 0.167 0.534 0.313 0.755
#> 7 -1.478 -0.586 TRUE 0.892 0.582 1.532 0.126
#> 8 0.312 0.137 TRUE -0.175 0.502 -0.348 0.728
#> 9 1.252 0.938 TRUE -0.314 0.619 -0.507 0.612
#> 10 0.894 1.118 TRUE 0.225 0.602 0.373 0.709
#> 11 0.422 0.487 TRUE 0.065 0.521 0.125 0.901
#> 12 0.786 0.105 TRUE -0.681 0.530 -1.283 0.199
#> 13 0.103 0.071 TRUE -0.032 0.494 -0.064 0.949
#> 14 -0.326 -1.368 TRUE -1.043 0.563 -1.852 0.064
#> 15 -0.752 -0.853 TRUE -0.100 0.533 -0.188 0.851
#> 16 0.299 0.357 TRUE 0.058 0.509 0.114 0.909
#> 17 0.401 0.125 TRUE -0.276 0.506 -0.547 0.585
#> 18 -2.281 -1.224 TRUE 1.057 0.721 1.465 0.143
#> 19 -0.801 -0.648 TRUE 0.154 0.525 0.293 0.769
#> 20 -1.210 -1.152 TRUE 0.058 0.589 0.099 0.921
#> 21 0.950 0.222 TRUE -0.727 0.548 -1.328 0.184
#> 22 0.249 0.403 TRUE 0.154 0.509 0.302 0.763
#> 23 0.266 -0.230 TRUE -0.496 0.498 -0.996 0.319
#> 24 1.536 1.203 TRUE -0.333 0.676 -0.493 0.622
#> 25 -1.606 -1.396 TRUE 0.210 0.651 0.322 0.747
#> 26 0.083 0.445 TRUE 0.362 0.507 0.714 0.475
#> 27 1.004 0.560 TRUE -0.444 0.567 -0.783 0.433
#> 28 0.569 0.665 TRUE 0.096 0.539 0.178 0.859
#> 29 0.337 0.976 TRUE 0.639 0.554 1.153 0.249
#> 30 -0.026 -0.534 TRUE -0.508 0.499 -1.017 0.309
#> 31 0.516 0.225 TRUE -0.291 0.514 -0.566 0.571
#> 32 -1.354 -1.455 TRUE -0.101 0.631 -0.161 0.872
#> 33 -0.274 0.254 TRUE 0.528 0.498 1.059 0.289
#> 34 1.348 1.515 TRUE 0.167 0.689 0.242 0.808
#> 35 -0.783 0.035 TRUE 0.819 0.512 1.598 0.11
#> 36 1.536 1.447 TRUE -0.089 0.702 -0.127 0.899
#> 37 0.011 -0.586 TRUE -0.597 0.502 -1.190 0.234
#> 38 1.085 0.351 TRUE -0.734 0.566 -1.298 0.194
#> 39 -0.206 -1.473 TRUE -1.267 0.573 -2.210 0.027
#> 40 -2.281 -1.677 TRUE 0.603 0.761 0.793 0.428
#> 41 0.223 -0.096 TRUE -0.319 0.496 -0.644 0.52
#> 42 1.807 2.071 TRUE 0.264 0.808 0.326 0.744
#> 43 0.089 -0.010 TRUE -0.099 0.493 -0.201 0.841
#> 44 -0.999 -1.345 TRUE -0.346 0.590 -0.586 0.558
#> 45 0.868 0.801 TRUE -0.067 0.571 -0.117 0.907
#> 46 -0.384 0.063 TRUE 0.447 0.495 0.902 0.367
#> 47 1.243 1.257 TRUE 0.014 0.649 0.021 0.983
#> 48 0.306 -0.314 TRUE -0.620 0.501 -1.238 0.216
#> 49 2.071 1.082 TRUE -0.988 0.736 -1.343 0.179
#> 50 -0.239 -0.666 TRUE -0.428 0.505 -0.846 0.397
#> 51 -0.326 0.058 TRUE 0.384 0.494 0.777 0.437
#> 52 -0.689 -1.082 TRUE -0.393 0.547 -0.718 0.473
#> 53 0.319 -0.093 TRUE -0.412 0.499 -0.825 0.409
#> 54 -0.662 -0.058 TRUE 0.604 0.505 1.198 0.231
#> 55 -0.447 -0.653 TRUE -0.206 0.509 -0.404 0.686
#> 56 -0.384 -0.340 TRUE 0.044 0.496 0.090 0.929
#> 57 -0.995 -0.549 TRUE 0.446 0.534 0.835 0.404
#> 58 -0.061 -1.562 TRUE -1.501 0.583 -2.573 0.01
#> 59 0.367 -0.224 TRUE -0.591 0.502 -1.177 0.239
#> 60 1.450 1.173 TRUE -0.277 0.663 -0.418 0.676
#> 61 -0.624 -0.567 TRUE 0.058 0.512 0.113 0.91
#> 62 0.737 1.029 TRUE 0.292 0.581 0.503 0.615
#> 63 -0.071 0.082 TRUE 0.153 0.493 0.311 0.756
#> 64 -0.632 -0.554 TRUE 0.078 0.512 0.152 0.88
#> 65 -1.718 -0.560 TRUE 1.158 0.610 1.897 0.058
#> 66 -0.602 -1.203 TRUE -0.601 0.554 -1.085 0.278
#> 67 -0.919 -1.376 TRUE -0.457 0.588 -0.778 0.437
#> 68 -0.325 0.111 TRUE 0.437 0.495 0.882 0.378
#> 69 0.044 1.182 TRUE 1.138 0.568 2.002 0.045
#> 70 -0.040 0.234 TRUE 0.274 0.497 0.552 0.581
#> 71 1.751 1.457 TRUE -0.293 0.729 -0.403 0.687
#> 72 0.871 1.001 TRUE 0.129 0.588 0.220 0.826
#> 73 -0.249 -0.999 TRUE -0.750 0.527 -1.423 0.155
#> 74 -0.576 -0.248 TRUE 0.328 0.501 0.655 0.512
#> 75 -0.710 -0.974 TRUE -0.264 0.540 -0.489 0.625
#> 76 1.013 1.163 TRUE 0.150 0.617 0.244 0.807
#> 77 -0.329 -0.551 TRUE -0.222 0.501 -0.443 0.658
#> 78 -0.005 -0.275 TRUE -0.270 0.492 -0.548 0.584
#> 79 2.071 1.457 TRUE -0.613 0.770 -0.796 0.426
#> 80 -0.691 -0.478 TRUE 0.213 0.512 0.416 0.678
#> 81 1.006 1.103 TRUE 0.098 0.610 0.160 0.873
#> 82 -0.311 0.224 TRUE 0.535 0.498 1.076 0.282
#> 83 -0.674 -0.385 TRUE 0.289 0.508 0.569 0.57
#> 84 0.969 0.630 TRUE -0.339 0.568 -0.596 0.551
#> 85 1.092 0.376 TRUE -0.717 0.567 -1.264 0.206
#> 86 -1.047 -0.952 TRUE 0.095 0.560 0.170 0.865
#> 87 0.072 -0.019 TRUE -0.091 0.493 -0.186 0.853
#> 88 1.229 0.879 TRUE -0.350 0.612 -0.572 0.568
#> 89 1.108 -0.060 TRUE -1.169 0.559 -2.090 0.037
#> 90 0.303 -0.365 TRUE -0.667 0.502 -1.330 0.183
#> 91 0.268 0.774 TRUE 0.506 0.534 0.949 0.343
#> 92 0.476 0.579 TRUE 0.103 0.529 0.196 0.845
#> 93 -1.195 -1.507 TRUE -0.312 0.622 -0.502 0.616
#> 94 0.452 0.488 TRUE 0.036 0.522 0.069 0.945
#> 95 -0.585 -0.213 TRUE 0.372 0.501 0.741 0.459
#> 96 -0.430 -0.035 TRUE 0.395 0.496 0.798 0.425
#> 97 0.380 -0.206 TRUE -0.586 0.502 -1.167 0.243
#> 98 -0.401 -0.959 TRUE -0.558 0.527 -1.059 0.29
#> 99 -0.047 0.063 TRUE 0.110 0.492 0.223 0.823
#> 100 -1.088 -0.917 TRUE 0.171 0.561 0.305 0.76
#> 101 -1.000 -0.142 TRUE 0.858 0.526 1.629 0.103
#> 102 -1.081 -2.281 TRUE -1.200 0.711 -1.686 0.092
#> 103 0.065 0.052 TRUE -0.014 0.493 -0.028 0.978
#> 104 1.035 1.721 TRUE 0.686 0.685 1.002 0.317
#> 105 -0.656 -0.919 TRUE -0.263 0.533 -0.493 0.622
#> 106 -1.147 -0.947 TRUE 0.200 0.568 0.352 0.725
#> 107 -1.024 -0.663 TRUE 0.361 0.541 0.667 0.505
#> 108 -0.309 0.064 TRUE 0.373 0.494 0.756 0.45
#> 109 0.499 -0.074 TRUE -0.573 0.508 -1.127 0.26
#> 110 -0.712 -1.059 TRUE -0.347 0.546 -0.635 0.525
#> 111 0.760 1.792 TRUE 1.032 0.674 1.530 0.126
#> 112 0.018 -0.212 TRUE -0.230 0.492 -0.468 0.64
#> 113 0.193 0.114 TRUE -0.079 0.497 -0.159 0.874
#> 114 -1.378 -1.607 TRUE -0.229 0.650 -0.353 0.724
#> 115 -0.567 -0.700 TRUE -0.133 0.515 -0.257 0.797
#> 116 1.206 0.659 TRUE -0.547 0.594 -0.921 0.357
#> 117 -1.184 -1.873 TRUE -0.689 0.665 -1.037 0.3
#> 118 -0.005 0.609 TRUE 0.614 0.516 1.190 0.234
#> 119 -1.306 -0.748 TRUE 0.558 0.571 0.977 0.329
#> 120 0.738 0.379 TRUE -0.359 0.535 -0.671 0.502
#> 121 -0.433 -0.213 TRUE 0.220 0.496 0.444 0.657
#> 122 0.709 1.243 TRUE 0.534 0.601 0.888 0.375
#> 123 -1.454 -0.870 TRUE 0.585 0.593 0.985 0.325
#> 124 0.224 0.840 TRUE 0.616 0.538 1.146 0.252
#> 125 0.795 0.277 TRUE -0.518 0.536 -0.968 0.333
#> 126 -0.269 -0.957 TRUE -0.688 0.524 -1.313 0.189
#> 127 -1.404 -1.765 TRUE -0.361 0.670 -0.539 0.59
#> 128 0.806 0.259 TRUE -0.547 0.536 -1.021 0.307
#> 129 -0.246 -1.636 TRUE -1.390 0.593 -2.344 0.019
#> 130 0.159 0.315 TRUE 0.156 0.503 0.310 0.757
#> 131 -0.921 -1.426 TRUE -0.504 0.593 -0.850 0.396
#> 132 -1.071 -0.653 TRUE 0.418 0.545 0.767 0.443
#> 133 -1.670 -1.455 TRUE 0.215 0.664 0.323 0.747
#> 134 0.822 0.389 TRUE -0.432 0.542 -0.798 0.425
#> 135 2.071 1.375 TRUE -0.696 0.762 -0.913 0.361
#> 136 0.712 0.442 TRUE -0.270 0.536 -0.503 0.615
#> 137 0.049 0.663 TRUE 0.614 0.520 1.181 0.237
#> 138 1.325 0.603 TRUE -0.722 0.604 -1.194 0.232
#> 139 0.201 0.788 TRUE 0.587 0.533 1.101 0.271
#> 140 0.163 0.006 TRUE -0.157 0.495 -0.317 0.752
#> 141 -1.160 -2.035 TRUE -0.875 0.684 -1.280 0.201
#> 142 1.124 2.071 TRUE 0.947 0.739 1.281 0.2
#> 143 0.599 0.723 TRUE 0.123 0.545 0.226 0.821
#> 144 -1.073 -0.970 TRUE 0.103 0.563 0.183 0.854
#> 145 0.059 0.813 TRUE 0.754 0.532 1.418 0.156
#> 146 0.956 1.055 TRUE 0.098 0.601 0.164 0.87
#> 147 0.142 -0.430 TRUE -0.572 0.498 -1.148 0.251
#> 148 -0.386 0.488 TRUE 0.874 0.511 1.711 0.087
#> 149 -0.267 -0.610 TRUE -0.343 0.503 -0.682 0.495
#> 150 1.261 0.680 TRUE -0.582 0.602 -0.967 0.333
#> 151 0.920 1.059 TRUE 0.139 0.598 0.232 0.816
#> 152 0.560 0.059 TRUE -0.500 0.513 -0.975 0.329
#> 153 0.506 0.254 TRUE -0.252 0.515 -0.490 0.624
#> 154 -0.864 -0.831 TRUE 0.034 0.539 0.063 0.95
#> 155 -2.281 -2.038 TRUE 0.243 0.799 0.304 0.761
#> 156 -0.648 -1.664 TRUE -1.015 0.607 -1.673 0.094
#> 157 -0.130 -0.630 TRUE -0.500 0.503 -0.993 0.32
#> 158 0.169 1.519 TRUE 1.350 0.612 2.206 0.027
#> 159 -0.523 -0.695 TRUE -0.172 0.513 -0.335 0.738
#> 160 -0.430 -0.589 TRUE -0.159 0.505 -0.314 0.754
#> 161 -1.210 -1.658 TRUE -0.448 0.641 -0.699 0.484
#> 162 -1.402 -1.133 TRUE 0.269 0.606 0.444 0.657
#> 163 -0.825 -0.539 TRUE 0.286 0.522 0.548 0.583
#> 164 0.698 0.819 TRUE 0.121 0.559 0.217 0.828
#> 165 0.412 0.707 TRUE 0.295 0.534 0.552 0.581
#> 166 1.536 0.895 TRUE -0.641 0.650 -0.987 0.324
#> 167 -0.189 -1.012 TRUE -0.823 0.528 -1.560 0.119
#> 168 0.354 0.029 TRUE -0.325 0.502 -0.647 0.517
#> 169 1.431 1.143 TRUE -0.288 0.658 -0.437 0.662
#> 170 -0.293 -1.042 TRUE -0.749 0.531 -1.409 0.159
#> 171 -0.229 -0.237 TRUE -0.007 0.492 -0.015 0.988
#> 172 -1.726 -1.969 TRUE -0.242 0.727 -0.333 0.739
#> 173 0.597 -0.528 TRUE -1.125 0.522 -2.156 0.031
#> 174 -0.310 -0.325 TRUE -0.015 0.494 -0.030 0.976
#> 175 -0.763 -0.264 TRUE 0.499 0.511 0.976 0.329
#> 176 1.519 0.031 TRUE -1.488 0.610 -2.440 0.015
#> 177 1.229 1.532 TRUE 0.303 0.678 0.447 0.655
#> 178 -1.148 -1.469 TRUE -0.321 0.614 -0.522 0.602
#> 179 -1.508 -1.550 TRUE -0.042 0.656 -0.065 0.948
#> 180 -2.281 -1.741 TRUE 0.540 0.767 0.703 0.482
#> 181 1.751 2.071 TRUE 0.320 0.802 0.399 0.69
#> 182 1.004 0.164 TRUE -0.840 0.551 -1.524 0.128
#> 183 -0.067 -0.892 TRUE -0.825 0.518 -1.592 0.111
#> 184 -0.069 0.668 TRUE 0.737 0.519 1.419 0.156
#> 185 -0.590 -0.198 TRUE 0.392 0.501 0.781 0.435
#> 186 1.061 1.274 TRUE 0.213 0.633 0.336 0.737
#> 187 -1.440 -0.488 TRUE 0.952 0.575 1.657 0.097
#> 188 0.839 1.792 TRUE 0.952 0.679 1.402 0.161
#> 189 0.426 -0.244 TRUE -0.670 0.505 -1.327 0.184
#> 190 -0.752 -0.652 TRUE 0.100 0.522 0.191 0.848
#> 191 -1.484 -1.758 TRUE -0.274 0.677 -0.404 0.686
#> 192 -0.026 -0.427 TRUE -0.401 0.495 -0.809 0.418
#> 193 -1.157 0.251 TRUE 1.408 0.546 2.581 0.01
#> 194 -0.090 -0.125 TRUE -0.036 0.491 -0.073 0.942
#> 195 -1.523 -0.689 TRUE 0.834 0.592 1.410 0.159
#> 196 -0.946 -0.744 TRUE 0.202 0.539 0.375 0.708
#> 197 0.236 0.050 TRUE -0.186 0.498 -0.374 0.709
#> 198 1.350 0.967 TRUE -0.382 0.633 -0.604 0.546
#> 199 -0.143 -0.634 TRUE -0.491 0.503 -0.977 0.329
#> 200 0.652 1.595 TRUE 0.943 0.641 1.470 0.141
#> 201 -0.095 -1.180 TRUE -1.085 0.542 -2.001 0.045
#> 202 -0.199 -0.469 TRUE -0.269 0.497 -0.543 0.587
#> 203 -1.216 -1.371 TRUE -0.156 0.610 -0.256 0.798
#> 204 -0.863 -1.642 TRUE -0.779 0.615 -1.268 0.205
#> 205 0.222 0.200 TRUE -0.022 0.501 -0.044 0.965
#> 206 -0.927 -1.161 TRUE -0.234 0.568 -0.413 0.68
#> 207 -1.707 -1.397 TRUE 0.310 0.663 0.468 0.64
#> 208 0.935 1.792 TRUE 0.857 0.686 1.249 0.212
#> 209 -0.960 -1.650 TRUE -0.691 0.621 -1.111 0.266
#> 210 0.823 1.457 TRUE 0.635 0.635 1.000 0.317
#> 211 0.191 0.293 TRUE 0.103 0.503 0.204 0.838
#> 212 -1.515 -1.201 TRUE 0.314 0.624 0.503 0.615
#> 213 -0.066 -0.123 TRUE -0.057 0.491 -0.117 0.907
#> 214 0.160 0.459 TRUE 0.298 0.509 0.586 0.558
#> 215 0.733 0.745 TRUE 0.011 0.556 0.020 0.984
#> 216 1.596 1.751 TRUE 0.155 0.744 0.208 0.835
#> 217 0.876 0.794 TRUE -0.082 0.571 -0.144 0.886
#> 218 1.721 2.071 TRUE 0.350 0.799 0.438 0.661
#> 219 -2.024 -2.281 TRUE -0.257 0.798 -0.322 0.747
#> 220 0.482 0.276 TRUE -0.206 0.514 -0.400 0.689
#> 221 0.561 0.039 TRUE -0.523 0.513 -1.019 0.308
#> 222 1.751 1.110 TRUE -0.641 0.695 -0.922 0.357
#> 223 -1.562 -0.841 TRUE 0.721 0.604 1.194 0.233
#> 224 -1.691 -1.969 TRUE -0.278 0.723 -0.384 0.701
#> 225 0.718 0.463 TRUE -0.255 0.537 -0.475 0.635
#> 226 0.208 -0.046 TRUE -0.255 0.496 -0.514 0.607
#> 227 -0.781 -0.904 TRUE -0.123 0.538 -0.229 0.819
#> 228 -0.860 -0.337 TRUE 0.524 0.518 1.010 0.312
#> 229 -2.035 -2.281 TRUE -0.246 0.799 -0.307 0.759
#> 230 0.309 0.533 TRUE 0.223 0.518 0.431 0.667
#> 231 -1.475 -1.332 TRUE 0.143 0.631 0.226 0.821
#> 232 -0.101 -0.644 TRUE -0.543 0.504 -1.079 0.281
#> 233 0.120 -0.082 TRUE -0.201 0.493 -0.408 0.683
#> 234 0.346 1.133 TRUE 0.788 0.570 1.381 0.167
#> 235 1.374 0.926 TRUE -0.448 0.632 -0.708 0.479
#> 236 -0.225 -0.032 TRUE 0.192 0.492 0.391 0.696
#> 237 0.034 -0.816 TRUE -0.851 0.514 -1.654 0.098
#> 238 0.623 1.751 TRUE 1.128 0.661 1.707 0.088
#> 239 -1.396 -1.763 TRUE -0.367 0.669 -0.549 0.583
#> 240 -0.389 -1.223 TRUE -0.833 0.549 -1.517 0.129
#> 241 0.706 0.589 TRUE -0.116 0.544 -0.214 0.83
#> 242 0.286 0.508 TRUE 0.222 0.516 0.431 0.667
#> 243 1.179 1.053 TRUE -0.126 0.622 -0.203 0.839
#> 244 -0.196 -0.527 TRUE -0.331 0.499 -0.664 0.506
#> 245 -0.651 -0.914 TRUE -0.263 0.532 -0.494 0.621
#> 246 0.042 -0.515 TRUE -0.557 0.499 -1.117 0.264
#> 247 0.495 0.248 TRUE -0.247 0.514 -0.481 0.631
#> 248 -0.046 0.010 TRUE 0.056 0.492 0.114 0.909
#> 249 -0.011 -0.013 TRUE -0.002 0.492 -0.004 0.997
#> 250 1.510 1.557 TRUE 0.047 0.711 0.066 0.947
#> 251 -1.119 -1.042 TRUE 0.078 0.573 0.136 0.892
#> 252 -1.940 -1.436 TRUE 0.504 0.695 0.725 0.468
#> 253 -1.146 -1.969 TRUE -0.823 0.674 -1.221 0.222
#> 254 -0.328 -0.225 TRUE 0.104 0.493 0.210 0.833
#> 255 -0.201 -0.165 TRUE 0.035 0.491 0.072 0.943
#> 256 1.237 1.571 TRUE 0.334 0.684 0.489 0.625
#> 257 1.532 2.071 TRUE 0.539 0.778 0.693 0.489
#> 258 0.090 -0.148 TRUE -0.237 0.493 -0.482 0.63
#> 259 1.001 1.198 TRUE 0.197 0.619 0.318 0.751
#> 260 0.262 0.378 TRUE 0.116 0.508 0.227 0.82
#> 261 0.083 0.232 TRUE 0.149 0.498 0.299 0.765
#> 262 -0.164 -0.020 TRUE 0.144 0.491 0.293 0.769
#> 263 0.263 -0.033 TRUE -0.297 0.498 -0.596 0.551
#> 264 1.062 1.109 TRUE 0.047 0.616 0.076 0.939
#> 265 0.118 0.200 TRUE 0.082 0.498 0.165 0.869
#> 266 1.792 1.457 TRUE -0.334 0.734 -0.455 0.649
#> 267 -0.041 -0.152 TRUE -0.111 0.491 -0.225 0.822
#> 268 -0.776 -0.430 TRUE 0.346 0.515 0.673 0.501
#> 269 -0.057 0.336 TRUE 0.393 0.500 0.786 0.432
#> 270 1.196 0.697 TRUE -0.499 0.595 -0.837 0.402
#> 271 1.171 0.350 TRUE -0.821 0.575 -1.429 0.153
#> 272 2.071 1.557 TRUE -0.514 0.781 -0.658 0.511
#> 273 -0.487 -0.568 TRUE -0.081 0.506 -0.160 0.873
#> 274 1.087 1.807 TRUE 0.720 0.700 1.027 0.304
#> 275 0.519 0.338 TRUE -0.182 0.519 -0.350 0.726
#> 276 -1.120 -0.469 TRUE 0.652 0.542 1.202 0.229
#> 277 1.006 0.359 TRUE -0.647 0.558 -1.159 0.246
#> 278 -0.042 0.068 TRUE 0.110 0.492 0.223 0.823
#> 279 -0.433 -0.308 TRUE 0.125 0.497 0.251 0.802
#> 280 -1.754 -1.176 TRUE 0.578 0.649 0.889 0.374
#> 281 -0.659 -1.335 TRUE -0.676 0.570 -1.187 0.235
#> 282 -0.993 -0.193 TRUE 0.800 0.526 1.521 0.128
#> 283 1.459 1.653 TRUE 0.194 0.717 0.270 0.787
#> 284 -0.144 0.290 TRUE 0.433 0.498 0.869 0.385
#> 285 -1.969 -2.024 TRUE -0.055 0.761 -0.072 0.942
#> 286 -1.001 -0.130 TRUE 0.871 0.527 1.654 0.098
#> 287 -1.417 -1.679 TRUE -0.262 0.661 -0.396 0.692
#> 288 -0.524 0.264 TRUE 0.788 0.505 1.561 0.118
#> 289 0.733 1.265 TRUE 0.532 0.606 0.878 0.38
#> 290 1.161 1.323 TRUE 0.163 0.648 0.251 0.802
#> 291 0.557 0.296 TRUE -0.261 0.519 -0.502 0.615
#> 292 0.855 0.171 TRUE -0.684 0.538 -1.273 0.203
#> 293 -1.342 -1.444 TRUE -0.102 0.629 -0.163 0.871
#> 294 1.751 1.134 TRUE -0.616 0.697 -0.884 0.377
#> 295 -0.471 0.032 TRUE 0.503 0.497 1.012 0.312
#> 296 1.064 0.715 TRUE -0.349 0.583 -0.600 0.549
#> 297 0.952 1.343 TRUE 0.391 0.631 0.620 0.535
#> 298 1.400 1.283 TRUE -0.117 0.669 -0.175 0.861
#> 299 -0.002 -0.113 TRUE -0.111 0.491 -0.226 0.821
#> 300 1.040 0.622 TRUE -0.417 0.574 -0.726 0.468
#> 301 -0.404 0.358 TRUE 0.761 0.505 1.508 0.131
#> 302 -1.364 -1.681 TRUE -0.317 0.657 -0.483 0.629
#> 303 0.164 0.174 TRUE 0.010 0.498 0.020 0.984
#> 304 -0.577 -0.927 TRUE -0.350 0.530 -0.661 0.509
#> 305 0.238 0.035 TRUE -0.203 0.497 -0.407 0.684
#> 306 1.354 1.198 TRUE -0.156 0.655 -0.238 0.812
#> 307 0.060 -0.404 TRUE -0.464 0.496 -0.936 0.349
#> 308 1.392 1.394 TRUE 0.002 0.680 0.003 0.998
#> 309 -1.361 -1.641 TRUE -0.280 0.652 -0.430 0.667
#> 310 -0.311 0.068 TRUE 0.379 0.494 0.767 0.443
#> 311 -0.554 -0.436 TRUE 0.118 0.504 0.235 0.814
#> 312 -0.435 -1.789 TRUE -1.353 0.616 -2.198 0.028
#> 313 2.071 2.071 TRUE 0.000 0.840 0.000 1
#> 314 -0.379 -0.282 TRUE 0.097 0.495 0.195 0.845
#> 315 0.923 0.739 TRUE -0.184 0.571 -0.322 0.748
#> 316 0.679 0.138 TRUE -0.541 0.523 -1.035 0.301
#> 317 -0.011 -0.462 TRUE -0.451 0.497 -0.909 0.363
#> 318 -1.167 -0.414 TRUE 0.753 0.545 1.382 0.167
#> 319 -1.056 -1.112 TRUE -0.056 0.573 -0.097 0.922
#> 320 1.455 1.751 TRUE 0.295 0.729 0.405 0.685
#> 321 0.438 0.018 TRUE -0.420 0.506 -0.830 0.406
#> 322 -1.002 -0.915 TRUE 0.087 0.554 0.157 0.875
#> 323 0.441 -0.149 TRUE -0.590 0.505 -1.168 0.243
#> 324 -0.348 -0.472 TRUE -0.124 0.499 -0.249 0.804
#> 325 -0.032 0.006 TRUE 0.039 0.492 0.079 0.937
#> 326 0.162 -0.314 TRUE -0.477 0.496 -0.961 0.336
#> 327 -0.466 -0.848 TRUE -0.383 0.521 -0.735 0.463
#> 328 -0.160 -0.497 TRUE -0.337 0.497 -0.678 0.498
#> 329 0.672 0.363 TRUE -0.309 0.529 -0.583 0.56
#> 330 0.394 0.118 TRUE -0.276 0.505 -0.547 0.584
#> 331 0.196 0.467 TRUE 0.272 0.511 0.532 0.595
#> 332 -1.824 -1.873 TRUE -0.050 0.726 -0.068 0.945
#> 333 0.130 -0.128 TRUE -0.258 0.493 -0.523 0.601
#> 334 0.796 0.745 TRUE -0.051 0.561 -0.090 0.928
#> 335 -0.471 0.780 TRUE 1.251 0.533 2.346 0.019
#> 336 -1.460 -0.670 TRUE 0.790 0.584 1.353 0.176
#> 337 -0.419 -0.382 TRUE 0.037 0.498 0.074 0.941
#> 338 0.409 0.688 TRUE 0.278 0.533 0.523 0.601
#> 339 0.082 -0.286 TRUE -0.368 0.494 -0.745 0.456
#> 340 0.513 0.313 TRUE -0.201 0.517 -0.388 0.698
#> 341 -0.425 -0.070 TRUE 0.355 0.495 0.717 0.473
#> 342 0.326 0.850 TRUE 0.523 0.542 0.966 0.334
#> 343 0.743 -0.563 TRUE -1.306 0.533 -2.448 0.014
#> 344 0.687 0.365 TRUE -0.322 0.531 -0.608 0.543
#> 345 -0.173 -0.150 TRUE 0.022 0.491 0.045 0.964
#> 346 0.557 0.518 TRUE -0.039 0.530 -0.074 0.941
#> 347 0.744 1.001 TRUE 0.257 0.579 0.445 0.656
#> 348 -0.162 0.209 TRUE 0.371 0.496 0.748 0.455
#> 349 1.020 1.517 TRUE 0.497 0.657 0.757 0.449
#> 350 0.536 -0.094 TRUE -0.630 0.510 -1.234 0.217
#> 351 -0.651 -0.742 TRUE -0.091 0.521 -0.174 0.862
#> 352 0.361 0.517 TRUE 0.156 0.519 0.300 0.764
#> 353 -0.507 -0.245 TRUE 0.261 0.498 0.525 0.6
#> 354 -0.110 -0.696 TRUE -0.586 0.506 -1.157 0.247
#> 355 0.245 0.348 TRUE 0.104 0.507 0.205 0.838
#> 356 0.577 0.285 TRUE -0.292 0.520 -0.561 0.574
#> 357 -0.622 0.090 TRUE 0.712 0.504 1.412 0.158
#> 358 -0.623 -1.047 TRUE -0.424 0.541 -0.783 0.434
#> 359 -0.126 -0.123 TRUE 0.003 0.491 0.005 0.996
#> 360 -0.331 -0.541 TRUE -0.210 0.501 -0.419 0.675
#> 361 0.907 1.350 TRUE 0.443 0.628 0.705 0.481
#> 362 -0.953 -0.782 TRUE 0.171 0.542 0.316 0.752
#> 363 -0.435 -0.367 TRUE 0.068 0.498 0.136 0.892
#> 364 1.016 1.235 TRUE 0.219 0.624 0.351 0.726
#> 365 0.658 1.240 TRUE 0.582 0.598 0.973 0.331
#> 366 0.032 0.293 TRUE 0.261 0.499 0.523 0.601
#> 367 -0.260 0.146 TRUE 0.406 0.495 0.821 0.412
#> 368 -1.969 -1.262 TRUE 0.707 0.683 1.034 0.301
#> 369 0.033 -0.114 TRUE -0.147 0.492 -0.299 0.765
#> 370 -0.291 -1.345 TRUE -1.053 0.560 -1.881 0.06
#> 371 0.853 1.792 TRUE 0.938 0.680 1.379 0.168
#> 372 -0.795 -0.555 TRUE 0.240 0.520 0.462 0.644
#> 373 1.167 0.998 TRUE -0.169 0.616 -0.274 0.784
#> 374 -0.748 -0.309 TRUE 0.439 0.511 0.860 0.39
#> 375 1.510 1.457 TRUE -0.052 0.700 -0.075 0.94
#> 376 -0.915 -1.257 TRUE -0.342 0.576 -0.594 0.552
#> 377 0.285 0.508 TRUE 0.223 0.516 0.432 0.666
#> 378 0.205 -0.132 TRUE -0.337 0.495 -0.681 0.496
#> 379 0.515 0.692 TRUE 0.177 0.538 0.330 0.742
#> 380 1.432 1.037 TRUE -0.395 0.649 -0.610 0.542
#> 381 -0.380 0.141 TRUE 0.521 0.497 1.049 0.294
#> 382 -0.171 -0.200 TRUE -0.029 0.491 -0.060 0.952
#> 383 -0.793 -0.899 TRUE -0.107 0.539 -0.198 0.843
#> 384 -0.537 -0.325 TRUE 0.212 0.501 0.424 0.672
#> 385 0.853 1.165 TRUE 0.311 0.603 0.516 0.606
#> 386 0.705 0.954 TRUE 0.249 0.572 0.436 0.663
#> 387 -0.763 0.374 TRUE 1.137 0.521 2.183 0.029
#> 388 -1.412 -1.763 TRUE -0.351 0.671 -0.523 0.601
#> 389 -0.303 -0.094 TRUE 0.209 0.492 0.424 0.672
#> 390 -0.230 -0.316 TRUE -0.086 0.493 -0.174 0.862
#> 391 -1.242 -0.136 TRUE 1.106 0.548 2.018 0.044
#> 392 -0.388 -0.515 TRUE -0.127 0.501 -0.252 0.801
#> 393 -0.916 -1.101 TRUE -0.184 0.562 -0.328 0.743
#> 394 -0.984 -0.841 TRUE 0.143 0.548 0.261 0.794
#> 395 -1.893 -1.620 TRUE 0.273 0.707 0.387 0.699
#> 396 0.453 0.275 TRUE -0.178 0.512 -0.347 0.729
#> 397 0.924 1.053 TRUE 0.130 0.598 0.217 0.828
#> 398 -0.963 -0.522 TRUE 0.441 0.531 0.831 0.406
#> 399 -1.915 -1.915 TRUE 0.000 0.742 0.000 1
#> 400 0.975 1.157 TRUE 0.182 0.613 0.297 0.766
#> 401 -0.455 -0.331 TRUE 0.124 0.498 0.249 0.804
#> 402 -1.375 -1.392 TRUE -0.016 0.627 -0.026 0.979
#> 403 -1.145 -1.611 TRUE -0.466 0.630 -0.740 0.46
#> 404 -0.218 -0.238 TRUE -0.020 0.492 -0.040 0.968
#> 405 0.659 1.134 TRUE 0.475 0.586 0.810 0.418
#> 406 1.332 0.462 TRUE -0.870 0.598 -1.455 0.146
#> 407 -1.443 -0.594 TRUE 0.849 0.579 1.468 0.142
#> 408 -0.043 0.586 TRUE 0.629 0.514 1.224 0.221
#> 409 0.766 -0.542 TRUE -1.308 0.534 -2.447 0.014
#> 410 0.356 -0.177 TRUE -0.534 0.501 -1.065 0.287
#> 411 -0.659 -0.701 TRUE -0.042 0.520 -0.081 0.935
#> 412 -0.175 -0.080 TRUE 0.096 0.491 0.195 0.845
#> 413 0.778 1.219 TRUE 0.440 0.604 0.730 0.465
#> 414 -1.330 -1.598 TRUE -0.268 0.644 -0.415 0.678
#> 415 -1.108 -1.482 TRUE -0.374 0.613 -0.611 0.541
#> 416 -0.356 -0.321 TRUE 0.035 0.495 0.070 0.944
#> 417 0.347 -0.493 TRUE -0.839 0.507 -1.655 0.098
#> 418 0.955 0.183 TRUE -0.772 0.547 -1.411 0.158
#> 419 -0.405 -0.164 TRUE 0.241 0.495 0.487 0.626
#> 420 -0.977 -0.879 TRUE 0.098 0.550 0.178 0.859
#> 421 0.513 1.063 TRUE 0.551 0.571 0.965 0.335
#> 422 -1.108 -1.445 TRUE -0.337 0.609 -0.554 0.58
#> 423 1.532 1.721 TRUE 0.189 0.733 0.258 0.797
#> 424 -0.015 -0.104 TRUE -0.090 0.491 -0.182 0.855
#> 425 -0.219 0.064 TRUE 0.283 0.493 0.575 0.565
#> 426 0.628 0.935 TRUE 0.306 0.565 0.542 0.587
#> 427 -1.235 -0.672 TRUE 0.562 0.560 1.004 0.315
#> 428 0.004 -0.426 TRUE -0.430 0.496 -0.867 0.386
#> 429 0.669 0.593 TRUE -0.076 0.541 -0.141 0.888
#> 430 -1.024 -0.907 TRUE 0.117 0.555 0.211 0.833
#> 431 1.812 1.812 TRUE 0.000 0.777 0.000 1
#> 432 0.522 0.167 TRUE -0.355 0.513 -0.692 0.489
#> 433 0.493 2.071 TRUE 1.577 0.700 2.253 0.024
#> 434 0.232 0.670 TRUE 0.438 0.525 0.835 0.404
#> 435 1.107 1.001 TRUE -0.106 0.610 -0.174 0.862
#> 436 0.238 0.158 TRUE -0.079 0.500 -0.158 0.874
#> 437 0.205 -0.048 TRUE -0.253 0.496 -0.510 0.61
#> 438 -0.158 0.057 TRUE 0.215 0.492 0.436 0.663
#> 439 -0.235 -0.545 TRUE -0.311 0.500 -0.621 0.534
#> 440 1.373 0.757 TRUE -0.616 0.620 -0.993 0.321
#> 441 -1.683 -1.415 TRUE 0.267 0.662 0.404 0.686
#> 442 -1.163 -0.870 TRUE 0.293 0.564 0.520 0.603
#> 443 0.708 0.045 TRUE -0.663 0.523 -1.267 0.205
#> 444 -1.758 -1.306 TRUE 0.452 0.661 0.685 0.494
#> 445 0.844 -0.169 TRUE -1.013 0.533 -1.900 0.057
#> 446 -1.361 -1.121 TRUE 0.240 0.601 0.399 0.69
#> 447 -0.146 0.378 TRUE 0.524 0.502 1.044 0.296
#> 448 0.687 0.591 TRUE -0.096 0.542 -0.177 0.859
#> 449 0.052 -0.475 TRUE -0.527 0.498 -1.059 0.29
#> 450 0.784 1.457 TRUE 0.674 0.632 1.066 0.286
#> 451 -1.562 -1.351 TRUE 0.211 0.642 0.329 0.742
#> 452 -0.173 -0.113 TRUE 0.060 0.491 0.121 0.903
#> 453 1.093 1.635 TRUE 0.543 0.679 0.800 0.424
#> 454 1.414 1.361 TRUE -0.052 0.678 -0.077 0.938
#> 455 0.885 1.387 TRUE 0.502 0.631 0.796 0.426
#> 456 -1.588 -1.583 TRUE 0.004 0.668 0.007 0.995
#> 457 0.386 0.432 TRUE 0.046 0.516 0.090 0.928
#> 458 -0.863 0.034 TRUE 0.897 0.517 1.734 0.083
#> 459 -0.863 -1.168 TRUE -0.305 0.564 -0.540 0.589
#> 460 2.071 1.536 TRUE -0.535 0.778 -0.687 0.492
#> 461 -0.301 -1.018 TRUE -0.716 0.529 -1.353 0.176
#> 462 0.038 0.419 TRUE 0.380 0.505 0.753 0.452
#> 463 -0.176 -0.023 TRUE 0.153 0.491 0.312 0.755
#> 464 0.715 1.751 TRUE 1.036 0.666 1.556 0.12
#> 465 -0.197 -0.146 TRUE 0.052 0.491 0.105 0.916
#> 466 -0.206 -1.330 TRUE -1.124 0.557 -2.017 0.044
#> 467 -1.435 -1.297 TRUE 0.138 0.624 0.221 0.825
#> 468 -1.583 -1.798 TRUE -0.215 0.692 -0.311 0.756
#> 469 1.484 1.751 TRUE 0.267 0.732 0.365 0.715
#> 470 1.198 0.289 TRUE -0.910 0.576 -1.580 0.114
#> 471 0.292 0.496 TRUE 0.205 0.515 0.397 0.691
#> 472 -0.102 0.893 TRUE 0.995 0.538 1.851 0.064
#> 473 0.786 0.175 TRUE -0.611 0.532 -1.148 0.251
#> 474 -0.387 -0.482 TRUE -0.095 0.500 -0.190 0.85
#> 475 -1.251 -0.800 TRUE 0.451 0.568 0.794 0.427
#> 476 1.320 0.911 TRUE -0.408 0.625 -0.653 0.514
#> 477 -1.213 -1.020 TRUE 0.193 0.579 0.332 0.74
#> 478 -1.681 -1.387 TRUE 0.294 0.659 0.445 0.656
#> 479 0.481 1.395 TRUE 0.914 0.607 1.507 0.132
#> 480 -0.319 -0.916 TRUE -0.597 0.522 -1.145 0.252
#> 481 -0.865 -0.521 TRUE 0.344 0.524 0.657 0.511
#> 482 2.071 2.071 TRUE 0.000 0.840 0.000 1
#> 483 -0.516 -0.442 TRUE 0.074 0.503 0.148 0.882
#> 484 -1.824 -1.578 TRUE 0.245 0.694 0.353 0.724
#> 485 0.914 0.339 TRUE -0.575 0.548 -1.049 0.294
#> 486 0.870 0.904 TRUE 0.034 0.580 0.059 0.953
#> 487 -0.295 0.221 TRUE 0.516 0.497 1.037 0.3
#> 488 -0.378 -0.851 TRUE -0.473 0.518 -0.912 0.362
#> 489 0.244 1.042 TRUE 0.798 0.557 1.432 0.152
#> 490 0.154 -0.234 TRUE -0.387 0.495 -0.783 0.434
#> 491 0.540 -0.069 TRUE -0.609 0.511 -1.192 0.233
#> 492 1.792 1.457 TRUE -0.334 0.734 -0.455 0.649
#> 493 0.483 -0.041 TRUE -0.524 0.508 -1.033 0.302
#> 494 0.043 -0.823 TRUE -0.866 0.515 -1.683 0.092
#> 495 -1.119 -1.143 TRUE -0.023 0.581 -0.040 0.968
#> 496 0.009 0.214 TRUE 0.205 0.496 0.413 0.679
#> 497 0.409 0.540 TRUE 0.130 0.523 0.249 0.803
#> 498 1.751 1.405 TRUE -0.346 0.723 -0.478 0.633
#> 499 -0.768 -0.443 TRUE 0.325 0.515 0.631 0.528
#> 500 2.071 2.071 TRUE 0.000 0.840 0.000 1
#> 501 -0.859 -0.647 TRUE 0.212 0.528 0.401 0.688
#> 502 1.255 1.567 TRUE 0.312 0.685 0.455 0.649
#> 503 -0.145 -0.104 TRUE 0.041 0.491 0.084 0.933
#> 504 0.154 0.337 TRUE 0.183 0.503 0.364 0.716
#> 505 -0.431 0.421 TRUE 0.852 0.508 1.676 0.094
#> 506 -0.295 -0.045 TRUE 0.250 0.492 0.508 0.611
#> 507 -0.226 -0.469 TRUE -0.243 0.497 -0.489 0.625
#> 508 -0.819 -0.959 TRUE -0.140 0.545 -0.258 0.797
#> 509 0.725 0.489 TRUE -0.237 0.539 -0.439 0.661
#> 510 0.771 0.210 TRUE -0.561 0.532 -1.055 0.292
#> 511 0.365 0.481 TRUE 0.116 0.518 0.224 0.823
#> 512 -1.893 -2.281 TRUE -0.388 0.783 -0.495 0.62
#> 513 -1.070 -0.113 TRUE 0.957 0.532 1.799 0.072
#> 514 -1.057 -1.353 TRUE -0.297 0.595 -0.498 0.618
#> 515 0.735 0.246 TRUE -0.489 0.530 -0.924 0.356
#> 516 1.821 1.585 TRUE -0.236 0.752 -0.314 0.753
#> 517 1.048 0.962 TRUE -0.086 0.601 -0.143 0.886
#> 518 -0.663 -0.882 TRUE -0.219 0.531 -0.413 0.68
#> 519 -0.145 0.656 TRUE 0.801 0.518 1.545 0.122
#> 520 0.033 -1.102 TRUE -1.135 0.536 -2.117 0.034
#> 521 -0.620 -0.179 TRUE 0.441 0.503 0.878 0.38
#> 522 -1.305 -1.177 TRUE 0.128 0.600 0.213 0.832
#> 523 -0.025 -0.311 TRUE -0.286 0.493 -0.580 0.562
#> 524 0.807 0.150 TRUE -0.657 0.533 -1.232 0.218
#> 525 0.968 0.947 TRUE -0.021 0.592 -0.036 0.971
#> 526 0.516 0.301 TRUE -0.215 0.517 -0.416 0.677
#> 527 0.045 0.294 TRUE 0.249 0.500 0.498 0.619
#> 528 1.071 0.791 TRUE -0.280 0.589 -0.476 0.634
#> 529 -0.696 -0.184 TRUE 0.512 0.506 1.011 0.312
#> 530 0.053 0.008 TRUE -0.045 0.493 -0.091 0.927
#> 531 -0.642 -0.937 TRUE -0.295 0.534 -0.553 0.581
#> 532 0.113 1.162 TRUE 1.049 0.567 1.850 0.064
#> 533 -0.019 0.819 TRUE 0.838 0.531 1.577 0.115
#> 534 0.900 0.564 TRUE -0.336 0.558 -0.603 0.547
#> 535 1.000 0.499 TRUE -0.502 0.564 -0.890 0.373
#> 536 -0.428 0.716 TRUE 1.143 0.527 2.170 0.03
#> 537 1.751 1.035 TRUE -0.716 0.689 -1.040 0.299
#> 538 0.606 0.520 TRUE -0.086 0.533 -0.161 0.872
#> 539 -0.224 -0.504 TRUE -0.280 0.498 -0.563 0.574
#> 540 -0.133 -0.323 TRUE -0.190 0.493 -0.386 0.7
#> 541 2.071 1.812 TRUE -0.258 0.809 -0.319 0.749
#> 542 1.390 1.510 TRUE 0.120 0.692 0.173 0.863
#> 543 -0.064 -0.395 TRUE -0.332 0.494 -0.671 0.502
#> 544 1.592 2.071 TRUE 0.478 0.784 0.610 0.542
#> 545 0.269 -0.098 TRUE -0.367 0.498 -0.738 0.46
#> 546 -0.256 0.536 TRUE 0.792 0.511 1.550 0.121
#> 547 -0.598 -0.452 TRUE 0.146 0.507 0.289 0.773
#> 548 -0.273 -0.029 TRUE 0.244 0.492 0.496 0.62
#> 549 0.627 -0.198 TRUE -0.825 0.517 -1.597 0.11
#> 550 -1.095 -1.137 TRUE -0.042 0.578 -0.073 0.942
#> 551 -0.978 -0.793 TRUE 0.186 0.544 0.341 0.733
#> 552 -0.834 -0.743 TRUE 0.090 0.532 0.170 0.865
#> 553 -0.393 0.365 TRUE 0.758 0.505 1.502 0.133
#> 554 -0.524 -0.802 TRUE -0.278 0.520 -0.535 0.593
#> 555 0.285 -0.071 TRUE -0.356 0.498 -0.715 0.474
#> 556 0.656 0.738 TRUE 0.081 0.550 0.148 0.882
#> 557 -0.350 0.293 TRUE 0.643 0.501 1.284 0.199
#> 558 0.153 0.461 TRUE 0.309 0.509 0.606 0.545
#> 559 0.175 0.305 TRUE 0.130 0.503 0.258 0.796
#> 560 -1.168 -0.974 TRUE 0.194 0.572 0.339 0.735
#> 561 0.294 0.623 TRUE 0.329 0.523 0.629 0.529
#> 562 -0.015 0.437 TRUE 0.451 0.505 0.894 0.372
#> 563 0.473 -0.037 TRUE -0.510 0.507 -1.006 0.315
#> 564 -2.029 -1.416 TRUE 0.613 0.704 0.871 0.384
#> 565 0.276 0.584 TRUE 0.309 0.520 0.593 0.553
#> 566 0.860 0.657 TRUE -0.202 0.560 -0.361 0.718
#> 567 -0.414 -0.556 TRUE -0.142 0.504 -0.282 0.778
#> 568 0.778 0.972 TRUE 0.194 0.579 0.336 0.737
#> 569 1.751 1.719 TRUE -0.032 0.759 -0.043 0.966
#> 570 0.385 0.152 TRUE -0.233 0.506 -0.461 0.645
#> 571 0.890 0.533 TRUE -0.357 0.555 -0.642 0.521
#> 572 -1.025 -0.771 TRUE 0.255 0.547 0.466 0.642
#> 573 -1.763 -1.475 TRUE 0.288 0.677 0.426 0.67
#> 574 1.635 0.368 TRUE -1.268 0.633 -2.001 0.045
#> 575 -1.408 -1.969 TRUE -0.561 0.696 -0.807 0.42
#> 576 1.223 1.491 TRUE 0.268 0.673 0.398 0.691
#> 577 -1.526 -1.573 TRUE -0.047 0.661 -0.071 0.944
#> 578 1.719 1.233 TRUE -0.486 0.702 -0.692 0.489
#> 579 0.376 0.353 TRUE -0.023 0.512 -0.046 0.963
#> 580 2.071 0.601 TRUE -1.469 0.705 -2.084 0.037
#> 581 -0.696 -0.903 TRUE -0.206 0.534 -0.386 0.699
#> 582 1.160 1.295 TRUE 0.135 0.644 0.209 0.834
#> 583 -0.540 -0.893 TRUE -0.353 0.526 -0.672 0.502
#> 584 -0.800 -1.361 TRUE -0.560 0.579 -0.967 0.333
#> 585 0.868 0.075 TRUE -0.792 0.537 -1.476 0.14
#> 586 0.313 0.528 TRUE 0.215 0.518 0.415 0.678
#> 587 1.431 1.152 TRUE -0.279 0.659 -0.423 0.672
#> 588 -0.238 -0.530 TRUE -0.292 0.499 -0.586 0.558
#> 589 0.348 -0.057 TRUE -0.404 0.501 -0.807 0.419
#> 590 0.169 0.506 TRUE 0.337 0.512 0.658 0.51
#> 591 -0.304 0.033 TRUE 0.336 0.493 0.682 0.495
#> 592 0.106 0.772 TRUE 0.666 0.529 1.258 0.208
#> 593 1.009 0.639 TRUE -0.370 0.572 -0.647 0.518
#> 594 -1.096 -1.583 TRUE -0.487 0.623 -0.782 0.434
#> 595 -0.565 -0.338 TRUE 0.228 0.502 0.453 0.65
#> 596 0.062 -0.082 TRUE -0.145 0.492 -0.294 0.769
#> 597 -0.344 -0.035 TRUE 0.310 0.493 0.628 0.53
#> 598 -0.279 0.236 TRUE 0.515 0.498 1.035 0.301
#> 599 0.472 0.296 TRUE -0.176 0.514 -0.342 0.733
#> 600 0.258 0.986 TRUE 0.728 0.552 1.318 0.187
#> 601 0.750 1.596 TRUE 0.846 0.647 1.307 0.191
#> 602 -0.017 -0.383 TRUE -0.366 0.494 -0.740 0.459
#> 603 -0.998 -1.433 TRUE -0.435 0.599 -0.726 0.468
#> 604 -0.579 -0.225 TRUE 0.354 0.501 0.707 0.48
#> 605 -0.658 -1.597 TRUE -0.939 0.599 -1.568 0.117
#> 606 -1.816 -0.707 TRUE 1.109 0.628 1.764 0.078
#> 607 -0.005 -0.553 TRUE -0.548 0.500 -1.095 0.274
#> 608 0.732 0.638 TRUE -0.093 0.549 -0.170 0.865
#> 609 0.032 0.111 TRUE 0.079 0.494 0.161 0.872
#> 610 0.269 -0.614 TRUE -0.883 0.509 -1.736 0.083
#> 611 0.475 0.160 TRUE -0.315 0.510 -0.618 0.537
#> 612 0.017 -0.125 TRUE -0.142 0.491 -0.289 0.773
#> 613 0.062 0.384 TRUE 0.322 0.504 0.639 0.523
#> 614 -0.960 -0.727 TRUE 0.233 0.539 0.431 0.666
#> 615 0.168 0.313 TRUE 0.144 0.503 0.287 0.774
#> 616 -1.349 -2.029 TRUE -0.680 0.698 -0.974 0.33
#> 617 -1.148 -0.799 TRUE 0.349 0.559 0.624 0.533
#> 618 -0.946 -1.011 TRUE -0.066 0.557 -0.118 0.906
#> 619 0.770 1.224 TRUE 0.454 0.603 0.753 0.451
#> 620 -1.271 -0.867 TRUE 0.404 0.574 0.703 0.482
#> 621 1.812 1.053 TRUE -0.759 0.698 -1.087 0.277
#> 622 0.293 0.105 TRUE -0.188 0.501 -0.375 0.708
#> 623 1.264 1.792 TRUE 0.527 0.714 0.738 0.461
#> 624 -0.603 -0.968 TRUE -0.365 0.534 -0.683 0.495
#> 625 -0.219 -0.155 TRUE 0.065 0.491 0.131 0.895
#> 626 -0.932 -1.183 TRUE -0.251 0.570 -0.440 0.66
#> 627 -1.073 -1.143 TRUE -0.070 0.577 -0.121 0.903
#> 628 -1.308 -1.969 TRUE -0.660 0.687 -0.961 0.336
#> 629 -0.682 -0.538 TRUE 0.144 0.513 0.281 0.779
#> 630 -0.454 0.321 TRUE 0.775 0.505 1.536 0.125
#> 631 0.539 1.387 TRUE 0.848 0.608 1.393 0.164
#> 632 -0.505 -1.171 TRUE -0.666 0.548 -1.216 0.224
#> 633 0.762 1.094 TRUE 0.331 0.589 0.562 0.574
#> 634 0.440 0.509 TRUE 0.069 0.523 0.131 0.896
#> 635 0.786 0.079 TRUE -0.706 0.530 -1.333 0.182
#> 636 0.406 -0.148 TRUE -0.553 0.503 -1.099 0.272
#> 637 -0.784 -0.575 TRUE 0.209 0.521 0.401 0.689
#> 638 0.110 -0.511 TRUE -0.621 0.500 -1.242 0.214
#> 639 -0.640 -0.752 TRUE -0.112 0.521 -0.215 0.83
#> 640 -1.427 -1.765 TRUE -0.338 0.672 -0.503 0.615
#> 641 -0.247 -0.548 TRUE -0.301 0.500 -0.603 0.547
#> 642 -0.604 -0.716 TRUE -0.113 0.518 -0.217 0.828
#> 643 1.115 0.913 TRUE -0.202 0.603 -0.335 0.738
#> 644 0.324 0.456 TRUE 0.133 0.514 0.258 0.797
#> 645 0.291 0.742 TRUE 0.451 0.532 0.848 0.396
#> 646 -1.765 -1.492 TRUE 0.273 0.679 0.402 0.688
#> 647 1.457 0.567 TRUE -0.890 0.619 -1.438 0.15
#> 648 -0.909 -0.734 TRUE 0.175 0.536 0.327 0.744
#> 649 -0.766 -1.265 TRUE -0.499 0.568 -0.879 0.38
#> 650 1.818 1.265 TRUE -0.553 0.718 -0.770 0.441
#> 651 -0.496 -0.973 TRUE -0.477 0.531 -0.898 0.369
#> 652 -0.061 0.169 TRUE 0.230 0.495 0.465 0.642
#> 653 -0.707 -0.186 TRUE 0.521 0.507 1.029 0.304
#> 654 -1.269 -0.899 TRUE 0.370 0.576 0.643 0.52
#> 655 -0.879 -1.010 TRUE -0.131 0.552 -0.237 0.813
#> 656 -0.834 -1.054 TRUE -0.220 0.553 -0.398 0.691
#> 657 0.390 0.058 TRUE -0.332 0.504 -0.659 0.51
#> 658 -0.248 0.390 TRUE 0.638 0.503 1.267 0.205
#> 659 1.508 1.017 TRUE -0.491 0.656 -0.748 0.455
#> 660 0.104 -0.541 TRUE -0.646 0.501 -1.288 0.198
#> 661 -0.195 -0.599 TRUE -0.404 0.502 -0.806 0.42
#> 662 1.812 1.442 TRUE -0.370 0.735 -0.504 0.614
#> 663 0.164 0.654 TRUE 0.491 0.522 0.941 0.347
#> 664 1.068 1.807 TRUE 0.739 0.699 1.057 0.291
#> 665 0.038 0.695 TRUE 0.656 0.522 1.257 0.209
#> 666 0.297 0.556 TRUE 0.259 0.519 0.499 0.618
#> 667 -0.242 0.268 TRUE 0.511 0.498 1.025 0.305
#> 668 0.118 0.295 TRUE 0.177 0.501 0.353 0.724
#> 669 -0.532 0.061 TRUE 0.593 0.500 1.186 0.236
#> 670 -0.546 -0.902 TRUE -0.356 0.527 -0.675 0.5
#> 671 0.288 0.083 TRUE -0.205 0.500 -0.410 0.682
#> 672 0.001 -0.191 TRUE -0.193 0.492 -0.392 0.695
#> 673 -0.323 0.029 TRUE 0.351 0.494 0.711 0.477
#> 674 0.096 0.683 TRUE 0.587 0.522 1.124 0.261
#> 675 -0.559 -0.036 TRUE 0.523 0.500 1.045 0.296
#> 676 -1.074 -1.812 TRUE -0.737 0.649 -1.136 0.256
#> 677 0.595 1.077 TRUE 0.482 0.576 0.835 0.403
#> 678 -0.295 -0.479 TRUE -0.184 0.498 -0.370 0.712
#> 679 -0.008 0.060 TRUE 0.068 0.493 0.138 0.89
#> 680 1.020 1.005 TRUE -0.015 0.602 -0.025 0.98
#> 681 1.792 1.673 TRUE -0.119 0.758 -0.157 0.876
#> 682 -0.169 -0.170 TRUE -0.001 0.491 -0.001 0.999
#> 683 1.649 1.459 TRUE -0.190 0.717 -0.265 0.791
#> 684 -1.245 -1.744 TRUE -0.499 0.654 -0.763 0.445
#> 685 0.262 -0.117 TRUE -0.379 0.497 -0.763 0.446
#> 686 0.955 0.447 TRUE -0.508 0.557 -0.913 0.361
#> 687 -0.186 -0.209 TRUE -0.022 0.491 -0.045 0.964
#> 688 -0.707 -0.689 TRUE 0.018 0.521 0.035 0.972
#> 689 -1.197 -1.500 TRUE -0.303 0.622 -0.487 0.627
#> 690 0.732 0.890 TRUE 0.158 0.568 0.279 0.78
#> 691 0.284 0.483 TRUE 0.199 0.514 0.387 0.699
#> 692 -1.137 -0.346 TRUE 0.791 0.540 1.464 0.143
#> 693 -0.005 -0.234 TRUE -0.229 0.492 -0.466 0.641
#> 694 0.290 -0.317 TRUE -0.606 0.500 -1.213 0.225
#> 695 1.045 1.087 TRUE 0.043 0.612 0.070 0.945
#> 696 0.710 0.250 TRUE -0.460 0.528 -0.870 0.384
#> 697 -0.289 -0.190 TRUE 0.098 0.492 0.199 0.842
#> 698 -1.304 -1.053 TRUE 0.251 0.590 0.424 0.671
#> 699 -1.005 -1.508 TRUE -0.503 0.608 -0.827 0.408
#> 700 -0.270 0.424 TRUE 0.694 0.505 1.374 0.17
#> 701 -1.736 -1.163 TRUE 0.573 0.646 0.886 0.375
#> 702 0.301 0.030 TRUE -0.271 0.500 -0.542 0.588
#> 703 0.324 0.014 TRUE -0.310 0.500 -0.619 0.536
#> 704 0.135 0.289 TRUE 0.154 0.501 0.308 0.758
#> 705 0.861 1.192 TRUE 0.331 0.607 0.546 0.585
#> 706 0.641 1.305 TRUE 0.664 0.604 1.099 0.272
#> 707 -0.982 -2.035 TRUE -1.053 0.672 -1.568 0.117
#> 708 0.491 0.502 TRUE 0.011 0.525 0.021 0.983
#> 709 0.402 1.147 TRUE 0.745 0.574 1.298 0.194
#> 710 -0.510 -0.687 TRUE -0.177 0.513 -0.346 0.729
#> 711 1.246 2.071 TRUE 0.824 0.750 1.099 0.272
#> 712 -0.346 -0.818 TRUE -0.472 0.516 -0.915 0.36
#> 713 0.206 0.173 TRUE -0.034 0.499 -0.067 0.946
#> 714 -1.492 -0.993 TRUE 0.500 0.605 0.825 0.409
#> 715 -0.807 -1.411 TRUE -0.604 0.585 -1.032 0.302
#> 716 0.830 0.799 TRUE -0.031 0.568 -0.054 0.957
#> 717 -0.125 -0.389 TRUE -0.264 0.494 -0.534 0.593
#> 718 -0.418 0.217 TRUE 0.635 0.500 1.270 0.204
#> 719 1.450 0.717 TRUE -0.733 0.627 -1.171 0.242
#> 720 -0.862 -0.975 TRUE -0.113 0.548 -0.206 0.837
#> 721 0.077 -0.378 TRUE -0.456 0.496 -0.919 0.358
#> 722 -0.675 -0.732 TRUE -0.057 0.522 -0.109 0.913
#> 723 1.115 1.451 TRUE 0.337 0.658 0.512 0.609
#> 724 -0.781 0.525 TRUE 1.306 0.529 2.468 0.014
#> 725 -0.311 -0.559 TRUE -0.248 0.501 -0.495 0.62
#> 726 -1.302 -1.183 TRUE 0.119 0.600 0.199 0.843
#> 727 -1.147 -1.318 TRUE -0.171 0.599 -0.285 0.775
#> 728 -0.194 -0.134 TRUE 0.060 0.491 0.123 0.902
#> 729 -0.757 -0.840 TRUE -0.083 0.533 -0.155 0.877
#> 730 -0.125 -0.232 TRUE -0.107 0.491 -0.219 0.827
#> 731 0.469 0.948 TRUE 0.479 0.557 0.860 0.39
#> 732 -1.818 -1.338 TRUE 0.480 0.671 0.716 0.474
#> 733 -0.102 -0.401 TRUE -0.299 0.494 -0.604 0.546
#> 734 1.158 0.169 TRUE -0.989 0.568 -1.742 0.081
#> 735 0.140 0.067 TRUE -0.073 0.495 -0.147 0.883
#> 736 0.029 -0.032 TRUE -0.060 0.492 -0.123 0.902
#> 737 0.434 0.363 TRUE -0.072 0.515 -0.139 0.889
#> 738 0.309 0.271 TRUE -0.037 0.506 -0.074 0.941
#> 739 -0.648 -0.541 TRUE 0.106 0.512 0.208 0.835
#> 740 -0.161 -0.644 TRUE -0.483 0.504 -0.958 0.338
#> 741 -0.496 -1.173 TRUE -0.678 0.547 -1.237 0.216
#> 742 -0.513 -0.581 TRUE -0.068 0.508 -0.134 0.894
#> 743 2.071 1.513 TRUE -0.557 0.776 -0.718 0.473
#> 744 -0.023 -0.174 TRUE -0.152 0.491 -0.309 0.757
#> 745 0.055 -0.005 TRUE -0.060 0.493 -0.122 0.903
#> 746 1.488 1.719 TRUE 0.230 0.728 0.316 0.752
#> 747 -0.444 -0.504 TRUE -0.060 0.502 -0.120 0.905
#> 748 1.025 1.234 TRUE 0.209 0.625 0.335 0.738
#> 749 -0.608 -0.435 TRUE 0.173 0.506 0.341 0.733
#> 750 2.071 1.435 TRUE -0.636 0.768 -0.827 0.408
#> 751 -0.391 -0.462 TRUE -0.071 0.500 -0.142 0.887
#> 752 -0.517 -0.171 TRUE 0.346 0.498 0.694 0.487
#> 753 0.193 0.570 TRUE 0.377 0.517 0.730 0.465
#> 754 0.649 1.076 TRUE 0.427 0.580 0.737 0.461
#> 755 -0.255 -0.023 TRUE 0.232 0.492 0.471 0.638
#> 756 0.008 -0.459 TRUE -0.467 0.497 -0.939 0.347
#> 757 -1.969 -1.631 TRUE 0.337 0.717 0.471 0.638
#> 758 -1.147 -0.934 TRUE 0.212 0.567 0.374 0.708
#> 759 0.324 0.729 TRUE 0.405 0.532 0.762 0.446
#> 760 0.813 1.129 TRUE 0.316 0.597 0.529 0.597
#> 761 -0.662 -1.162 TRUE -0.500 0.553 -0.905 0.366
#> 762 1.212 -0.137 TRUE -1.350 0.571 -2.364 0.018
#> 763 0.306 0.426 TRUE 0.120 0.512 0.235 0.814
#> 764 0.447 0.869 TRUE 0.422 0.549 0.769 0.442
#> 765 0.278 0.596 TRUE 0.317 0.521 0.609 0.543
#> 766 0.285 0.503 TRUE 0.218 0.516 0.423 0.672
#> 767 1.162 0.731 TRUE -0.431 0.594 -0.726 0.468
#> 768 -1.622 -1.824 TRUE -0.201 0.699 -0.288 0.774
#> 769 1.457 0.998 TRUE -0.460 0.648 -0.709 0.478
#> 770 1.812 2.071 TRUE 0.258 0.809 0.319 0.749
#> 771 -1.476 -1.170 TRUE 0.306 0.617 0.496 0.62
#> 772 1.143 0.069 TRUE -1.074 0.564 -1.903 0.057
#> 773 0.827 0.941 TRUE 0.115 0.579 0.198 0.843
#> 774 0.516 0.639 TRUE 0.122 0.535 0.229 0.819
#> 775 -1.273 -1.969 TRUE -0.696 0.684 -1.018 0.309
#> 776 1.385 0.778 TRUE -0.606 0.623 -0.974 0.33
#> 777 0.303 0.398 TRUE 0.095 0.511 0.186 0.852
#> 778 0.260 0.599 TRUE 0.339 0.521 0.652 0.515
#> 779 -1.046 -0.973 TRUE 0.074 0.561 0.131 0.896
#> 780 -0.343 -0.467 TRUE -0.124 0.499 -0.249 0.804
#> 781 2.071 1.328 TRUE -0.742 0.758 -0.980 0.327
#> 782 0.282 -0.173 TRUE -0.455 0.498 -0.913 0.361
#> 783 -1.611 -2.035 TRUE -0.424 0.723 -0.587 0.557
#> 784 -0.616 -0.882 TRUE -0.267 0.529 -0.504 0.614
#> 785 0.626 0.425 TRUE -0.202 0.529 -0.381 0.703
#> 786 0.156 -0.102 TRUE -0.258 0.494 -0.522 0.602
#> 787 0.531 0.217 TRUE -0.314 0.515 -0.610 0.542
#> 788 0.315 0.496 TRUE 0.180 0.516 0.349 0.727
#> 789 -0.249 0.269 TRUE 0.518 0.498 1.039 0.299
#> 790 -0.019 -0.557 TRUE -0.538 0.500 -1.077 0.282
#> 791 -0.183 -0.303 TRUE -0.120 0.492 -0.244 0.807
#> 792 0.389 0.643 TRUE 0.253 0.529 0.479 0.632
#> 793 -0.551 -1.051 TRUE -0.500 0.539 -0.928 0.354
#> 794 1.696 1.394 TRUE -0.302 0.715 -0.422 0.673
#> 795 0.291 0.340 TRUE 0.049 0.508 0.097 0.923
#> 796 0.578 0.735 TRUE 0.158 0.545 0.289 0.772
#> 797 -0.191 -0.661 TRUE -0.470 0.505 -0.932 0.351
#> 798 -0.696 -1.212 TRUE -0.515 0.559 -0.922 0.357
#> 799 -0.726 -1.457 TRUE -0.731 0.586 -1.248 0.212
#> 800 -1.144 -0.448 TRUE 0.697 0.543 1.282 0.2
#> 801 2.071 1.328 TRUE -0.742 0.758 -0.980 0.327
#> 802 -1.215 -0.893 TRUE 0.321 0.570 0.563 0.573
#> 803 1.394 1.117 TRUE -0.277 0.651 -0.425 0.671
#> 804 0.099 0.412 TRUE 0.313 0.506 0.620 0.536
#> 805 -0.416 -0.608 TRUE -0.192 0.506 -0.380 0.704
#> 806 -0.761 -1.132 TRUE -0.370 0.555 -0.667 0.505
#> 807 -0.959 -0.633 TRUE 0.326 0.535 0.610 0.542
#> 808 -0.344 -0.190 TRUE 0.154 0.493 0.312 0.755
#> 809 -0.026 0.104 TRUE 0.130 0.493 0.264 0.792
#> 810 -1.196 -0.482 TRUE 0.714 0.549 1.300 0.194
#> 811 -1.090 -0.893 TRUE 0.198 0.560 0.354 0.724
#> 812 0.146 0.180 TRUE 0.034 0.498 0.069 0.945
#> 813 1.402 2.071 TRUE 0.669 0.765 0.874 0.382
#> 814 -0.654 -0.827 TRUE -0.172 0.527 -0.327 0.744
#> 815 0.576 0.365 TRUE -0.211 0.523 -0.403 0.687
#> 816 0.079 0.164 TRUE 0.086 0.496 0.173 0.862
#> 817 -0.587 -0.554 TRUE 0.033 0.510 0.066 0.948
#> 818 1.052 1.635 TRUE 0.583 0.675 0.864 0.388
#> 819 -0.930 -1.437 TRUE -0.507 0.595 -0.851 0.395
#> 820 1.229 0.534 TRUE -0.694 0.590 -1.178 0.239
#> 821 0.084 0.407 TRUE 0.323 0.505 0.639 0.523
#> 822 -0.127 -0.254 TRUE -0.128 0.492 -0.259 0.795
#> 823 -0.037 0.946 TRUE 0.983 0.543 1.811 0.07
#> 824 -0.061 0.177 TRUE 0.238 0.495 0.482 0.63
#> 825 -0.548 0.402 TRUE 0.949 0.511 1.856 0.063
#> 826 0.224 0.512 TRUE 0.288 0.514 0.561 0.575
#> 827 0.447 -0.181 TRUE -0.628 0.506 -1.243 0.214
#> 828 0.421 0.286 TRUE -0.136 0.511 -0.265 0.791
#> 829 -0.481 0.283 TRUE 0.765 0.504 1.517 0.129
#> 830 -0.048 0.094 TRUE 0.142 0.493 0.288 0.773
#> 831 -0.889 -0.761 TRUE 0.128 0.536 0.239 0.811
#> 832 -0.946 -0.820 TRUE 0.125 0.544 0.230 0.818
#> 833 0.792 0.990 TRUE 0.198 0.581 0.340 0.734
#> 834 -0.963 -0.241 TRUE 0.723 0.524 1.379 0.168
#> 835 -0.048 -1.248 TRUE -1.200 0.549 -2.187 0.029
#> 836 0.596 0.832 TRUE 0.236 0.554 0.425 0.671
#> 837 -1.598 -0.756 TRUE 0.842 0.604 1.394 0.163
#> 838 -2.038 -2.281 TRUE -0.243 0.799 -0.304 0.761
#> 839 1.721 1.807 TRUE 0.086 0.766 0.112 0.91
#> 840 -0.873 -0.677 TRUE 0.196 0.531 0.369 0.712
#> 841 0.928 0.470 TRUE -0.459 0.555 -0.826 0.409
#> 842 1.491 1.319 TRUE -0.172 0.683 -0.252 0.801
#> 843 1.471 1.108 TRUE -0.363 0.660 -0.551 0.582
#> 844 0.048 -0.104 TRUE -0.152 0.492 -0.309 0.758
#> 845 1.012 0.820 TRUE -0.192 0.585 -0.328 0.743
#> 846 -0.131 0.040 TRUE 0.172 0.492 0.349 0.727
#> 847 0.710 0.855 TRUE 0.145 0.563 0.257 0.797
#> 848 0.868 -0.051 TRUE -0.919 0.535 -1.716 0.086
#> 849 1.331 0.664 TRUE -0.667 0.609 -1.096 0.273
#> 850 0.327 0.839 TRUE 0.512 0.541 0.947 0.344
#> 851 0.979 1.193 TRUE 0.214 0.617 0.348 0.728
#> 852 0.462 0.892 TRUE 0.430 0.552 0.780 0.435
#> 853 -0.568 -0.425 TRUE 0.143 0.504 0.284 0.777
#> 854 0.528 0.882 TRUE 0.354 0.554 0.639 0.523
#> 855 0.397 0.056 TRUE -0.340 0.504 -0.675 0.5
#> 856 -0.901 -0.753 TRUE 0.148 0.537 0.275 0.783
#> 857 -0.624 -0.574 TRUE 0.050 0.512 0.098 0.922
#> 858 -0.640 0.238 TRUE 0.878 0.509 1.725 0.085
#> 859 1.374 1.571 TRUE 0.197 0.698 0.283 0.777
#> 860 0.286 0.347 TRUE 0.062 0.508 0.121 0.903
#> 861 -0.025 -0.032 TRUE -0.007 0.491 -0.015 0.988
#> 862 -0.127 -0.897 TRUE -0.770 0.519 -1.484 0.138
#> 863 -0.335 -0.493 TRUE -0.158 0.499 -0.316 0.752
#> 864 -0.148 -0.516 TRUE -0.368 0.498 -0.739 0.46
#> 865 0.602 0.257 TRUE -0.344 0.521 -0.662 0.508
#> 866 0.087 -0.291 TRUE -0.379 0.494 -0.767 0.443
#> 867 -0.124 0.133 TRUE 0.257 0.494 0.521 0.602
#> 868 1.221 0.131 TRUE -1.090 0.574 -1.898 0.058
#> 869 -0.753 -0.577 TRUE 0.176 0.519 0.339 0.735
#> 870 -1.273 -1.349 TRUE -0.076 0.613 -0.124 0.902
#> 871 1.009 0.650 TRUE -0.359 0.573 -0.627 0.531
#> 872 -0.698 -1.415 TRUE -0.718 0.580 -1.237 0.216
#> 873 -1.121 -0.771 TRUE 0.350 0.555 0.631 0.528
#> 874 0.205 0.319 TRUE 0.114 0.504 0.227 0.821
#> 875 0.432 0.182 TRUE -0.251 0.509 -0.493 0.622
#> 876 0.939 0.331 TRUE -0.609 0.550 -1.107 0.268
#> 877 0.154 0.233 TRUE 0.078 0.500 0.157 0.876
#> 878 -0.833 -0.787 TRUE 0.047 0.534 0.088 0.93
#> 879 -0.382 0.384 TRUE 0.766 0.505 1.516 0.13
#> 880 0.730 1.279 TRUE 0.549 0.607 0.905 0.366
#> 881 -0.702 -0.145 TRUE 0.557 0.506 1.099 0.272
#> 882 -1.754 -1.969 TRUE -0.215 0.730 -0.295 0.768
#> 883 0.344 1.341 TRUE 0.997 0.594 1.678 0.093
#> 884 1.252 1.432 TRUE 0.181 0.669 0.270 0.787
#> 885 -0.223 -0.130 TRUE 0.092 0.491 0.188 0.851
#> 886 1.394 1.807 TRUE 0.413 0.729 0.566 0.572
#> 887 1.116 0.921 TRUE -0.194 0.604 -0.322 0.748
#> 888 0.649 -0.017 TRUE -0.665 0.518 -1.284 0.199
#> 889 -0.923 -0.932 TRUE -0.009 0.549 -0.016 0.987
#> 890 -1.089 -1.414 TRUE -0.326 0.604 -0.539 0.59
#> 891 0.072 -0.101 TRUE -0.174 0.492 -0.353 0.724
#> 892 0.145 0.043 TRUE -0.103 0.495 -0.207 0.836
#> 893 -1.075 -0.593 TRUE 0.482 0.542 0.889 0.374
#> 894 0.785 1.209 TRUE 0.425 0.603 0.704 0.481
#> 895 -0.789 -0.084 TRUE 0.706 0.512 1.379 0.168
#> 896 0.025 -0.641 TRUE -0.666 0.504 -1.320 0.187
#> 897 0.121 0.197 TRUE 0.076 0.498 0.153 0.878
#> 898 -0.774 -0.940 TRUE -0.167 0.541 -0.308 0.758
#> 899 0.535 0.054 TRUE -0.481 0.512 -0.940 0.347
#> 900 -0.872 -0.339 TRUE 0.533 0.519 1.026 0.305
#> 901 -0.206 -0.154 TRUE 0.052 0.491 0.105 0.916
#> 902 1.159 1.328 TRUE 0.170 0.648 0.262 0.793
#> 903 0.722 0.408 TRUE -0.314 0.535 -0.586 0.558
#> 904 -0.460 -0.090 TRUE 0.370 0.496 0.745 0.456
#> 905 1.239 1.045 TRUE -0.194 0.627 -0.309 0.757
#> 906 0.584 1.186 TRUE 0.602 0.587 1.025 0.305
#> 907 -0.306 -0.120 TRUE 0.186 0.492 0.378 0.705
#> 908 0.218 -0.623 TRUE -0.841 0.508 -1.658 0.097
#> 909 -0.723 -0.954 TRUE -0.231 0.539 -0.429 0.668
#> 910 -0.406 -0.660 TRUE -0.253 0.508 -0.499 0.618
#> 911 1.457 1.812 TRUE 0.355 0.737 0.482 0.63
#> 912 0.892 1.323 TRUE 0.431 0.624 0.691 0.49
#> 913 0.025 0.106 TRUE 0.081 0.494 0.163 0.87
#> 914 -0.171 -0.128 TRUE 0.044 0.491 0.089 0.929
#> 915 1.387 1.751 TRUE 0.364 0.721 0.505 0.614
#> 916 1.459 0.887 TRUE -0.572 0.640 -0.894 0.371
#> 917 -0.227 -0.223 TRUE 0.003 0.492 0.007 0.994
#> 918 -1.763 -1.969 TRUE -0.205 0.731 -0.281 0.779
#> 919 0.877 1.190 TRUE 0.313 0.608 0.514 0.607
#> 920 -1.631 -2.024 TRUE -0.393 0.724 -0.542 0.588
#> 921 2.071 2.071 TRUE 0.000 0.840 0.000 1
#> 922 -0.779 -1.824 TRUE -1.044 0.633 -1.650 0.099
#> 923 1.505 1.263 TRUE -0.242 0.679 -0.357 0.721
#> 924 0.362 1.696 TRUE 1.334 0.642 2.079 0.038
#> 925 0.578 0.189 TRUE -0.389 0.517 -0.751 0.452
#> 926 1.361 1.150 TRUE -0.211 0.651 -0.324 0.746
#> 927 0.727 0.739 TRUE 0.012 0.555 0.022 0.982
#> 928 1.400 0.134 TRUE -1.266 0.596 -2.124 0.034
#> 929 0.858 0.232 TRUE -0.626 0.540 -1.161 0.246
#> 930 -0.407 -0.990 TRUE -0.584 0.529 -1.103 0.27
#> 931 -0.435 -0.274 TRUE 0.160 0.497 0.323 0.747
#> 932 -0.152 -0.063 TRUE 0.088 0.491 0.180 0.857
#> 933 1.036 1.510 TRUE 0.474 0.658 0.721 0.471
#> 934 -0.894 -0.683 TRUE 0.211 0.532 0.397 0.692
#> 935 0.848 1.224 TRUE 0.376 0.609 0.618 0.537
#> 936 -0.487 -0.033 TRUE 0.454 0.497 0.912 0.362
#> 937 -0.878 -1.176 TRUE -0.298 0.566 -0.527 0.598
#> 938 0.955 0.797 TRUE -0.158 0.578 -0.273 0.785
#> 939 0.450 -0.045 TRUE -0.495 0.506 -0.979 0.328
#> 940 -0.176 0.328 TRUE 0.505 0.500 1.009 0.313
#> 941 0.634 0.476 TRUE -0.158 0.532 -0.296 0.767
#> 942 -0.189 0.666 TRUE 0.854 0.519 1.646 0.1
#> 943 -1.258 -1.583 TRUE -0.325 0.636 -0.511 0.61
#> 944 2.071 1.519 TRUE -0.552 0.777 -0.710 0.477
#> 945 -0.811 -0.398 TRUE 0.413 0.516 0.800 0.423
#> 946 -0.416 -0.854 TRUE -0.438 0.520 -0.843 0.399
#> 947 -0.619 1.171 TRUE 1.790 0.576 3.107 0.002
#> 948 -0.749 -1.348 TRUE -0.599 0.575 -1.041 0.298
#> 949 0.654 0.624 TRUE -0.030 0.542 -0.056 0.955
#> 950 0.482 0.582 TRUE 0.100 0.529 0.189 0.85
#> 951 0.562 0.432 TRUE -0.130 0.525 -0.248 0.804
#> 952 0.409 -0.108 TRUE -0.518 0.503 -1.028 0.304
#> 953 0.200 -0.278 TRUE -0.477 0.496 -0.962 0.336
#> 954 -0.389 -0.401 TRUE -0.012 0.498 -0.024 0.981
#> 955 0.738 -0.025 TRUE -0.763 0.525 -1.455 0.146
#> 956 0.046 0.148 TRUE 0.102 0.495 0.205 0.837
#> 957 -0.075 -0.250 TRUE -0.175 0.492 -0.357 0.721
#> 958 -1.291 -1.075 TRUE 0.216 0.591 0.366 0.715
#> 959 -0.254 -0.064 TRUE 0.189 0.492 0.385 0.7
#> 960 -0.986 -0.694 TRUE 0.292 0.540 0.540 0.589
#> 961 0.853 0.561 TRUE -0.292 0.554 -0.527 0.598
#> 962 -0.498 -0.926 TRUE -0.428 0.527 -0.812 0.417
#> 963 -0.966 -0.638 TRUE 0.328 0.536 0.613 0.54
#> 964 -0.927 -0.677 TRUE 0.250 0.535 0.468 0.64
#> 965 -1.094 -1.556 TRUE -0.463 0.620 -0.746 0.455
#> 966 -1.645 -0.871 TRUE 0.774 0.615 1.259 0.208
#> 967 -0.573 -0.863 TRUE -0.290 0.525 -0.551 0.581
#> 968 1.034 1.792 TRUE 0.758 0.694 1.092 0.275
#> 969 -0.453 -1.145 TRUE -0.691 0.544 -1.272 0.203
#> 970 -1.068 -1.817 TRUE -0.750 0.649 -1.155 0.248
#> 971 0.182 0.046 TRUE -0.136 0.496 -0.274 0.784
#> 972 -1.247 -0.400 TRUE 0.847 0.552 1.535 0.125
#> 973 0.499 0.792 TRUE 0.293 0.545 0.538 0.591
#> 974 -0.774 -1.047 TRUE -0.272 0.549 -0.496 0.62
#> 975 0.921 0.913 TRUE -0.008 0.585 -0.014 0.989
#> 976 0.780 0.905 TRUE 0.125 0.573 0.219 0.827
#> 977 0.010 0.431 TRUE 0.421 0.505 0.833 0.405
#> 978 0.326 0.241 TRUE -0.085 0.505 -0.168 0.867
#> 979 1.265 1.510 TRUE 0.245 0.679 0.361 0.718
#> 980 -0.218 -0.202 TRUE 0.016 0.491 0.032 0.974
#> 981 1.066 1.419 TRUE 0.352 0.650 0.543 0.587
#> 982 -1.433 -1.824 TRUE -0.390 0.680 -0.574 0.566
#> 983 -0.731 -0.581 TRUE 0.150 0.518 0.290 0.772
#> 984 -1.139 -1.433 TRUE -0.294 0.610 -0.482 0.63
#> 985 0.624 0.991 TRUE 0.367 0.570 0.645 0.519
#> 986 0.161 0.034 TRUE -0.128 0.495 -0.258 0.797
#> 987 -1.087 -1.402 TRUE -0.314 0.603 -0.522 0.602
#> 988 -2.038 -1.629 TRUE 0.408 0.725 0.563 0.574
#> 989 -0.194 0.111 TRUE 0.304 0.493 0.617 0.537
#> 990 -1.396 -1.677 TRUE -0.281 0.659 -0.426 0.67
#> 991 -0.880 -1.393 TRUE -0.513 0.587 -0.873 0.383
#> 992 0.351 0.533 TRUE 0.182 0.520 0.349 0.727
#> 993 2.071 0.696 TRUE -1.375 0.710 -1.937 0.053
#> 994 0.724 0.050 TRUE -0.674 0.524 -1.286 0.198
#> 995 -0.447 0.435 TRUE 0.881 0.510 1.729 0.084
#> 996 1.536 1.278 TRUE -0.258 0.684 -0.378 0.705
#> 997 -0.311 0.235 TRUE 0.546 0.498 1.096 0.273
#> 998 0.265 -0.380 TRUE -0.645 0.501 -1.289 0.197
#> 999 -0.303 -0.828 TRUE -0.524 0.515 -1.017 0.309
#> 1000 -0.224 -0.513 TRUE -0.289 0.498 -0.580 0.562
# single response pattern change using EAP information
RCI(mod, predat=dat_pre[1,], postdat=dat_post[1,])
#> pre.score post.score converged diff SE z p
#> 1 0.785 -0.266 TRUE -1.051 0.529 -1.986 0.047
# WLE estimator with Fisher information for SE (see Jabrayilov et al. 2016)
RCI(mod, predat = dat_pre[1,], postdat = dat_post[1,],
method = 'WLE', Fisher = TRUE)
#> pre.score post.score converged diff SE z p
#> 1 0.813 -0.284 TRUE -1.096 0.563 -1.946 0.052
# multiple respondents
RCI(mod, predat = dat_pre[1:6,], postdat = dat_post[1:6,])
#> pre.score post.score converged diff SE z p
#> 1 0.785 -0.266 TRUE -1.051 0.529 -1.986 0.047
#> 2 -1.019 -2.281 TRUE -1.261 0.708 -1.782 0.075
#> 3 -1.230 -1.577 TRUE -0.346 0.633 -0.547 0.584
#> 4 -0.749 -1.150 TRUE -0.401 0.556 -0.722 0.47
#> 5 -1.119 -0.949 TRUE 0.170 0.566 0.301 0.763
#> 6 -0.892 -0.725 TRUE 0.167 0.534 0.313 0.755
# include large-sample z-type cutoffs
RCI(mod, predat = dat_pre[1:6,], postdat = dat_post[1:6,],
cutoffs = c(-1.96, 1.96))
#> pre.score post.score converged diff SE z p cut_decision
#> 1 0.785 -0.266 TRUE -1.051 0.529 -1.986 0.047 decreased
#> 2 -1.019 -2.281 TRUE -1.261 0.708 -1.782 0.075 unchanged
#> 3 -1.230 -1.577 TRUE -0.346 0.633 -0.547 0.584 unchanged
#> 4 -0.749 -1.150 TRUE -0.401 0.556 -0.722 0.47 unchanged
#> 5 -1.119 -0.949 TRUE 0.170 0.566 0.301 0.763 unchanged
#> 6 -0.892 -0.725 TRUE 0.167 0.534 0.313 0.755 unchanged
######
# CTT version by omitting IRT model
# Requires either sample or population SEM's as input
(istats <- itemstats(dat_pre)$overall)
#> N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
#> 1000 10.638 4.825 0.208 0.064 0.841 1.923
SEM.alpha <- istats$SEM.alpha # SEM estimate of dat_pre
# assumes SEM.post = SEM.pre
RCI(predat = dat_pre, postdat = dat_post, SEM.pre=SEM.alpha)
#> pre.score post.score diff SE z p
#> 1 15 9 -6 2.72 -2.206 0.027
#> 2 4 0 -4 2.72 -1.471 0.141
#> 3 4 3 -1 2.72 -0.368 0.713
#> 4 6 4 -2 2.72 -0.735 0.462
#> 5 4 5 1 2.72 0.368 0.713
#> 6 6 7 1 2.72 0.368 0.713
#> 7 3 8 5 2.72 1.838 0.066
#> 8 13 12 -1 2.72 -0.368 0.713
#> 9 17 16 -1 2.72 -0.368 0.713
#> 10 16 17 1 2.72 0.368 0.713
#> 11 13 14 1 2.72 0.368 0.713
#> 12 16 12 -4 2.72 -1.471 0.141
#> 13 12 11 -1 2.72 -0.368 0.713
#> 14 9 3 -6 2.72 -2.206 0.027
#> 15 6 6 0 2.72 0.000 1
#> 16 13 13 0 2.72 0.000 1
#> 17 13 11 -2 2.72 -0.735 0.462
#> 18 0 4 4 2.72 1.471 0.141
#> 19 6 8 2 2.72 0.735 0.462
#> 20 4 5 1 2.72 0.368 0.713
#> 21 16 13 -3 2.72 -1.103 0.27
#> 22 12 12 0 2.72 0.000 1
#> 23 13 10 -3 2.72 -1.103 0.27
#> 24 18 17 -1 2.72 -0.368 0.713
#> 25 3 3 0 2.72 0.000 1
#> 26 12 13 1 2.72 0.368 0.713
#> 27 17 15 -2 2.72 -0.735 0.462
#> 28 14 15 1 2.72 0.368 0.713
#> 29 13 17 4 2.72 1.471 0.141
#> 30 10 7 -3 2.72 -1.103 0.27
#> 31 15 13 -2 2.72 -0.735 0.462
#> 32 3 3 0 2.72 0.000 1
#> 33 8 12 4 2.72 1.471 0.141
#> 34 17 18 1 2.72 0.368 0.713
#> 35 6 10 4 2.72 1.471 0.141
#> 36 18 18 0 2.72 0.000 1
#> 37 10 7 -3 2.72 -1.103 0.27
#> 38 17 13 -4 2.72 -1.471 0.141
#> 39 10 3 -7 2.72 -2.573 0.01
#> 40 0 2 2 2.72 0.735 0.462
#> 41 12 10 -2 2.72 -0.735 0.462
#> 42 19 20 1 2.72 0.368 0.713
#> 43 11 10 -1 2.72 -0.368 0.713
#> 44 5 3 -2 2.72 -0.735 0.462
#> 45 16 15 -1 2.72 -0.368 0.713
#> 46 8 12 4 2.72 1.471 0.141
#> 47 17 17 0 2.72 0.000 1
#> 48 12 10 -2 2.72 -0.735 0.462
#> 49 20 16 -4 2.72 -1.471 0.141
#> 50 8 7 -1 2.72 -0.368 0.713
#> 51 9 11 2 2.72 0.735 0.462
#> 52 7 5 -2 2.72 -0.735 0.462
#> 53 13 10 -3 2.72 -1.103 0.27
#> 54 6 10 4 2.72 1.471 0.141
#> 55 7 6 -1 2.72 -0.368 0.713
#> 56 7 9 2 2.72 0.735 0.462
#> 57 5 7 2 2.72 0.735 0.462
#> 58 11 3 -8 2.72 -2.941 0.003
#> 59 13 10 -3 2.72 -1.103 0.27
#> 60 18 18 0 2.72 0.000 1
#> 61 7 7 0 2.72 0.000 1
#> 62 15 16 1 2.72 0.368 0.713
#> 63 11 11 0 2.72 0.000 1
#> 64 7 8 1 2.72 0.368 0.713
#> 65 2 7 5 2.72 1.838 0.066
#> 66 7 4 -3 2.72 -1.103 0.27
#> 67 5 4 -1 2.72 -0.368 0.713
#> 68 9 12 3 2.72 1.103 0.27
#> 69 11 17 6 2.72 2.206 0.027
#> 70 12 11 -1 2.72 -0.368 0.713
#> 71 19 18 -1 2.72 -0.368 0.713
#> 72 15 16 1 2.72 0.368 0.713
#> 73 9 5 -4 2.72 -1.471 0.141
#> 74 8 10 2 2.72 0.735 0.462
#> 75 7 5 -2 2.72 -0.735 0.462
#> 76 16 17 1 2.72 0.368 0.713
#> 77 9 7 -2 2.72 -0.735 0.462
#> 78 12 9 -3 2.72 -1.103 0.27
#> 79 20 18 -2 2.72 -0.735 0.462
#> 80 6 8 2 2.72 0.735 0.462
#> 81 16 16 0 2.72 0.000 1
#> 82 8 12 4 2.72 1.471 0.141
#> 83 7 8 1 2.72 0.368 0.713
#> 84 16 15 -1 2.72 -0.368 0.713
#> 85 17 13 -4 2.72 -1.471 0.141
#> 86 5 6 1 2.72 0.368 0.713
#> 87 11 11 0 2.72 0.000 1
#> 88 17 15 -2 2.72 -0.735 0.462
#> 89 17 11 -6 2.72 -2.206 0.027
#> 90 12 8 -4 2.72 -1.471 0.141
#> 91 13 15 2 2.72 0.735 0.462
#> 92 13 14 1 2.72 0.368 0.713
#> 93 5 3 -2 2.72 -0.735 0.462
#> 94 13 13 0 2.72 0.000 1
#> 95 7 10 3 2.72 1.103 0.27
#> 96 8 10 2 2.72 0.735 0.462
#> 97 14 9 -5 2.72 -1.838 0.066
#> 98 8 6 -2 2.72 -0.735 0.462
#> 99 11 11 0 2.72 0.000 1
#> 100 5 5 0 2.72 0.000 1
#> 101 5 11 6 2.72 2.206 0.027
#> 102 5 0 -5 2.72 -1.838 0.066
#> 103 11 11 0 2.72 0.000 1
#> 104 16 19 3 2.72 1.103 0.27
#> 105 7 6 -1 2.72 -0.368 0.713
#> 106 4 6 2 2.72 0.735 0.462
#> 107 5 7 2 2.72 0.735 0.462
#> 108 9 11 2 2.72 0.735 0.462
#> 109 14 10 -4 2.72 -1.471 0.141
#> 110 6 5 -1 2.72 -0.368 0.713
#> 111 14 19 5 2.72 1.838 0.066
#> 112 11 10 -1 2.72 -0.368 0.713
#> 113 12 11 -1 2.72 -0.368 0.713
#> 114 4 2 -2 2.72 -0.735 0.462
#> 115 7 7 0 2.72 0.000 1
#> 116 17 15 -2 2.72 -0.735 0.462
#> 117 4 1 -3 2.72 -1.103 0.27
#> 118 12 14 2 2.72 0.735 0.462
#> 119 4 7 3 2.72 1.103 0.27
#> 120 14 13 -1 2.72 -0.368 0.713
#> 121 9 9 0 2.72 0.000 1
#> 122 15 18 3 2.72 1.103 0.27
#> 123 4 6 2 2.72 0.735 0.462
#> 124 13 16 3 2.72 1.103 0.27
#> 125 15 13 -2 2.72 -0.735 0.462
#> 126 10 5 -5 2.72 -1.838 0.066
#> 127 3 2 -1 2.72 -0.368 0.713
#> 128 15 13 -2 2.72 -0.735 0.462
#> 129 9 2 -7 2.72 -2.573 0.01
#> 130 12 13 1 2.72 0.368 0.713
#> 131 5 3 -2 2.72 -0.735 0.462
#> 132 5 6 1 2.72 0.368 0.713
#> 133 2 3 1 2.72 0.368 0.713
#> 134 15 13 -2 2.72 -0.735 0.462
#> 135 20 17 -3 2.72 -1.103 0.27
#> 136 14 13 -1 2.72 -0.368 0.713
#> 137 11 14 3 2.72 1.103 0.27
#> 138 17 14 -3 2.72 -1.103 0.27
#> 139 13 15 2 2.72 0.735 0.462
#> 140 12 11 -1 2.72 -0.368 0.713
#> 141 4 1 -3 2.72 -1.103 0.27
#> 142 16 20 4 2.72 1.471 0.141
#> 143 15 14 -1 2.72 -0.368 0.713
#> 144 5 6 1 2.72 0.368 0.713
#> 145 10 15 5 2.72 1.838 0.066
#> 146 16 16 0 2.72 0.000 1
#> 147 12 8 -4 2.72 -1.471 0.141
#> 148 8 13 5 2.72 1.838 0.066
#> 149 9 8 -1 2.72 -0.368 0.713
#> 150 17 15 -2 2.72 -0.735 0.462
#> 151 16 15 -1 2.72 -0.368 0.713
#> 152 14 11 -3 2.72 -1.103 0.27
#> 153 13 13 0 2.72 0.000 1
#> 154 6 6 0 2.72 0.000 1
#> 155 0 1 1 2.72 0.368 0.713
#> 156 7 2 -5 2.72 -1.838 0.066
#> 157 10 7 -3 2.72 -1.103 0.27
#> 158 11 18 7 2.72 2.573 0.01
#> 159 8 6 -2 2.72 -0.735 0.462
#> 160 8 8 0 2.72 0.000 1
#> 161 4 2 -2 2.72 -0.735 0.462
#> 162 4 4 0 2.72 0.000 1
#> 163 6 7 1 2.72 0.368 0.713
#> 164 15 15 0 2.72 0.000 1
#> 165 14 15 1 2.72 0.368 0.713
#> 166 18 16 -2 2.72 -0.735 0.462
#> 167 9 5 -4 2.72 -1.471 0.141
#> 168 12 10 -2 2.72 -0.735 0.462
#> 169 18 18 0 2.72 0.000 1
#> 170 9 5 -4 2.72 -1.471 0.141
#> 171 9 9 0 2.72 0.000 1
#> 172 2 1 -1 2.72 -0.368 0.713
#> 173 13 7 -6 2.72 -2.206 0.027
#> 174 9 9 0 2.72 0.000 1
#> 175 7 10 3 2.72 1.103 0.27
#> 176 18 12 -6 2.72 -2.206 0.027
#> 177 17 18 1 2.72 0.368 0.713
#> 178 5 2 -3 2.72 -1.103 0.27
#> 179 3 3 0 2.72 0.000 1
#> 180 0 2 2 2.72 0.735 0.462
#> 181 19 20 1 2.72 0.368 0.713
#> 182 16 12 -4 2.72 -1.471 0.141
#> 183 10 5 -5 2.72 -1.838 0.066
#> 184 10 15 5 2.72 1.838 0.066
#> 185 7 10 3 2.72 1.103 0.27
#> 186 16 17 1 2.72 0.368 0.713
#> 187 3 8 5 2.72 1.838 0.066
#> 188 16 19 3 2.72 1.103 0.27
#> 189 13 9 -4 2.72 -1.471 0.141
#> 190 7 8 1 2.72 0.368 0.713
#> 191 3 2 -1 2.72 -0.368 0.713
#> 192 10 8 -2 2.72 -0.735 0.462
#> 193 3 12 9 2.72 3.309 0.001
#> 194 11 11 0 2.72 0.000 1
#> 195 3 7 4 2.72 1.471 0.141
#> 196 6 7 1 2.72 0.368 0.713
#> 197 13 11 -2 2.72 -0.735 0.462
#> 198 17 17 0 2.72 0.000 1
#> 199 9 7 -2 2.72 -0.735 0.462
#> 200 16 18 2 2.72 0.735 0.462
#> 201 10 4 -6 2.72 -2.206 0.027
#> 202 9 9 0 2.72 0.000 1
#> 203 4 3 -1 2.72 -0.368 0.713
#> 204 6 2 -4 2.72 -1.471 0.141
#> 205 12 12 0 2.72 0.000 1
#> 206 5 4 -1 2.72 -0.368 0.713
#> 207 2 3 1 2.72 0.368 0.713
#> 208 15 19 4 2.72 1.471 0.141
#> 209 6 2 -4 2.72 -1.471 0.141
#> 210 16 18 2 2.72 0.735 0.462
#> 211 12 13 1 2.72 0.368 0.713
#> 212 2 3 1 2.72 0.368 0.713
#> 213 11 10 -1 2.72 -0.368 0.713
#> 214 12 13 1 2.72 0.368 0.713
#> 215 14 15 1 2.72 0.368 0.713
#> 216 19 19 0 2.72 0.000 1
#> 217 16 15 -1 2.72 -0.368 0.713
#> 218 19 20 1 2.72 0.368 0.713
#> 219 1 0 -1 2.72 -0.368 0.713
#> 220 13 12 -1 2.72 -0.368 0.713
#> 221 14 11 -3 2.72 -1.103 0.27
#> 222 19 16 -3 2.72 -1.103 0.27
#> 223 3 5 2 2.72 0.735 0.462
#> 224 2 1 -1 2.72 -0.368 0.713
#> 225 16 13 -3 2.72 -1.103 0.27
#> 226 12 11 -1 2.72 -0.368 0.713
#> 227 6 6 0 2.72 0.000 1
#> 228 5 8 3 2.72 1.103 0.27
#> 229 1 0 -1 2.72 -0.368 0.713
#> 230 12 13 1 2.72 0.368 0.713
#> 231 3 4 1 2.72 0.368 0.713
#> 232 10 7 -3 2.72 -1.103 0.27
#> 233 12 10 -2 2.72 -0.735 0.462
#> 234 14 16 2 2.72 0.735 0.462
#> 235 18 16 -2 2.72 -0.735 0.462
#> 236 10 10 0 2.72 0.000 1
#> 237 11 6 -5 2.72 -1.838 0.066
#> 238 14 19 5 2.72 1.838 0.066
#> 239 3 2 -1 2.72 -0.368 0.713
#> 240 8 4 -4 2.72 -1.471 0.141
#> 241 13 15 2 2.72 0.735 0.462
#> 242 12 13 1 2.72 0.368 0.713
#> 243 17 16 -1 2.72 -0.368 0.713
#> 244 9 7 -2 2.72 -0.735 0.462
#> 245 7 6 -1 2.72 -0.368 0.713
#> 246 10 8 -2 2.72 -0.735 0.462
#> 247 14 12 -2 2.72 -0.735 0.462
#> 248 11 11 0 2.72 0.000 1
#> 249 11 10 -1 2.72 -0.368 0.713
#> 250 18 19 1 2.72 0.368 0.713
#> 251 4 5 1 2.72 0.368 0.713
#> 252 1 3 2 2.72 0.735 0.462
#> 253 4 1 -3 2.72 -1.103 0.27
#> 254 8 10 2 2.72 0.735 0.462
#> 255 10 10 0 2.72 0.000 1
#> 256 17 18 1 2.72 0.368 0.713
#> 257 18 20 2 2.72 0.735 0.462
#> 258 11 10 -1 2.72 -0.368 0.713
#> 259 17 17 0 2.72 0.000 1
#> 260 12 13 1 2.72 0.368 0.713
#> 261 11 12 1 2.72 0.368 0.713
#> 262 9 11 2 2.72 0.735 0.462
#> 263 13 11 -2 2.72 -0.735 0.462
#> 264 17 16 -1 2.72 -0.368 0.713
#> 265 11 11 0 2.72 0.000 1
#> 266 19 18 -1 2.72 -0.368 0.713
#> 267 10 10 0 2.72 0.000 1
#> 268 5 9 4 2.72 1.471 0.141
#> 269 11 12 1 2.72 0.368 0.713
#> 270 17 14 -3 2.72 -1.103 0.27
#> 271 17 13 -4 2.72 -1.471 0.141
#> 272 20 19 -1 2.72 -0.368 0.713
#> 273 8 7 -1 2.72 -0.368 0.713
#> 274 16 19 3 2.72 1.103 0.27
#> 275 14 13 -1 2.72 -0.368 0.713
#> 276 4 8 4 2.72 1.471 0.141
#> 277 16 13 -3 2.72 -1.103 0.27
#> 278 11 11 0 2.72 0.000 1
#> 279 8 8 0 2.72 0.000 1
#> 280 2 4 2 2.72 0.735 0.462
#> 281 7 3 -4 2.72 -1.471 0.141
#> 282 5 10 5 2.72 1.838 0.066
#> 283 18 19 1 2.72 0.368 0.713
#> 284 10 14 4 2.72 1.471 0.141
#> 285 1 1 0 2.72 0.000 1
#> 286 5 10 5 2.72 1.838 0.066
#> 287 3 2 -1 2.72 -0.368 0.713
#> 288 7 13 6 2.72 2.206 0.027
#> 289 14 18 4 2.72 1.471 0.141
#> 290 17 17 0 2.72 0.000 1
#> 291 14 12 -2 2.72 -0.735 0.462
#> 292 16 11 -5 2.72 -1.838 0.066
#> 293 4 3 -1 2.72 -0.368 0.713
#> 294 19 17 -2 2.72 -0.735 0.462
#> 295 8 12 4 2.72 1.471 0.141
#> 296 17 15 -2 2.72 -0.735 0.462
#> 297 16 18 2 2.72 0.735 0.462
#> 298 18 17 -1 2.72 -0.368 0.713
#> 299 10 10 0 2.72 0.000 1
#> 300 16 15 -1 2.72 -0.368 0.713
#> 301 8 11 3 2.72 1.103 0.27
#> 302 3 2 -1 2.72 -0.368 0.713
#> 303 13 11 -2 2.72 -0.735 0.462
#> 304 8 5 -3 2.72 -1.103 0.27
#> 305 11 11 0 2.72 0.000 1
#> 306 17 17 0 2.72 0.000 1
#> 307 12 8 -4 2.72 -1.471 0.141
#> 308 18 18 0 2.72 0.000 1
#> 309 3 2 -1 2.72 -0.368 0.713
#> 310 9 11 2 2.72 0.735 0.462
#> 311 8 9 1 2.72 0.368 0.713
#> 312 8 2 -6 2.72 -2.206 0.027
#> 313 20 20 0 2.72 0.000 1
#> 314 9 9 0 2.72 0.000 1
#> 315 16 15 -1 2.72 -0.368 0.713
#> 316 15 11 -4 2.72 -1.471 0.141
#> 317 11 8 -3 2.72 -1.103 0.27
#> 318 4 9 5 2.72 1.838 0.066
#> 319 5 5 0 2.72 0.000 1
#> 320 18 19 1 2.72 0.368 0.713
#> 321 14 11 -3 2.72 -1.103 0.27
#> 322 6 6 0 2.72 0.000 1
#> 323 14 10 -4 2.72 -1.471 0.141
#> 324 9 8 -1 2.72 -0.368 0.713
#> 325 11 10 -1 2.72 -0.368 0.713
#> 326 12 8 -4 2.72 -1.471 0.141
#> 327 8 6 -2 2.72 -0.735 0.462
#> 328 10 8 -2 2.72 -0.735 0.462
#> 329 14 13 -1 2.72 -0.368 0.713
#> 330 14 11 -3 2.72 -1.103 0.27
#> 331 13 13 0 2.72 0.000 1
#> 332 2 1 -1 2.72 -0.368 0.713
#> 333 12 10 -2 2.72 -0.735 0.462
#> 334 16 16 0 2.72 0.000 1
#> 335 9 15 6 2.72 2.206 0.027
#> 336 3 7 4 2.72 1.471 0.141
#> 337 8 8 0 2.72 0.000 1
#> 338 13 14 1 2.72 0.368 0.713
#> 339 11 9 -2 2.72 -0.735 0.462
#> 340 14 13 -1 2.72 -0.368 0.713
#> 341 8 10 2 2.72 0.735 0.462
#> 342 13 15 2 2.72 0.735 0.462
#> 343 15 7 -8 2.72 -2.941 0.003
#> 344 14 12 -2 2.72 -0.735 0.462
#> 345 9 11 2 2.72 0.735 0.462
#> 346 14 14 0 2.72 0.000 1
#> 347 15 16 1 2.72 0.368 0.713
#> 348 9 12 3 2.72 1.103 0.27
#> 349 16 18 2 2.72 0.735 0.462
#> 350 14 10 -4 2.72 -1.471 0.141
#> 351 7 7 0 2.72 0.000 1
#> 352 12 14 2 2.72 0.735 0.462
#> 353 7 9 2 2.72 0.735 0.462
#> 354 11 7 -4 2.72 -1.471 0.141
#> 355 11 13 2 2.72 0.735 0.462
#> 356 14 12 -2 2.72 -0.735 0.462
#> 357 6 12 6 2.72 2.206 0.027
#> 358 7 5 -2 2.72 -0.735 0.462
#> 359 11 10 -1 2.72 -0.368 0.713
#> 360 9 8 -1 2.72 -0.368 0.713
#> 361 15 18 3 2.72 1.103 0.27
#> 362 5 6 1 2.72 0.368 0.713
#> 363 8 10 2 2.72 0.735 0.462
#> 364 16 17 1 2.72 0.368 0.713
#> 365 14 17 3 2.72 1.103 0.27
#> 366 11 13 2 2.72 0.735 0.462
#> 367 9 11 2 2.72 0.735 0.462
#> 368 1 4 3 2.72 1.103 0.27
#> 369 11 9 -2 2.72 -0.735 0.462
#> 370 9 4 -5 2.72 -1.838 0.066
#> 371 16 19 3 2.72 1.103 0.27
#> 372 6 8 2 2.72 0.735 0.462
#> 373 16 16 0 2.72 0.000 1
#> 374 7 9 2 2.72 0.735 0.462
#> 375 18 18 0 2.72 0.000 1
#> 376 6 4 -2 2.72 -0.735 0.462
#> 377 13 14 1 2.72 0.368 0.713
#> 378 12 10 -2 2.72 -0.735 0.462
#> 379 13 15 2 2.72 0.735 0.462
#> 380 18 16 -2 2.72 -0.735 0.462
#> 381 9 11 2 2.72 0.735 0.462
#> 382 10 10 0 2.72 0.000 1
#> 383 6 6 0 2.72 0.000 1
#> 384 8 9 1 2.72 0.368 0.713
#> 385 15 17 2 2.72 0.735 0.462
#> 386 15 16 1 2.72 0.368 0.713
#> 387 6 13 7 2.72 2.573 0.01
#> 388 4 2 -2 2.72 -0.735 0.462
#> 389 9 11 2 2.72 0.735 0.462
#> 390 9 9 0 2.72 0.000 1
#> 391 4 10 6 2.72 2.206 0.027
#> 392 9 8 -1 2.72 -0.368 0.713
#> 393 6 4 -2 2.72 -0.735 0.462
#> 394 5 5 0 2.72 0.000 1
#> 395 1 3 2 2.72 0.735 0.462
#> 396 13 13 0 2.72 0.000 1
#> 397 15 17 2 2.72 0.735 0.462
#> 398 6 7 1 2.72 0.368 0.713
#> 399 1 1 0 2.72 0.000 1
#> 400 16 17 1 2.72 0.368 0.713
#> 401 9 9 0 2.72 0.000 1
#> 402 3 4 1 2.72 0.368 0.713
#> 403 3 2 -1 2.72 -0.368 0.713
#> 404 10 10 0 2.72 0.000 1
#> 405 15 17 2 2.72 0.735 0.462
#> 406 17 13 -4 2.72 -1.471 0.141
#> 407 3 8 5 2.72 1.838 0.066
#> 408 10 14 4 2.72 1.471 0.141
#> 409 15 8 -7 2.72 -2.573 0.01
#> 410 12 10 -2 2.72 -0.735 0.462
#> 411 8 6 -2 2.72 -0.735 0.462
#> 412 9 9 0 2.72 0.000 1
#> 413 14 17 3 2.72 1.103 0.27
#> 414 3 2 -1 2.72 -0.368 0.713
#> 415 5 3 -2 2.72 -0.735 0.462
#> 416 9 9 0 2.72 0.000 1
#> 417 12 8 -4 2.72 -1.471 0.141
#> 418 16 12 -4 2.72 -1.471 0.141
#> 419 9 9 0 2.72 0.000 1
#> 420 5 5 0 2.72 0.000 1
#> 421 14 16 2 2.72 0.735 0.462
#> 422 5 3 -2 2.72 -0.735 0.462
#> 423 18 19 1 2.72 0.368 0.713
#> 424 10 10 0 2.72 0.000 1
#> 425 9 12 3 2.72 1.103 0.27
#> 426 15 16 1 2.72 0.368 0.713
#> 427 4 6 2 2.72 0.735 0.462
#> 428 11 8 -3 2.72 -1.103 0.27
#> 429 14 14 0 2.72 0.000 1
#> 430 5 6 1 2.72 0.368 0.713
#> 431 19 19 0 2.72 0.000 1
#> 432 13 12 -1 2.72 -0.368 0.713
#> 433 14 20 6 2.72 2.206 0.027
#> 434 12 15 3 2.72 1.103 0.27
#> 435 16 16 0 2.72 0.000 1
#> 436 11 12 1 2.72 0.368 0.713
#> 437 11 10 -1 2.72 -0.368 0.713
#> 438 10 11 1 2.72 0.368 0.713
#> 439 9 7 -2 2.72 -0.735 0.462
#> 440 18 15 -3 2.72 -1.103 0.27
#> 441 2 3 1 2.72 0.368 0.713
#> 442 4 5 1 2.72 0.368 0.713
#> 443 15 11 -4 2.72 -1.471 0.141
#> 444 2 4 2 2.72 0.735 0.462
#> 445 16 9 -7 2.72 -2.573 0.01
#> 446 4 5 1 2.72 0.368 0.713
#> 447 10 13 3 2.72 1.103 0.27
#> 448 15 14 -1 2.72 -0.368 0.713
#> 449 11 8 -3 2.72 -1.103 0.27
#> 450 16 18 2 2.72 0.735 0.462
#> 451 3 3 0 2.72 0.000 1
#> 452 10 10 0 2.72 0.000 1
#> 453 17 19 2 2.72 0.735 0.462
#> 454 18 18 0 2.72 0.000 1
#> 455 16 18 2 2.72 0.735 0.462
#> 456 2 3 1 2.72 0.368 0.713
#> 457 13 14 1 2.72 0.368 0.713
#> 458 6 11 5 2.72 1.838 0.066
#> 459 5 4 -1 2.72 -0.368 0.713
#> 460 20 18 -2 2.72 -0.735 0.462
#> 461 9 5 -4 2.72 -1.471 0.141
#> 462 11 13 2 2.72 0.735 0.462
#> 463 10 11 1 2.72 0.368 0.713
#> 464 15 19 4 2.72 1.471 0.141
#> 465 10 9 -1 2.72 -0.368 0.713
#> 466 9 3 -6 2.72 -2.206 0.027
#> 467 3 4 1 2.72 0.368 0.713
#> 468 3 2 -1 2.72 -0.368 0.713
#> 469 18 19 1 2.72 0.368 0.713
#> 470 17 13 -4 2.72 -1.471 0.141
#> 471 12 13 1 2.72 0.368 0.713
#> 472 11 15 4 2.72 1.471 0.141
#> 473 15 12 -3 2.72 -1.103 0.27
#> 474 8 8 0 2.72 0.000 1
#> 475 4 6 2 2.72 0.735 0.462
#> 476 18 16 -2 2.72 -0.735 0.462
#> 477 4 5 1 2.72 0.368 0.713
#> 478 2 3 1 2.72 0.368 0.713
#> 479 14 17 3 2.72 1.103 0.27
#> 480 9 5 -4 2.72 -1.471 0.141
#> 481 6 8 2 2.72 0.735 0.462
#> 482 20 20 0 2.72 0.000 1
#> 483 8 8 0 2.72 0.000 1
#> 484 2 3 1 2.72 0.368 0.713
#> 485 15 12 -3 2.72 -1.103 0.27
#> 486 15 16 1 2.72 0.368 0.713
#> 487 9 12 3 2.72 1.103 0.27
#> 488 8 6 -2 2.72 -0.735 0.462
#> 489 13 17 4 2.72 1.471 0.141
#> 490 12 9 -3 2.72 -1.103 0.27
#> 491 14 10 -4 2.72 -1.471 0.141
#> 492 19 18 -1 2.72 -0.368 0.713
#> 493 14 10 -4 2.72 -1.471 0.141
#> 494 11 6 -5 2.72 -1.838 0.066
#> 495 5 4 -1 2.72 -0.368 0.713
#> 496 12 12 0 2.72 0.000 1
#> 497 13 14 1 2.72 0.368 0.713
#> 498 19 18 -1 2.72 -0.368 0.713
#> 499 7 8 1 2.72 0.368 0.713
#> 500 20 20 0 2.72 0.000 1
#> 501 6 8 2 2.72 0.735 0.462
#> 502 17 18 1 2.72 0.368 0.713
#> 503 9 9 0 2.72 0.000 1
#> 504 12 13 1 2.72 0.368 0.713
#> 505 8 13 5 2.72 1.838 0.066
#> 506 9 11 2 2.72 0.735 0.462
#> 507 9 8 -1 2.72 -0.368 0.713
#> 508 6 5 -1 2.72 -0.368 0.713
#> 509 15 14 -1 2.72 -0.368 0.713
#> 510 15 12 -3 2.72 -1.103 0.27
#> 511 14 14 0 2.72 0.000 1
#> 512 1 0 -1 2.72 -0.368 0.713
#> 513 5 11 6 2.72 2.206 0.027
#> 514 5 4 -1 2.72 -0.368 0.713
#> 515 15 11 -4 2.72 -1.471 0.141
#> 516 19 18 -1 2.72 -0.368 0.713
#> 517 16 15 -1 2.72 -0.368 0.713
#> 518 6 6 0 2.72 0.000 1
#> 519 9 14 5 2.72 1.838 0.066
#> 520 11 5 -6 2.72 -2.206 0.027
#> 521 8 11 3 2.72 1.103 0.27
#> 522 3 4 1 2.72 0.368 0.713
#> 523 11 9 -2 2.72 -0.735 0.462
#> 524 16 13 -3 2.72 -1.103 0.27
#> 525 16 16 0 2.72 0.000 1
#> 526 14 13 -1 2.72 -0.368 0.713
#> 527 11 12 1 2.72 0.368 0.713
#> 528 17 16 -1 2.72 -0.368 0.713
#> 529 7 10 3 2.72 1.103 0.27
#> 530 11 11 0 2.72 0.000 1
#> 531 7 5 -2 2.72 -0.735 0.462
#> 532 12 17 5 2.72 1.838 0.066
#> 533 10 16 6 2.72 2.206 0.027
#> 534 15 14 -1 2.72 -0.368 0.713
#> 535 16 14 -2 2.72 -0.735 0.462
#> 536 8 15 7 2.72 2.573 0.01
#> 537 19 16 -3 2.72 -1.103 0.27
#> 538 14 14 0 2.72 0.000 1
#> 539 10 8 -2 2.72 -0.735 0.462
#> 540 11 9 -2 2.72 -0.735 0.462
#> 541 20 19 -1 2.72 -0.368 0.713
#> 542 17 18 1 2.72 0.368 0.713
#> 543 9 8 -1 2.72 -0.368 0.713
#> 544 18 20 2 2.72 0.735 0.462
#> 545 12 10 -2 2.72 -0.735 0.462
#> 546 10 14 4 2.72 1.471 0.141
#> 547 8 8 0 2.72 0.000 1
#> 548 10 11 1 2.72 0.368 0.713
#> 549 15 8 -7 2.72 -2.573 0.01
#> 550 5 4 -1 2.72 -0.368 0.713
#> 551 5 6 1 2.72 0.368 0.713
#> 552 6 7 1 2.72 0.368 0.713
#> 553 9 13 4 2.72 1.471 0.141
#> 554 8 5 -3 2.72 -1.103 0.27
#> 555 12 10 -2 2.72 -0.735 0.462
#> 556 15 15 0 2.72 0.000 1
#> 557 9 13 4 2.72 1.471 0.141
#> 558 11 14 3 2.72 1.103 0.27
#> 559 12 13 1 2.72 0.368 0.713
#> 560 4 5 1 2.72 0.368 0.713
#> 561 13 14 1 2.72 0.368 0.713
#> 562 11 13 2 2.72 0.735 0.462
#> 563 14 10 -4 2.72 -1.471 0.141
#> 564 1 4 3 2.72 1.103 0.27
#> 565 13 14 1 2.72 0.368 0.713
#> 566 15 14 -1 2.72 -0.368 0.713
#> 567 8 7 -1 2.72 -0.368 0.713
#> 568 15 16 1 2.72 0.368 0.713
#> 569 19 19 0 2.72 0.000 1
#> 570 13 11 -2 2.72 -0.735 0.462
#> 571 15 14 -1 2.72 -0.368 0.713
#> 572 5 6 1 2.72 0.368 0.713
#> 573 2 3 1 2.72 0.368 0.713
#> 574 19 14 -5 2.72 -1.838 0.066
#> 575 3 1 -2 2.72 -0.735 0.462
#> 576 17 18 1 2.72 0.368 0.713
#> 577 2 3 1 2.72 0.368 0.713
#> 578 19 17 -2 2.72 -0.735 0.462
#> 579 13 13 0 2.72 0.000 1
#> 580 20 15 -5 2.72 -1.838 0.066
#> 581 6 5 -1 2.72 -0.368 0.713
#> 582 17 18 1 2.72 0.368 0.713
#> 583 7 6 -1 2.72 -0.368 0.713
#> 584 6 4 -2 2.72 -0.735 0.462
#> 585 16 12 -4 2.72 -1.471 0.141
#> 586 13 13 0 2.72 0.000 1
#> 587 18 17 -1 2.72 -0.368 0.713
#> 588 9 7 -2 2.72 -0.735 0.462
#> 589 12 10 -2 2.72 -0.735 0.462
#> 590 12 14 2 2.72 0.735 0.462
#> 591 9 12 3 2.72 1.103 0.27
#> 592 12 16 4 2.72 1.471 0.141
#> 593 17 15 -2 2.72 -0.735 0.462
#> 594 4 3 -1 2.72 -0.368 0.713
#> 595 8 8 0 2.72 0.000 1
#> 596 11 9 -2 2.72 -0.735 0.462
#> 597 8 10 2 2.72 0.735 0.462
#> 598 10 12 2 2.72 0.735 0.462
#> 599 13 13 0 2.72 0.000 1
#> 600 12 16 4 2.72 1.471 0.141
#> 601 15 19 4 2.72 1.471 0.141
#> 602 11 9 -2 2.72 -0.735 0.462
#> 603 5 3 -2 2.72 -0.735 0.462
#> 604 7 9 2 2.72 0.735 0.462
#> 605 7 2 -5 2.72 -1.838 0.066
#> 606 2 6 4 2.72 1.471 0.141
#> 607 10 8 -2 2.72 -0.735 0.462
#> 608 14 14 0 2.72 0.000 1
#> 609 11 12 1 2.72 0.368 0.713
#> 610 12 7 -5 2.72 -1.838 0.066
#> 611 13 12 -1 2.72 -0.368 0.713
#> 612 10 9 -1 2.72 -0.368 0.713
#> 613 11 13 2 2.72 0.735 0.462
#> 614 5 6 1 2.72 0.368 0.713
#> 615 12 12 0 2.72 0.000 1
#> 616 4 1 -3 2.72 -1.103 0.27
#> 617 4 7 3 2.72 1.103 0.27
#> 618 5 5 0 2.72 0.000 1
#> 619 16 18 2 2.72 0.735 0.462
#> 620 4 6 2 2.72 0.735 0.462
#> 621 19 16 -3 2.72 -1.103 0.27
#> 622 13 12 -1 2.72 -0.368 0.713
#> 623 17 19 2 2.72 0.735 0.462
#> 624 8 5 -3 2.72 -1.103 0.27
#> 625 9 11 2 2.72 0.735 0.462
#> 626 5 4 -1 2.72 -0.368 0.713
#> 627 5 5 0 2.72 0.000 1
#> 628 4 1 -3 2.72 -1.103 0.27
#> 629 7 8 1 2.72 0.368 0.713
#> 630 8 13 5 2.72 1.838 0.066
#> 631 14 18 4 2.72 1.471 0.141
#> 632 8 3 -5 2.72 -1.838 0.066
#> 633 16 16 0 2.72 0.000 1
#> 634 13 14 1 2.72 0.368 0.713
#> 635 15 11 -4 2.72 -1.471 0.141
#> 636 13 9 -4 2.72 -1.471 0.141
#> 637 6 7 1 2.72 0.368 0.713
#> 638 12 7 -5 2.72 -1.838 0.066
#> 639 6 6 0 2.72 0.000 1
#> 640 3 2 -1 2.72 -0.368 0.713
#> 641 9 7 -2 2.72 -0.735 0.462
#> 642 7 7 0 2.72 0.000 1
#> 643 16 16 0 2.72 0.000 1
#> 644 13 13 0 2.72 0.000 1
#> 645 12 15 3 2.72 1.103 0.27
#> 646 2 3 1 2.72 0.368 0.713
#> 647 18 14 -4 2.72 -1.471 0.141
#> 648 5 7 2 2.72 0.735 0.462
#> 649 6 4 -2 2.72 -0.735 0.462
#> 650 19 18 -1 2.72 -0.368 0.713
#> 651 8 4 -4 2.72 -1.471 0.141
#> 652 10 12 2 2.72 0.735 0.462
#> 653 6 10 4 2.72 1.471 0.141
#> 654 4 5 1 2.72 0.368 0.713
#> 655 6 6 0 2.72 0.000 1
#> 656 7 5 -2 2.72 -0.735 0.462
#> 657 13 12 -1 2.72 -0.368 0.713
#> 658 10 13 3 2.72 1.103 0.27
#> 659 18 17 -1 2.72 -0.368 0.713
#> 660 11 8 -3 2.72 -1.103 0.27
#> 661 10 7 -3 2.72 -1.103 0.27
#> 662 19 18 -1 2.72 -0.368 0.713
#> 663 12 14 2 2.72 0.735 0.462
#> 664 17 19 2 2.72 0.735 0.462
#> 665 11 15 4 2.72 1.471 0.141
#> 666 13 13 0 2.72 0.000 1
#> 667 10 12 2 2.72 0.735 0.462
#> 668 11 12 1 2.72 0.368 0.713
#> 669 8 11 3 2.72 1.103 0.27
#> 670 8 5 -3 2.72 -1.103 0.27
#> 671 12 11 -1 2.72 -0.368 0.713
#> 672 10 10 0 2.72 0.000 1
#> 673 9 10 1 2.72 0.368 0.713
#> 674 12 15 3 2.72 1.103 0.27
#> 675 7 11 4 2.72 1.471 0.141
#> 676 4 2 -2 2.72 -0.735 0.462
#> 677 15 17 2 2.72 0.735 0.462
#> 678 9 6 -3 2.72 -1.103 0.27
#> 679 11 11 0 2.72 0.000 1
#> 680 17 16 -1 2.72 -0.368 0.713
#> 681 19 19 0 2.72 0.000 1
#> 682 9 10 1 2.72 0.368 0.713
#> 683 19 18 -1 2.72 -0.368 0.713
#> 684 5 1 -4 2.72 -1.471 0.141
#> 685 12 10 -2 2.72 -0.735 0.462
#> 686 16 13 -3 2.72 -1.103 0.27
#> 687 9 10 1 2.72 0.368 0.713
#> 688 7 6 -1 2.72 -0.368 0.713
#> 689 4 2 -2 2.72 -0.735 0.462
#> 690 14 15 1 2.72 0.368 0.713
#> 691 12 14 2 2.72 0.735 0.462
#> 692 4 8 4 2.72 1.471 0.141
#> 693 10 9 -1 2.72 -0.368 0.713
#> 694 13 9 -4 2.72 -1.471 0.141
#> 695 16 17 1 2.72 0.368 0.713
#> 696 14 13 -1 2.72 -0.368 0.713
#> 697 9 9 0 2.72 0.000 1
#> 698 3 5 2 2.72 0.735 0.462
#> 699 5 3 -2 2.72 -0.735 0.462
#> 700 10 13 3 2.72 1.103 0.27
#> 701 2 4 2 2.72 0.735 0.462
#> 702 14 11 -3 2.72 -1.103 0.27
#> 703 13 11 -2 2.72 -0.735 0.462
#> 704 12 13 1 2.72 0.368 0.713
#> 705 16 17 1 2.72 0.368 0.713
#> 706 15 17 2 2.72 0.735 0.462
#> 707 5 1 -4 2.72 -1.471 0.141
#> 708 13 13 0 2.72 0.000 1
#> 709 13 17 4 2.72 1.471 0.141
#> 710 8 6 -2 2.72 -0.735 0.462
#> 711 17 20 3 2.72 1.103 0.27
#> 712 8 6 -2 2.72 -0.735 0.462
#> 713 13 12 -1 2.72 -0.368 0.713
#> 714 3 5 2 2.72 0.735 0.462
#> 715 6 3 -3 2.72 -1.103 0.27
#> 716 15 16 1 2.72 0.368 0.713
#> 717 10 9 -1 2.72 -0.368 0.713
#> 718 9 12 3 2.72 1.103 0.27
#> 719 18 15 -3 2.72 -1.103 0.27
#> 720 5 6 1 2.72 0.368 0.713
#> 721 11 9 -2 2.72 -0.735 0.462
#> 722 7 7 0 2.72 0.000 1
#> 723 16 18 2 2.72 0.735 0.462
#> 724 6 13 7 2.72 2.573 0.01
#> 725 9 7 -2 2.72 -0.735 0.462
#> 726 4 4 0 2.72 0.000 1
#> 727 4 3 -1 2.72 -0.368 0.713
#> 728 9 10 1 2.72 0.368 0.713
#> 729 7 5 -2 2.72 -0.735 0.462
#> 730 9 10 1 2.72 0.368 0.713
#> 731 14 16 2 2.72 0.735 0.462
#> 732 2 4 2 2.72 0.735 0.462
#> 733 10 8 -2 2.72 -0.735 0.462
#> 734 17 12 -5 2.72 -1.838 0.066
#> 735 12 12 0 2.72 0.000 1
#> 736 11 10 -1 2.72 -0.368 0.713
#> 737 13 14 1 2.72 0.368 0.713
#> 738 12 13 1 2.72 0.368 0.713
#> 739 7 7 0 2.72 0.000 1
#> 740 9 8 -1 2.72 -0.368 0.713
#> 741 7 4 -3 2.72 -1.103 0.27
#> 742 8 7 -1 2.72 -0.368 0.713
#> 743 20 18 -2 2.72 -0.735 0.462
#> 744 12 10 -2 2.72 -0.735 0.462
#> 745 10 10 0 2.72 0.000 1
#> 746 18 19 1 2.72 0.368 0.713
#> 747 7 7 0 2.72 0.000 1
#> 748 16 17 1 2.72 0.368 0.713
#> 749 7 8 1 2.72 0.368 0.713
#> 750 20 18 -2 2.72 -0.735 0.462
#> 751 8 8 0 2.72 0.000 1
#> 752 8 10 2 2.72 0.735 0.462
#> 753 12 14 2 2.72 0.735 0.462
#> 754 15 17 2 2.72 0.735 0.462
#> 755 9 11 2 2.72 0.735 0.462
#> 756 10 8 -2 2.72 -0.735 0.462
#> 757 1 2 1 2.72 0.368 0.713
#> 758 4 6 2 2.72 0.735 0.462
#> 759 13 14 1 2.72 0.368 0.713
#> 760 15 17 2 2.72 0.735 0.462
#> 761 6 4 -2 2.72 -0.735 0.462
#> 762 17 11 -6 2.72 -2.206 0.027
#> 763 13 13 0 2.72 0.000 1
#> 764 13 15 2 2.72 0.735 0.462
#> 765 13 14 1 2.72 0.368 0.713
#> 766 13 13 0 2.72 0.000 1
#> 767 17 14 -3 2.72 -1.103 0.27
#> 768 2 2 0 2.72 0.000 1
#> 769 18 16 -2 2.72 -0.735 0.462
#> 770 19 20 1 2.72 0.368 0.713
#> 771 3 4 1 2.72 0.368 0.713
#> 772 17 11 -6 2.72 -2.206 0.027
#> 773 15 15 0 2.72 0.000 1
#> 774 13 14 1 2.72 0.368 0.713
#> 775 3 1 -2 2.72 -0.735 0.462
#> 776 18 16 -2 2.72 -0.735 0.462
#> 777 12 12 0 2.72 0.000 1
#> 778 12 14 2 2.72 0.735 0.462
#> 779 5 5 0 2.72 0.000 1
#> 780 9 8 -1 2.72 -0.368 0.713
#> 781 20 17 -3 2.72 -1.103 0.27
#> 782 12 8 -4 2.72 -1.471 0.141
#> 783 2 1 -1 2.72 -0.368 0.713
#> 784 7 6 -1 2.72 -0.368 0.713
#> 785 14 14 0 2.72 0.000 1
#> 786 12 10 -2 2.72 -0.735 0.462
#> 787 14 12 -2 2.72 -0.735 0.462
#> 788 13 14 1 2.72 0.368 0.713
#> 789 9 12 3 2.72 1.103 0.27
#> 790 11 7 -4 2.72 -1.471 0.141
#> 791 10 9 -1 2.72 -0.368 0.713
#> 792 14 14 0 2.72 0.000 1
#> 793 8 5 -3 2.72 -1.103 0.27
#> 794 19 18 -1 2.72 -0.368 0.713
#> 795 12 12 0 2.72 0.000 1
#> 796 13 15 2 2.72 0.735 0.462
#> 797 10 6 -4 2.72 -1.471 0.141
#> 798 7 4 -3 2.72 -1.103 0.27
#> 799 6 2 -4 2.72 -1.471 0.141
#> 800 4 8 4 2.72 1.471 0.141
#> 801 20 17 -3 2.72 -1.103 0.27
#> 802 5 6 1 2.72 0.368 0.713
#> 803 18 17 -1 2.72 -0.368 0.713
#> 804 11 13 2 2.72 0.735 0.462
#> 805 9 6 -3 2.72 -1.103 0.27
#> 806 6 4 -2 2.72 -0.735 0.462
#> 807 6 6 0 2.72 0.000 1
#> 808 9 10 1 2.72 0.368 0.713
#> 809 11 11 0 2.72 0.000 1
#> 810 4 7 3 2.72 1.103 0.27
#> 811 4 6 2 2.72 0.735 0.462
#> 812 11 12 1 2.72 0.368 0.713
#> 813 18 20 2 2.72 0.735 0.462
#> 814 6 7 1 2.72 0.368 0.713
#> 815 14 13 -1 2.72 -0.368 0.713
#> 816 11 12 1 2.72 0.368 0.713
#> 817 8 7 -1 2.72 -0.368 0.713
#> 818 16 19 3 2.72 1.103 0.27
#> 819 5 3 -2 2.72 -0.735 0.462
#> 820 17 13 -4 2.72 -1.471 0.141
#> 821 11 14 3 2.72 1.103 0.27
#> 822 10 10 0 2.72 0.000 1
#> 823 10 16 6 2.72 2.206 0.027
#> 824 11 12 1 2.72 0.368 0.713
#> 825 8 13 5 2.72 1.838 0.066
#> 826 13 15 2 2.72 0.735 0.462
#> 827 14 10 -4 2.72 -1.471 0.141
#> 828 14 13 -1 2.72 -0.368 0.713
#> 829 7 13 6 2.72 2.206 0.027
#> 830 10 11 1 2.72 0.368 0.713
#> 831 6 6 0 2.72 0.000 1
#> 832 5 6 1 2.72 0.368 0.713
#> 833 15 16 1 2.72 0.368 0.713
#> 834 5 9 4 2.72 1.471 0.141
#> 835 10 3 -7 2.72 -2.573 0.01
#> 836 14 15 1 2.72 0.368 0.713
#> 837 2 6 4 2.72 1.471 0.141
#> 838 1 0 -1 2.72 -0.368 0.713
#> 839 19 19 0 2.72 0.000 1
#> 840 7 7 0 2.72 0.000 1
#> 841 16 14 -2 2.72 -0.735 0.462
#> 842 18 17 -1 2.72 -0.368 0.713
#> 843 18 17 -1 2.72 -0.368 0.713
#> 844 11 10 -1 2.72 -0.368 0.713
#> 845 16 15 -1 2.72 -0.368 0.713
#> 846 10 11 1 2.72 0.368 0.713
#> 847 15 16 1 2.72 0.368 0.713
#> 848 15 11 -4 2.72 -1.471 0.141
#> 849 18 15 -3 2.72 -1.103 0.27
#> 850 13 15 2 2.72 0.735 0.462
#> 851 16 17 1 2.72 0.368 0.713
#> 852 13 16 3 2.72 1.103 0.27
#> 853 6 9 3 2.72 1.103 0.27
#> 854 14 16 2 2.72 0.735 0.462
#> 855 12 11 -1 2.72 -0.368 0.713
#> 856 5 6 1 2.72 0.368 0.713
#> 857 6 7 1 2.72 0.368 0.713
#> 858 7 13 6 2.72 2.206 0.027
#> 859 18 18 0 2.72 0.000 1
#> 860 11 13 2 2.72 0.735 0.462
#> 861 11 10 -1 2.72 -0.368 0.713
#> 862 9 6 -3 2.72 -1.103 0.27
#> 863 8 7 -1 2.72 -0.368 0.713
#> 864 9 7 -2 2.72 -0.735 0.462
#> 865 15 13 -2 2.72 -0.735 0.462
#> 866 12 9 -3 2.72 -1.103 0.27
#> 867 10 12 2 2.72 0.735 0.462
#> 868 17 12 -5 2.72 -1.838 0.066
#> 869 6 8 2 2.72 0.735 0.462
#> 870 4 4 0 2.72 0.000 1
#> 871 16 15 -1 2.72 -0.368 0.713
#> 872 7 3 -4 2.72 -1.471 0.141
#> 873 4 7 3 2.72 1.103 0.27
#> 874 12 12 0 2.72 0.000 1
#> 875 14 12 -2 2.72 -0.735 0.462
#> 876 17 13 -4 2.72 -1.471 0.141
#> 877 12 11 -1 2.72 -0.368 0.713
#> 878 6 6 0 2.72 0.000 1
#> 879 8 13 5 2.72 1.838 0.066
#> 880 15 17 2 2.72 0.735 0.462
#> 881 7 10 3 2.72 1.103 0.27
#> 882 2 1 -1 2.72 -0.368 0.713
#> 883 13 18 5 2.72 1.838 0.066
#> 884 17 18 1 2.72 0.368 0.713
#> 885 8 10 2 2.72 0.735 0.462
#> 886 18 19 1 2.72 0.368 0.713
#> 887 17 16 -1 2.72 -0.368 0.713
#> 888 14 11 -3 2.72 -1.103 0.27
#> 889 6 6 0 2.72 0.000 1
#> 890 4 3 -1 2.72 -0.368 0.713
#> 891 12 10 -2 2.72 -0.735 0.462
#> 892 11 12 1 2.72 0.368 0.713
#> 893 5 7 2 2.72 0.735 0.462
#> 894 15 17 2 2.72 0.735 0.462
#> 895 6 11 5 2.72 1.838 0.066
#> 896 11 7 -4 2.72 -1.471 0.141
#> 897 11 13 2 2.72 0.735 0.462
#> 898 6 5 -1 2.72 -0.368 0.713
#> 899 13 11 -2 2.72 -0.735 0.462
#> 900 5 9 4 2.72 1.471 0.141
#> 901 10 10 0 2.72 0.000 1
#> 902 17 18 1 2.72 0.368 0.713
#> 903 15 14 -1 2.72 -0.368 0.713
#> 904 8 11 3 2.72 1.103 0.27
#> 905 17 16 -1 2.72 -0.368 0.713
#> 906 14 17 3 2.72 1.103 0.27
#> 907 9 10 1 2.72 0.368 0.713
#> 908 13 8 -5 2.72 -1.838 0.066
#> 909 7 5 -2 2.72 -0.735 0.462
#> 910 8 6 -2 2.72 -0.735 0.462
#> 911 18 19 1 2.72 0.368 0.713
#> 912 15 17 2 2.72 0.735 0.462
#> 913 11 12 1 2.72 0.368 0.713
#> 914 10 10 0 2.72 0.000 1
#> 915 18 19 1 2.72 0.368 0.713
#> 916 18 16 -2 2.72 -0.735 0.462
#> 917 10 10 0 2.72 0.000 1
#> 918 2 1 -1 2.72 -0.368 0.713
#> 919 16 17 1 2.72 0.368 0.713
#> 920 2 1 -1 2.72 -0.368 0.713
#> 921 20 20 0 2.72 0.000 1
#> 922 6 2 -4 2.72 -1.471 0.141
#> 923 18 17 -1 2.72 -0.368 0.713
#> 924 13 19 6 2.72 2.206 0.027
#> 925 14 11 -3 2.72 -1.103 0.27
#> 926 18 17 -1 2.72 -0.368 0.713
#> 927 16 15 -1 2.72 -0.368 0.713
#> 928 18 11 -7 2.72 -2.573 0.01
#> 929 15 12 -3 2.72 -1.103 0.27
#> 930 9 5 -4 2.72 -1.471 0.141
#> 931 9 9 0 2.72 0.000 1
#> 932 10 10 0 2.72 0.000 1
#> 933 16 18 2 2.72 0.735 0.462
#> 934 5 7 2 2.72 0.735 0.462
#> 935 16 17 1 2.72 0.368 0.713
#> 936 8 10 2 2.72 0.735 0.462
#> 937 5 4 -1 2.72 -0.368 0.713
#> 938 16 15 -1 2.72 -0.368 0.713
#> 939 13 10 -3 2.72 -1.103 0.27
#> 940 10 13 3 2.72 1.103 0.27
#> 941 14 14 0 2.72 0.000 1
#> 942 10 14 4 2.72 1.471 0.141
#> 943 4 3 -1 2.72 -0.368 0.713
#> 944 20 18 -2 2.72 -0.735 0.462
#> 945 6 8 2 2.72 0.735 0.462
#> 946 8 5 -3 2.72 -1.103 0.27
#> 947 7 17 10 2.72 3.676 0
#> 948 7 3 -4 2.72 -1.471 0.141
#> 949 14 14 0 2.72 0.000 1
#> 950 14 13 -1 2.72 -0.368 0.713
#> 951 14 13 -1 2.72 -0.368 0.713
#> 952 14 10 -4 2.72 -1.471 0.141
#> 953 12 9 -3 2.72 -1.103 0.27
#> 954 8 8 0 2.72 0.000 1
#> 955 14 11 -3 2.72 -1.103 0.27
#> 956 10 12 2 2.72 0.735 0.462
#> 957 11 9 -2 2.72 -0.735 0.462
#> 958 4 4 0 2.72 0.000 1
#> 959 9 10 1 2.72 0.368 0.713
#> 960 5 7 2 2.72 0.735 0.462
#> 961 16 13 -3 2.72 -1.103 0.27
#> 962 7 5 -2 2.72 -0.735 0.462
#> 963 6 7 1 2.72 0.368 0.713
#> 964 5 6 1 2.72 0.368 0.713
#> 965 5 2 -3 2.72 -1.103 0.27
#> 966 2 5 3 2.72 1.103 0.27
#> 967 7 6 -1 2.72 -0.368 0.713
#> 968 16 19 3 2.72 1.103 0.27
#> 969 8 4 -4 2.72 -1.471 0.141
#> 970 4 1 -3 2.72 -1.103 0.27
#> 971 12 10 -2 2.72 -0.735 0.462
#> 972 3 9 6 2.72 2.206 0.027
#> 973 14 16 2 2.72 0.735 0.462
#> 974 7 5 -2 2.72 -0.735 0.462
#> 975 16 16 0 2.72 0.000 1
#> 976 15 16 1 2.72 0.368 0.713
#> 977 11 14 3 2.72 1.103 0.27
#> 978 14 13 -1 2.72 -0.368 0.713
#> 979 17 18 1 2.72 0.368 0.713
#> 980 10 10 0 2.72 0.000 1
#> 981 17 18 1 2.72 0.368 0.713
#> 982 3 2 -1 2.72 -0.368 0.713
#> 983 6 7 1 2.72 0.368 0.713
#> 984 4 3 -1 2.72 -0.368 0.713
#> 985 14 16 2 2.72 0.735 0.462
#> 986 11 11 0 2.72 0.000 1
#> 987 5 3 -2 2.72 -0.735 0.462
#> 988 1 2 1 2.72 0.368 0.713
#> 989 10 11 1 2.72 0.368 0.713
#> 990 4 2 -2 2.72 -0.735 0.462
#> 991 5 4 -1 2.72 -0.368 0.713
#> 992 12 14 2 2.72 0.735 0.462
#> 993 20 14 -6 2.72 -2.206 0.027
#> 994 15 12 -3 2.72 -1.103 0.27
#> 995 8 14 6 2.72 2.206 0.027
#> 996 18 17 -1 2.72 -0.368 0.713
#> 997 9 13 4 2.72 1.471 0.141
#> 998 12 9 -3 2.72 -1.103 0.27
#> 999 9 6 -3 2.72 -1.103 0.27
#> 1000 10 8 -2 2.72 -0.735 0.462
# include cutoffs
RCI(predat = dat_pre, postdat = dat_post, SEM.pre=SEM.alpha,
cutoffs=c(-1.96, 1.96))
#> pre.score post.score diff SE z p cut_decision
#> 1 15 9 -6 2.72 -2.206 0.027 decreased
#> 2 4 0 -4 2.72 -1.471 0.141 unchanged
#> 3 4 3 -1 2.72 -0.368 0.713 unchanged
#> 4 6 4 -2 2.72 -0.735 0.462 unchanged
#> 5 4 5 1 2.72 0.368 0.713 unchanged
#> 6 6 7 1 2.72 0.368 0.713 unchanged
#> 7 3 8 5 2.72 1.838 0.066 unchanged
#> 8 13 12 -1 2.72 -0.368 0.713 unchanged
#> 9 17 16 -1 2.72 -0.368 0.713 unchanged
#> 10 16 17 1 2.72 0.368 0.713 unchanged
#> 11 13 14 1 2.72 0.368 0.713 unchanged
#> 12 16 12 -4 2.72 -1.471 0.141 unchanged
#> 13 12 11 -1 2.72 -0.368 0.713 unchanged
#> 14 9 3 -6 2.72 -2.206 0.027 decreased
#> 15 6 6 0 2.72 0.000 1 unchanged
#> 16 13 13 0 2.72 0.000 1 unchanged
#> 17 13 11 -2 2.72 -0.735 0.462 unchanged
#> 18 0 4 4 2.72 1.471 0.141 unchanged
#> 19 6 8 2 2.72 0.735 0.462 unchanged
#> 20 4 5 1 2.72 0.368 0.713 unchanged
#> 21 16 13 -3 2.72 -1.103 0.27 unchanged
#> 22 12 12 0 2.72 0.000 1 unchanged
#> 23 13 10 -3 2.72 -1.103 0.27 unchanged
#> 24 18 17 -1 2.72 -0.368 0.713 unchanged
#> 25 3 3 0 2.72 0.000 1 unchanged
#> 26 12 13 1 2.72 0.368 0.713 unchanged
#> 27 17 15 -2 2.72 -0.735 0.462 unchanged
#> 28 14 15 1 2.72 0.368 0.713 unchanged
#> 29 13 17 4 2.72 1.471 0.141 unchanged
#> 30 10 7 -3 2.72 -1.103 0.27 unchanged
#> 31 15 13 -2 2.72 -0.735 0.462 unchanged
#> 32 3 3 0 2.72 0.000 1 unchanged
#> 33 8 12 4 2.72 1.471 0.141 unchanged
#> 34 17 18 1 2.72 0.368 0.713 unchanged
#> 35 6 10 4 2.72 1.471 0.141 unchanged
#> 36 18 18 0 2.72 0.000 1 unchanged
#> 37 10 7 -3 2.72 -1.103 0.27 unchanged
#> 38 17 13 -4 2.72 -1.471 0.141 unchanged
#> 39 10 3 -7 2.72 -2.573 0.01 decreased
#> 40 0 2 2 2.72 0.735 0.462 unchanged
#> 41 12 10 -2 2.72 -0.735 0.462 unchanged
#> 42 19 20 1 2.72 0.368 0.713 unchanged
#> 43 11 10 -1 2.72 -0.368 0.713 unchanged
#> 44 5 3 -2 2.72 -0.735 0.462 unchanged
#> 45 16 15 -1 2.72 -0.368 0.713 unchanged
#> 46 8 12 4 2.72 1.471 0.141 unchanged
#> 47 17 17 0 2.72 0.000 1 unchanged
#> 48 12 10 -2 2.72 -0.735 0.462 unchanged
#> 49 20 16 -4 2.72 -1.471 0.141 unchanged
#> 50 8 7 -1 2.72 -0.368 0.713 unchanged
#> 51 9 11 2 2.72 0.735 0.462 unchanged
#> 52 7 5 -2 2.72 -0.735 0.462 unchanged
#> 53 13 10 -3 2.72 -1.103 0.27 unchanged
#> 54 6 10 4 2.72 1.471 0.141 unchanged
#> 55 7 6 -1 2.72 -0.368 0.713 unchanged
#> 56 7 9 2 2.72 0.735 0.462 unchanged
#> 57 5 7 2 2.72 0.735 0.462 unchanged
#> 58 11 3 -8 2.72 -2.941 0.003 decreased
#> 59 13 10 -3 2.72 -1.103 0.27 unchanged
#> 60 18 18 0 2.72 0.000 1 unchanged
#> 61 7 7 0 2.72 0.000 1 unchanged
#> 62 15 16 1 2.72 0.368 0.713 unchanged
#> 63 11 11 0 2.72 0.000 1 unchanged
#> 64 7 8 1 2.72 0.368 0.713 unchanged
#> 65 2 7 5 2.72 1.838 0.066 unchanged
#> 66 7 4 -3 2.72 -1.103 0.27 unchanged
#> 67 5 4 -1 2.72 -0.368 0.713 unchanged
#> 68 9 12 3 2.72 1.103 0.27 unchanged
#> 69 11 17 6 2.72 2.206 0.027 increased
#> 70 12 11 -1 2.72 -0.368 0.713 unchanged
#> 71 19 18 -1 2.72 -0.368 0.713 unchanged
#> 72 15 16 1 2.72 0.368 0.713 unchanged
#> 73 9 5 -4 2.72 -1.471 0.141 unchanged
#> 74 8 10 2 2.72 0.735 0.462 unchanged
#> 75 7 5 -2 2.72 -0.735 0.462 unchanged
#> 76 16 17 1 2.72 0.368 0.713 unchanged
#> 77 9 7 -2 2.72 -0.735 0.462 unchanged
#> 78 12 9 -3 2.72 -1.103 0.27 unchanged
#> 79 20 18 -2 2.72 -0.735 0.462 unchanged
#> 80 6 8 2 2.72 0.735 0.462 unchanged
#> 81 16 16 0 2.72 0.000 1 unchanged
#> 82 8 12 4 2.72 1.471 0.141 unchanged
#> 83 7 8 1 2.72 0.368 0.713 unchanged
#> 84 16 15 -1 2.72 -0.368 0.713 unchanged
#> 85 17 13 -4 2.72 -1.471 0.141 unchanged
#> 86 5 6 1 2.72 0.368 0.713 unchanged
#> 87 11 11 0 2.72 0.000 1 unchanged
#> 88 17 15 -2 2.72 -0.735 0.462 unchanged
#> 89 17 11 -6 2.72 -2.206 0.027 decreased
#> 90 12 8 -4 2.72 -1.471 0.141 unchanged
#> 91 13 15 2 2.72 0.735 0.462 unchanged
#> 92 13 14 1 2.72 0.368 0.713 unchanged
#> 93 5 3 -2 2.72 -0.735 0.462 unchanged
#> 94 13 13 0 2.72 0.000 1 unchanged
#> 95 7 10 3 2.72 1.103 0.27 unchanged
#> 96 8 10 2 2.72 0.735 0.462 unchanged
#> 97 14 9 -5 2.72 -1.838 0.066 unchanged
#> 98 8 6 -2 2.72 -0.735 0.462 unchanged
#> 99 11 11 0 2.72 0.000 1 unchanged
#> 100 5 5 0 2.72 0.000 1 unchanged
#> 101 5 11 6 2.72 2.206 0.027 increased
#> 102 5 0 -5 2.72 -1.838 0.066 unchanged
#> 103 11 11 0 2.72 0.000 1 unchanged
#> 104 16 19 3 2.72 1.103 0.27 unchanged
#> 105 7 6 -1 2.72 -0.368 0.713 unchanged
#> 106 4 6 2 2.72 0.735 0.462 unchanged
#> 107 5 7 2 2.72 0.735 0.462 unchanged
#> 108 9 11 2 2.72 0.735 0.462 unchanged
#> 109 14 10 -4 2.72 -1.471 0.141 unchanged
#> 110 6 5 -1 2.72 -0.368 0.713 unchanged
#> 111 14 19 5 2.72 1.838 0.066 unchanged
#> 112 11 10 -1 2.72 -0.368 0.713 unchanged
#> 113 12 11 -1 2.72 -0.368 0.713 unchanged
#> 114 4 2 -2 2.72 -0.735 0.462 unchanged
#> 115 7 7 0 2.72 0.000 1 unchanged
#> 116 17 15 -2 2.72 -0.735 0.462 unchanged
#> 117 4 1 -3 2.72 -1.103 0.27 unchanged
#> 118 12 14 2 2.72 0.735 0.462 unchanged
#> 119 4 7 3 2.72 1.103 0.27 unchanged
#> 120 14 13 -1 2.72 -0.368 0.713 unchanged
#> 121 9 9 0 2.72 0.000 1 unchanged
#> 122 15 18 3 2.72 1.103 0.27 unchanged
#> 123 4 6 2 2.72 0.735 0.462 unchanged
#> 124 13 16 3 2.72 1.103 0.27 unchanged
#> 125 15 13 -2 2.72 -0.735 0.462 unchanged
#> 126 10 5 -5 2.72 -1.838 0.066 unchanged
#> 127 3 2 -1 2.72 -0.368 0.713 unchanged
#> 128 15 13 -2 2.72 -0.735 0.462 unchanged
#> 129 9 2 -7 2.72 -2.573 0.01 decreased
#> 130 12 13 1 2.72 0.368 0.713 unchanged
#> 131 5 3 -2 2.72 -0.735 0.462 unchanged
#> 132 5 6 1 2.72 0.368 0.713 unchanged
#> 133 2 3 1 2.72 0.368 0.713 unchanged
#> 134 15 13 -2 2.72 -0.735 0.462 unchanged
#> 135 20 17 -3 2.72 -1.103 0.27 unchanged
#> 136 14 13 -1 2.72 -0.368 0.713 unchanged
#> 137 11 14 3 2.72 1.103 0.27 unchanged
#> 138 17 14 -3 2.72 -1.103 0.27 unchanged
#> 139 13 15 2 2.72 0.735 0.462 unchanged
#> 140 12 11 -1 2.72 -0.368 0.713 unchanged
#> 141 4 1 -3 2.72 -1.103 0.27 unchanged
#> 142 16 20 4 2.72 1.471 0.141 unchanged
#> 143 15 14 -1 2.72 -0.368 0.713 unchanged
#> 144 5 6 1 2.72 0.368 0.713 unchanged
#> 145 10 15 5 2.72 1.838 0.066 unchanged
#> 146 16 16 0 2.72 0.000 1 unchanged
#> 147 12 8 -4 2.72 -1.471 0.141 unchanged
#> 148 8 13 5 2.72 1.838 0.066 unchanged
#> 149 9 8 -1 2.72 -0.368 0.713 unchanged
#> 150 17 15 -2 2.72 -0.735 0.462 unchanged
#> 151 16 15 -1 2.72 -0.368 0.713 unchanged
#> 152 14 11 -3 2.72 -1.103 0.27 unchanged
#> 153 13 13 0 2.72 0.000 1 unchanged
#> 154 6 6 0 2.72 0.000 1 unchanged
#> 155 0 1 1 2.72 0.368 0.713 unchanged
#> 156 7 2 -5 2.72 -1.838 0.066 unchanged
#> 157 10 7 -3 2.72 -1.103 0.27 unchanged
#> 158 11 18 7 2.72 2.573 0.01 increased
#> 159 8 6 -2 2.72 -0.735 0.462 unchanged
#> 160 8 8 0 2.72 0.000 1 unchanged
#> 161 4 2 -2 2.72 -0.735 0.462 unchanged
#> 162 4 4 0 2.72 0.000 1 unchanged
#> 163 6 7 1 2.72 0.368 0.713 unchanged
#> 164 15 15 0 2.72 0.000 1 unchanged
#> 165 14 15 1 2.72 0.368 0.713 unchanged
#> 166 18 16 -2 2.72 -0.735 0.462 unchanged
#> 167 9 5 -4 2.72 -1.471 0.141 unchanged
#> 168 12 10 -2 2.72 -0.735 0.462 unchanged
#> 169 18 18 0 2.72 0.000 1 unchanged
#> 170 9 5 -4 2.72 -1.471 0.141 unchanged
#> 171 9 9 0 2.72 0.000 1 unchanged
#> 172 2 1 -1 2.72 -0.368 0.713 unchanged
#> 173 13 7 -6 2.72 -2.206 0.027 decreased
#> 174 9 9 0 2.72 0.000 1 unchanged
#> 175 7 10 3 2.72 1.103 0.27 unchanged
#> 176 18 12 -6 2.72 -2.206 0.027 decreased
#> 177 17 18 1 2.72 0.368 0.713 unchanged
#> 178 5 2 -3 2.72 -1.103 0.27 unchanged
#> 179 3 3 0 2.72 0.000 1 unchanged
#> 180 0 2 2 2.72 0.735 0.462 unchanged
#> 181 19 20 1 2.72 0.368 0.713 unchanged
#> 182 16 12 -4 2.72 -1.471 0.141 unchanged
#> 183 10 5 -5 2.72 -1.838 0.066 unchanged
#> 184 10 15 5 2.72 1.838 0.066 unchanged
#> 185 7 10 3 2.72 1.103 0.27 unchanged
#> 186 16 17 1 2.72 0.368 0.713 unchanged
#> 187 3 8 5 2.72 1.838 0.066 unchanged
#> 188 16 19 3 2.72 1.103 0.27 unchanged
#> 189 13 9 -4 2.72 -1.471 0.141 unchanged
#> 190 7 8 1 2.72 0.368 0.713 unchanged
#> 191 3 2 -1 2.72 -0.368 0.713 unchanged
#> 192 10 8 -2 2.72 -0.735 0.462 unchanged
#> 193 3 12 9 2.72 3.309 0.001 increased
#> 194 11 11 0 2.72 0.000 1 unchanged
#> 195 3 7 4 2.72 1.471 0.141 unchanged
#> 196 6 7 1 2.72 0.368 0.713 unchanged
#> 197 13 11 -2 2.72 -0.735 0.462 unchanged
#> 198 17 17 0 2.72 0.000 1 unchanged
#> 199 9 7 -2 2.72 -0.735 0.462 unchanged
#> 200 16 18 2 2.72 0.735 0.462 unchanged
#> 201 10 4 -6 2.72 -2.206 0.027 decreased
#> 202 9 9 0 2.72 0.000 1 unchanged
#> 203 4 3 -1 2.72 -0.368 0.713 unchanged
#> 204 6 2 -4 2.72 -1.471 0.141 unchanged
#> 205 12 12 0 2.72 0.000 1 unchanged
#> 206 5 4 -1 2.72 -0.368 0.713 unchanged
#> 207 2 3 1 2.72 0.368 0.713 unchanged
#> 208 15 19 4 2.72 1.471 0.141 unchanged
#> 209 6 2 -4 2.72 -1.471 0.141 unchanged
#> 210 16 18 2 2.72 0.735 0.462 unchanged
#> 211 12 13 1 2.72 0.368 0.713 unchanged
#> 212 2 3 1 2.72 0.368 0.713 unchanged
#> 213 11 10 -1 2.72 -0.368 0.713 unchanged
#> 214 12 13 1 2.72 0.368 0.713 unchanged
#> 215 14 15 1 2.72 0.368 0.713 unchanged
#> 216 19 19 0 2.72 0.000 1 unchanged
#> 217 16 15 -1 2.72 -0.368 0.713 unchanged
#> 218 19 20 1 2.72 0.368 0.713 unchanged
#> 219 1 0 -1 2.72 -0.368 0.713 unchanged
#> 220 13 12 -1 2.72 -0.368 0.713 unchanged
#> 221 14 11 -3 2.72 -1.103 0.27 unchanged
#> 222 19 16 -3 2.72 -1.103 0.27 unchanged
#> 223 3 5 2 2.72 0.735 0.462 unchanged
#> 224 2 1 -1 2.72 -0.368 0.713 unchanged
#> 225 16 13 -3 2.72 -1.103 0.27 unchanged
#> 226 12 11 -1 2.72 -0.368 0.713 unchanged
#> 227 6 6 0 2.72 0.000 1 unchanged
#> 228 5 8 3 2.72 1.103 0.27 unchanged
#> 229 1 0 -1 2.72 -0.368 0.713 unchanged
#> 230 12 13 1 2.72 0.368 0.713 unchanged
#> 231 3 4 1 2.72 0.368 0.713 unchanged
#> 232 10 7 -3 2.72 -1.103 0.27 unchanged
#> 233 12 10 -2 2.72 -0.735 0.462 unchanged
#> 234 14 16 2 2.72 0.735 0.462 unchanged
#> 235 18 16 -2 2.72 -0.735 0.462 unchanged
#> 236 10 10 0 2.72 0.000 1 unchanged
#> 237 11 6 -5 2.72 -1.838 0.066 unchanged
#> 238 14 19 5 2.72 1.838 0.066 unchanged
#> 239 3 2 -1 2.72 -0.368 0.713 unchanged
#> 240 8 4 -4 2.72 -1.471 0.141 unchanged
#> 241 13 15 2 2.72 0.735 0.462 unchanged
#> 242 12 13 1 2.72 0.368 0.713 unchanged
#> 243 17 16 -1 2.72 -0.368 0.713 unchanged
#> 244 9 7 -2 2.72 -0.735 0.462 unchanged
#> 245 7 6 -1 2.72 -0.368 0.713 unchanged
#> 246 10 8 -2 2.72 -0.735 0.462 unchanged
#> 247 14 12 -2 2.72 -0.735 0.462 unchanged
#> 248 11 11 0 2.72 0.000 1 unchanged
#> 249 11 10 -1 2.72 -0.368 0.713 unchanged
#> 250 18 19 1 2.72 0.368 0.713 unchanged
#> 251 4 5 1 2.72 0.368 0.713 unchanged
#> 252 1 3 2 2.72 0.735 0.462 unchanged
#> 253 4 1 -3 2.72 -1.103 0.27 unchanged
#> 254 8 10 2 2.72 0.735 0.462 unchanged
#> 255 10 10 0 2.72 0.000 1 unchanged
#> 256 17 18 1 2.72 0.368 0.713 unchanged
#> 257 18 20 2 2.72 0.735 0.462 unchanged
#> 258 11 10 -1 2.72 -0.368 0.713 unchanged
#> 259 17 17 0 2.72 0.000 1 unchanged
#> 260 12 13 1 2.72 0.368 0.713 unchanged
#> 261 11 12 1 2.72 0.368 0.713 unchanged
#> 262 9 11 2 2.72 0.735 0.462 unchanged
#> 263 13 11 -2 2.72 -0.735 0.462 unchanged
#> 264 17 16 -1 2.72 -0.368 0.713 unchanged
#> 265 11 11 0 2.72 0.000 1 unchanged
#> 266 19 18 -1 2.72 -0.368 0.713 unchanged
#> 267 10 10 0 2.72 0.000 1 unchanged
#> 268 5 9 4 2.72 1.471 0.141 unchanged
#> 269 11 12 1 2.72 0.368 0.713 unchanged
#> 270 17 14 -3 2.72 -1.103 0.27 unchanged
#> 271 17 13 -4 2.72 -1.471 0.141 unchanged
#> 272 20 19 -1 2.72 -0.368 0.713 unchanged
#> 273 8 7 -1 2.72 -0.368 0.713 unchanged
#> 274 16 19 3 2.72 1.103 0.27 unchanged
#> 275 14 13 -1 2.72 -0.368 0.713 unchanged
#> 276 4 8 4 2.72 1.471 0.141 unchanged
#> 277 16 13 -3 2.72 -1.103 0.27 unchanged
#> 278 11 11 0 2.72 0.000 1 unchanged
#> 279 8 8 0 2.72 0.000 1 unchanged
#> 280 2 4 2 2.72 0.735 0.462 unchanged
#> 281 7 3 -4 2.72 -1.471 0.141 unchanged
#> 282 5 10 5 2.72 1.838 0.066 unchanged
#> 283 18 19 1 2.72 0.368 0.713 unchanged
#> 284 10 14 4 2.72 1.471 0.141 unchanged
#> 285 1 1 0 2.72 0.000 1 unchanged
#> 286 5 10 5 2.72 1.838 0.066 unchanged
#> 287 3 2 -1 2.72 -0.368 0.713 unchanged
#> 288 7 13 6 2.72 2.206 0.027 increased
#> 289 14 18 4 2.72 1.471 0.141 unchanged
#> 290 17 17 0 2.72 0.000 1 unchanged
#> 291 14 12 -2 2.72 -0.735 0.462 unchanged
#> 292 16 11 -5 2.72 -1.838 0.066 unchanged
#> 293 4 3 -1 2.72 -0.368 0.713 unchanged
#> 294 19 17 -2 2.72 -0.735 0.462 unchanged
#> 295 8 12 4 2.72 1.471 0.141 unchanged
#> 296 17 15 -2 2.72 -0.735 0.462 unchanged
#> 297 16 18 2 2.72 0.735 0.462 unchanged
#> 298 18 17 -1 2.72 -0.368 0.713 unchanged
#> 299 10 10 0 2.72 0.000 1 unchanged
#> 300 16 15 -1 2.72 -0.368 0.713 unchanged
#> 301 8 11 3 2.72 1.103 0.27 unchanged
#> 302 3 2 -1 2.72 -0.368 0.713 unchanged
#> 303 13 11 -2 2.72 -0.735 0.462 unchanged
#> 304 8 5 -3 2.72 -1.103 0.27 unchanged
#> 305 11 11 0 2.72 0.000 1 unchanged
#> 306 17 17 0 2.72 0.000 1 unchanged
#> 307 12 8 -4 2.72 -1.471 0.141 unchanged
#> 308 18 18 0 2.72 0.000 1 unchanged
#> 309 3 2 -1 2.72 -0.368 0.713 unchanged
#> 310 9 11 2 2.72 0.735 0.462 unchanged
#> 311 8 9 1 2.72 0.368 0.713 unchanged
#> 312 8 2 -6 2.72 -2.206 0.027 decreased
#> 313 20 20 0 2.72 0.000 1 unchanged
#> 314 9 9 0 2.72 0.000 1 unchanged
#> 315 16 15 -1 2.72 -0.368 0.713 unchanged
#> 316 15 11 -4 2.72 -1.471 0.141 unchanged
#> 317 11 8 -3 2.72 -1.103 0.27 unchanged
#> 318 4 9 5 2.72 1.838 0.066 unchanged
#> 319 5 5 0 2.72 0.000 1 unchanged
#> 320 18 19 1 2.72 0.368 0.713 unchanged
#> 321 14 11 -3 2.72 -1.103 0.27 unchanged
#> 322 6 6 0 2.72 0.000 1 unchanged
#> 323 14 10 -4 2.72 -1.471 0.141 unchanged
#> 324 9 8 -1 2.72 -0.368 0.713 unchanged
#> 325 11 10 -1 2.72 -0.368 0.713 unchanged
#> 326 12 8 -4 2.72 -1.471 0.141 unchanged
#> 327 8 6 -2 2.72 -0.735 0.462 unchanged
#> 328 10 8 -2 2.72 -0.735 0.462 unchanged
#> 329 14 13 -1 2.72 -0.368 0.713 unchanged
#> 330 14 11 -3 2.72 -1.103 0.27 unchanged
#> 331 13 13 0 2.72 0.000 1 unchanged
#> 332 2 1 -1 2.72 -0.368 0.713 unchanged
#> 333 12 10 -2 2.72 -0.735 0.462 unchanged
#> 334 16 16 0 2.72 0.000 1 unchanged
#> 335 9 15 6 2.72 2.206 0.027 increased
#> 336 3 7 4 2.72 1.471 0.141 unchanged
#> 337 8 8 0 2.72 0.000 1 unchanged
#> 338 13 14 1 2.72 0.368 0.713 unchanged
#> 339 11 9 -2 2.72 -0.735 0.462 unchanged
#> 340 14 13 -1 2.72 -0.368 0.713 unchanged
#> 341 8 10 2 2.72 0.735 0.462 unchanged
#> 342 13 15 2 2.72 0.735 0.462 unchanged
#> 343 15 7 -8 2.72 -2.941 0.003 decreased
#> 344 14 12 -2 2.72 -0.735 0.462 unchanged
#> 345 9 11 2 2.72 0.735 0.462 unchanged
#> 346 14 14 0 2.72 0.000 1 unchanged
#> 347 15 16 1 2.72 0.368 0.713 unchanged
#> 348 9 12 3 2.72 1.103 0.27 unchanged
#> 349 16 18 2 2.72 0.735 0.462 unchanged
#> 350 14 10 -4 2.72 -1.471 0.141 unchanged
#> 351 7 7 0 2.72 0.000 1 unchanged
#> 352 12 14 2 2.72 0.735 0.462 unchanged
#> 353 7 9 2 2.72 0.735 0.462 unchanged
#> 354 11 7 -4 2.72 -1.471 0.141 unchanged
#> 355 11 13 2 2.72 0.735 0.462 unchanged
#> 356 14 12 -2 2.72 -0.735 0.462 unchanged
#> 357 6 12 6 2.72 2.206 0.027 increased
#> 358 7 5 -2 2.72 -0.735 0.462 unchanged
#> 359 11 10 -1 2.72 -0.368 0.713 unchanged
#> 360 9 8 -1 2.72 -0.368 0.713 unchanged
#> 361 15 18 3 2.72 1.103 0.27 unchanged
#> 362 5 6 1 2.72 0.368 0.713 unchanged
#> 363 8 10 2 2.72 0.735 0.462 unchanged
#> 364 16 17 1 2.72 0.368 0.713 unchanged
#> 365 14 17 3 2.72 1.103 0.27 unchanged
#> 366 11 13 2 2.72 0.735 0.462 unchanged
#> 367 9 11 2 2.72 0.735 0.462 unchanged
#> 368 1 4 3 2.72 1.103 0.27 unchanged
#> 369 11 9 -2 2.72 -0.735 0.462 unchanged
#> 370 9 4 -5 2.72 -1.838 0.066 unchanged
#> 371 16 19 3 2.72 1.103 0.27 unchanged
#> 372 6 8 2 2.72 0.735 0.462 unchanged
#> 373 16 16 0 2.72 0.000 1 unchanged
#> 374 7 9 2 2.72 0.735 0.462 unchanged
#> 375 18 18 0 2.72 0.000 1 unchanged
#> 376 6 4 -2 2.72 -0.735 0.462 unchanged
#> 377 13 14 1 2.72 0.368 0.713 unchanged
#> 378 12 10 -2 2.72 -0.735 0.462 unchanged
#> 379 13 15 2 2.72 0.735 0.462 unchanged
#> 380 18 16 -2 2.72 -0.735 0.462 unchanged
#> 381 9 11 2 2.72 0.735 0.462 unchanged
#> 382 10 10 0 2.72 0.000 1 unchanged
#> 383 6 6 0 2.72 0.000 1 unchanged
#> 384 8 9 1 2.72 0.368 0.713 unchanged
#> 385 15 17 2 2.72 0.735 0.462 unchanged
#> 386 15 16 1 2.72 0.368 0.713 unchanged
#> 387 6 13 7 2.72 2.573 0.01 increased
#> 388 4 2 -2 2.72 -0.735 0.462 unchanged
#> 389 9 11 2 2.72 0.735 0.462 unchanged
#> 390 9 9 0 2.72 0.000 1 unchanged
#> 391 4 10 6 2.72 2.206 0.027 increased
#> 392 9 8 -1 2.72 -0.368 0.713 unchanged
#> 393 6 4 -2 2.72 -0.735 0.462 unchanged
#> 394 5 5 0 2.72 0.000 1 unchanged
#> 395 1 3 2 2.72 0.735 0.462 unchanged
#> 396 13 13 0 2.72 0.000 1 unchanged
#> 397 15 17 2 2.72 0.735 0.462 unchanged
#> 398 6 7 1 2.72 0.368 0.713 unchanged
#> 399 1 1 0 2.72 0.000 1 unchanged
#> 400 16 17 1 2.72 0.368 0.713 unchanged
#> 401 9 9 0 2.72 0.000 1 unchanged
#> 402 3 4 1 2.72 0.368 0.713 unchanged
#> 403 3 2 -1 2.72 -0.368 0.713 unchanged
#> 404 10 10 0 2.72 0.000 1 unchanged
#> 405 15 17 2 2.72 0.735 0.462 unchanged
#> 406 17 13 -4 2.72 -1.471 0.141 unchanged
#> 407 3 8 5 2.72 1.838 0.066 unchanged
#> 408 10 14 4 2.72 1.471 0.141 unchanged
#> 409 15 8 -7 2.72 -2.573 0.01 decreased
#> 410 12 10 -2 2.72 -0.735 0.462 unchanged
#> 411 8 6 -2 2.72 -0.735 0.462 unchanged
#> 412 9 9 0 2.72 0.000 1 unchanged
#> 413 14 17 3 2.72 1.103 0.27 unchanged
#> 414 3 2 -1 2.72 -0.368 0.713 unchanged
#> 415 5 3 -2 2.72 -0.735 0.462 unchanged
#> 416 9 9 0 2.72 0.000 1 unchanged
#> 417 12 8 -4 2.72 -1.471 0.141 unchanged
#> 418 16 12 -4 2.72 -1.471 0.141 unchanged
#> 419 9 9 0 2.72 0.000 1 unchanged
#> 420 5 5 0 2.72 0.000 1 unchanged
#> 421 14 16 2 2.72 0.735 0.462 unchanged
#> 422 5 3 -2 2.72 -0.735 0.462 unchanged
#> 423 18 19 1 2.72 0.368 0.713 unchanged
#> 424 10 10 0 2.72 0.000 1 unchanged
#> 425 9 12 3 2.72 1.103 0.27 unchanged
#> 426 15 16 1 2.72 0.368 0.713 unchanged
#> 427 4 6 2 2.72 0.735 0.462 unchanged
#> 428 11 8 -3 2.72 -1.103 0.27 unchanged
#> 429 14 14 0 2.72 0.000 1 unchanged
#> 430 5 6 1 2.72 0.368 0.713 unchanged
#> 431 19 19 0 2.72 0.000 1 unchanged
#> 432 13 12 -1 2.72 -0.368 0.713 unchanged
#> 433 14 20 6 2.72 2.206 0.027 increased
#> 434 12 15 3 2.72 1.103 0.27 unchanged
#> 435 16 16 0 2.72 0.000 1 unchanged
#> 436 11 12 1 2.72 0.368 0.713 unchanged
#> 437 11 10 -1 2.72 -0.368 0.713 unchanged
#> 438 10 11 1 2.72 0.368 0.713 unchanged
#> 439 9 7 -2 2.72 -0.735 0.462 unchanged
#> 440 18 15 -3 2.72 -1.103 0.27 unchanged
#> 441 2 3 1 2.72 0.368 0.713 unchanged
#> 442 4 5 1 2.72 0.368 0.713 unchanged
#> 443 15 11 -4 2.72 -1.471 0.141 unchanged
#> 444 2 4 2 2.72 0.735 0.462 unchanged
#> 445 16 9 -7 2.72 -2.573 0.01 decreased
#> 446 4 5 1 2.72 0.368 0.713 unchanged
#> 447 10 13 3 2.72 1.103 0.27 unchanged
#> 448 15 14 -1 2.72 -0.368 0.713 unchanged
#> 449 11 8 -3 2.72 -1.103 0.27 unchanged
#> 450 16 18 2 2.72 0.735 0.462 unchanged
#> 451 3 3 0 2.72 0.000 1 unchanged
#> 452 10 10 0 2.72 0.000 1 unchanged
#> 453 17 19 2 2.72 0.735 0.462 unchanged
#> 454 18 18 0 2.72 0.000 1 unchanged
#> 455 16 18 2 2.72 0.735 0.462 unchanged
#> 456 2 3 1 2.72 0.368 0.713 unchanged
#> 457 13 14 1 2.72 0.368 0.713 unchanged
#> 458 6 11 5 2.72 1.838 0.066 unchanged
#> 459 5 4 -1 2.72 -0.368 0.713 unchanged
#> 460 20 18 -2 2.72 -0.735 0.462 unchanged
#> 461 9 5 -4 2.72 -1.471 0.141 unchanged
#> 462 11 13 2 2.72 0.735 0.462 unchanged
#> 463 10 11 1 2.72 0.368 0.713 unchanged
#> 464 15 19 4 2.72 1.471 0.141 unchanged
#> 465 10 9 -1 2.72 -0.368 0.713 unchanged
#> 466 9 3 -6 2.72 -2.206 0.027 decreased
#> 467 3 4 1 2.72 0.368 0.713 unchanged
#> 468 3 2 -1 2.72 -0.368 0.713 unchanged
#> 469 18 19 1 2.72 0.368 0.713 unchanged
#> 470 17 13 -4 2.72 -1.471 0.141 unchanged
#> 471 12 13 1 2.72 0.368 0.713 unchanged
#> 472 11 15 4 2.72 1.471 0.141 unchanged
#> 473 15 12 -3 2.72 -1.103 0.27 unchanged
#> 474 8 8 0 2.72 0.000 1 unchanged
#> 475 4 6 2 2.72 0.735 0.462 unchanged
#> 476 18 16 -2 2.72 -0.735 0.462 unchanged
#> 477 4 5 1 2.72 0.368 0.713 unchanged
#> 478 2 3 1 2.72 0.368 0.713 unchanged
#> 479 14 17 3 2.72 1.103 0.27 unchanged
#> 480 9 5 -4 2.72 -1.471 0.141 unchanged
#> 481 6 8 2 2.72 0.735 0.462 unchanged
#> 482 20 20 0 2.72 0.000 1 unchanged
#> 483 8 8 0 2.72 0.000 1 unchanged
#> 484 2 3 1 2.72 0.368 0.713 unchanged
#> 485 15 12 -3 2.72 -1.103 0.27 unchanged
#> 486 15 16 1 2.72 0.368 0.713 unchanged
#> 487 9 12 3 2.72 1.103 0.27 unchanged
#> 488 8 6 -2 2.72 -0.735 0.462 unchanged
#> 489 13 17 4 2.72 1.471 0.141 unchanged
#> 490 12 9 -3 2.72 -1.103 0.27 unchanged
#> 491 14 10 -4 2.72 -1.471 0.141 unchanged
#> 492 19 18 -1 2.72 -0.368 0.713 unchanged
#> 493 14 10 -4 2.72 -1.471 0.141 unchanged
#> 494 11 6 -5 2.72 -1.838 0.066 unchanged
#> 495 5 4 -1 2.72 -0.368 0.713 unchanged
#> 496 12 12 0 2.72 0.000 1 unchanged
#> 497 13 14 1 2.72 0.368 0.713 unchanged
#> 498 19 18 -1 2.72 -0.368 0.713 unchanged
#> 499 7 8 1 2.72 0.368 0.713 unchanged
#> 500 20 20 0 2.72 0.000 1 unchanged
#> 501 6 8 2 2.72 0.735 0.462 unchanged
#> 502 17 18 1 2.72 0.368 0.713 unchanged
#> 503 9 9 0 2.72 0.000 1 unchanged
#> 504 12 13 1 2.72 0.368 0.713 unchanged
#> 505 8 13 5 2.72 1.838 0.066 unchanged
#> 506 9 11 2 2.72 0.735 0.462 unchanged
#> 507 9 8 -1 2.72 -0.368 0.713 unchanged
#> 508 6 5 -1 2.72 -0.368 0.713 unchanged
#> 509 15 14 -1 2.72 -0.368 0.713 unchanged
#> 510 15 12 -3 2.72 -1.103 0.27 unchanged
#> 511 14 14 0 2.72 0.000 1 unchanged
#> 512 1 0 -1 2.72 -0.368 0.713 unchanged
#> 513 5 11 6 2.72 2.206 0.027 increased
#> 514 5 4 -1 2.72 -0.368 0.713 unchanged
#> 515 15 11 -4 2.72 -1.471 0.141 unchanged
#> 516 19 18 -1 2.72 -0.368 0.713 unchanged
#> 517 16 15 -1 2.72 -0.368 0.713 unchanged
#> 518 6 6 0 2.72 0.000 1 unchanged
#> 519 9 14 5 2.72 1.838 0.066 unchanged
#> 520 11 5 -6 2.72 -2.206 0.027 decreased
#> 521 8 11 3 2.72 1.103 0.27 unchanged
#> 522 3 4 1 2.72 0.368 0.713 unchanged
#> 523 11 9 -2 2.72 -0.735 0.462 unchanged
#> 524 16 13 -3 2.72 -1.103 0.27 unchanged
#> 525 16 16 0 2.72 0.000 1 unchanged
#> 526 14 13 -1 2.72 -0.368 0.713 unchanged
#> 527 11 12 1 2.72 0.368 0.713 unchanged
#> 528 17 16 -1 2.72 -0.368 0.713 unchanged
#> 529 7 10 3 2.72 1.103 0.27 unchanged
#> 530 11 11 0 2.72 0.000 1 unchanged
#> 531 7 5 -2 2.72 -0.735 0.462 unchanged
#> 532 12 17 5 2.72 1.838 0.066 unchanged
#> 533 10 16 6 2.72 2.206 0.027 increased
#> 534 15 14 -1 2.72 -0.368 0.713 unchanged
#> 535 16 14 -2 2.72 -0.735 0.462 unchanged
#> 536 8 15 7 2.72 2.573 0.01 increased
#> 537 19 16 -3 2.72 -1.103 0.27 unchanged
#> 538 14 14 0 2.72 0.000 1 unchanged
#> 539 10 8 -2 2.72 -0.735 0.462 unchanged
#> 540 11 9 -2 2.72 -0.735 0.462 unchanged
#> 541 20 19 -1 2.72 -0.368 0.713 unchanged
#> 542 17 18 1 2.72 0.368 0.713 unchanged
#> 543 9 8 -1 2.72 -0.368 0.713 unchanged
#> 544 18 20 2 2.72 0.735 0.462 unchanged
#> 545 12 10 -2 2.72 -0.735 0.462 unchanged
#> 546 10 14 4 2.72 1.471 0.141 unchanged
#> 547 8 8 0 2.72 0.000 1 unchanged
#> 548 10 11 1 2.72 0.368 0.713 unchanged
#> 549 15 8 -7 2.72 -2.573 0.01 decreased
#> 550 5 4 -1 2.72 -0.368 0.713 unchanged
#> 551 5 6 1 2.72 0.368 0.713 unchanged
#> 552 6 7 1 2.72 0.368 0.713 unchanged
#> 553 9 13 4 2.72 1.471 0.141 unchanged
#> 554 8 5 -3 2.72 -1.103 0.27 unchanged
#> 555 12 10 -2 2.72 -0.735 0.462 unchanged
#> 556 15 15 0 2.72 0.000 1 unchanged
#> 557 9 13 4 2.72 1.471 0.141 unchanged
#> 558 11 14 3 2.72 1.103 0.27 unchanged
#> 559 12 13 1 2.72 0.368 0.713 unchanged
#> 560 4 5 1 2.72 0.368 0.713 unchanged
#> 561 13 14 1 2.72 0.368 0.713 unchanged
#> 562 11 13 2 2.72 0.735 0.462 unchanged
#> 563 14 10 -4 2.72 -1.471 0.141 unchanged
#> 564 1 4 3 2.72 1.103 0.27 unchanged
#> 565 13 14 1 2.72 0.368 0.713 unchanged
#> 566 15 14 -1 2.72 -0.368 0.713 unchanged
#> 567 8 7 -1 2.72 -0.368 0.713 unchanged
#> 568 15 16 1 2.72 0.368 0.713 unchanged
#> 569 19 19 0 2.72 0.000 1 unchanged
#> 570 13 11 -2 2.72 -0.735 0.462 unchanged
#> 571 15 14 -1 2.72 -0.368 0.713 unchanged
#> 572 5 6 1 2.72 0.368 0.713 unchanged
#> 573 2 3 1 2.72 0.368 0.713 unchanged
#> 574 19 14 -5 2.72 -1.838 0.066 unchanged
#> 575 3 1 -2 2.72 -0.735 0.462 unchanged
#> 576 17 18 1 2.72 0.368 0.713 unchanged
#> 577 2 3 1 2.72 0.368 0.713 unchanged
#> 578 19 17 -2 2.72 -0.735 0.462 unchanged
#> 579 13 13 0 2.72 0.000 1 unchanged
#> 580 20 15 -5 2.72 -1.838 0.066 unchanged
#> 581 6 5 -1 2.72 -0.368 0.713 unchanged
#> 582 17 18 1 2.72 0.368 0.713 unchanged
#> 583 7 6 -1 2.72 -0.368 0.713 unchanged
#> 584 6 4 -2 2.72 -0.735 0.462 unchanged
#> 585 16 12 -4 2.72 -1.471 0.141 unchanged
#> 586 13 13 0 2.72 0.000 1 unchanged
#> 587 18 17 -1 2.72 -0.368 0.713 unchanged
#> 588 9 7 -2 2.72 -0.735 0.462 unchanged
#> 589 12 10 -2 2.72 -0.735 0.462 unchanged
#> 590 12 14 2 2.72 0.735 0.462 unchanged
#> 591 9 12 3 2.72 1.103 0.27 unchanged
#> 592 12 16 4 2.72 1.471 0.141 unchanged
#> 593 17 15 -2 2.72 -0.735 0.462 unchanged
#> 594 4 3 -1 2.72 -0.368 0.713 unchanged
#> 595 8 8 0 2.72 0.000 1 unchanged
#> 596 11 9 -2 2.72 -0.735 0.462 unchanged
#> 597 8 10 2 2.72 0.735 0.462 unchanged
#> 598 10 12 2 2.72 0.735 0.462 unchanged
#> 599 13 13 0 2.72 0.000 1 unchanged
#> 600 12 16 4 2.72 1.471 0.141 unchanged
#> 601 15 19 4 2.72 1.471 0.141 unchanged
#> 602 11 9 -2 2.72 -0.735 0.462 unchanged
#> 603 5 3 -2 2.72 -0.735 0.462 unchanged
#> 604 7 9 2 2.72 0.735 0.462 unchanged
#> 605 7 2 -5 2.72 -1.838 0.066 unchanged
#> 606 2 6 4 2.72 1.471 0.141 unchanged
#> 607 10 8 -2 2.72 -0.735 0.462 unchanged
#> 608 14 14 0 2.72 0.000 1 unchanged
#> 609 11 12 1 2.72 0.368 0.713 unchanged
#> 610 12 7 -5 2.72 -1.838 0.066 unchanged
#> 611 13 12 -1 2.72 -0.368 0.713 unchanged
#> 612 10 9 -1 2.72 -0.368 0.713 unchanged
#> 613 11 13 2 2.72 0.735 0.462 unchanged
#> 614 5 6 1 2.72 0.368 0.713 unchanged
#> 615 12 12 0 2.72 0.000 1 unchanged
#> 616 4 1 -3 2.72 -1.103 0.27 unchanged
#> 617 4 7 3 2.72 1.103 0.27 unchanged
#> 618 5 5 0 2.72 0.000 1 unchanged
#> 619 16 18 2 2.72 0.735 0.462 unchanged
#> 620 4 6 2 2.72 0.735 0.462 unchanged
#> 621 19 16 -3 2.72 -1.103 0.27 unchanged
#> 622 13 12 -1 2.72 -0.368 0.713 unchanged
#> 623 17 19 2 2.72 0.735 0.462 unchanged
#> 624 8 5 -3 2.72 -1.103 0.27 unchanged
#> 625 9 11 2 2.72 0.735 0.462 unchanged
#> 626 5 4 -1 2.72 -0.368 0.713 unchanged
#> 627 5 5 0 2.72 0.000 1 unchanged
#> 628 4 1 -3 2.72 -1.103 0.27 unchanged
#> 629 7 8 1 2.72 0.368 0.713 unchanged
#> 630 8 13 5 2.72 1.838 0.066 unchanged
#> 631 14 18 4 2.72 1.471 0.141 unchanged
#> 632 8 3 -5 2.72 -1.838 0.066 unchanged
#> 633 16 16 0 2.72 0.000 1 unchanged
#> 634 13 14 1 2.72 0.368 0.713 unchanged
#> 635 15 11 -4 2.72 -1.471 0.141 unchanged
#> 636 13 9 -4 2.72 -1.471 0.141 unchanged
#> 637 6 7 1 2.72 0.368 0.713 unchanged
#> 638 12 7 -5 2.72 -1.838 0.066 unchanged
#> 639 6 6 0 2.72 0.000 1 unchanged
#> 640 3 2 -1 2.72 -0.368 0.713 unchanged
#> 641 9 7 -2 2.72 -0.735 0.462 unchanged
#> 642 7 7 0 2.72 0.000 1 unchanged
#> 643 16 16 0 2.72 0.000 1 unchanged
#> 644 13 13 0 2.72 0.000 1 unchanged
#> 645 12 15 3 2.72 1.103 0.27 unchanged
#> 646 2 3 1 2.72 0.368 0.713 unchanged
#> 647 18 14 -4 2.72 -1.471 0.141 unchanged
#> 648 5 7 2 2.72 0.735 0.462 unchanged
#> 649 6 4 -2 2.72 -0.735 0.462 unchanged
#> 650 19 18 -1 2.72 -0.368 0.713 unchanged
#> 651 8 4 -4 2.72 -1.471 0.141 unchanged
#> 652 10 12 2 2.72 0.735 0.462 unchanged
#> 653 6 10 4 2.72 1.471 0.141 unchanged
#> 654 4 5 1 2.72 0.368 0.713 unchanged
#> 655 6 6 0 2.72 0.000 1 unchanged
#> 656 7 5 -2 2.72 -0.735 0.462 unchanged
#> 657 13 12 -1 2.72 -0.368 0.713 unchanged
#> 658 10 13 3 2.72 1.103 0.27 unchanged
#> 659 18 17 -1 2.72 -0.368 0.713 unchanged
#> 660 11 8 -3 2.72 -1.103 0.27 unchanged
#> 661 10 7 -3 2.72 -1.103 0.27 unchanged
#> 662 19 18 -1 2.72 -0.368 0.713 unchanged
#> 663 12 14 2 2.72 0.735 0.462 unchanged
#> 664 17 19 2 2.72 0.735 0.462 unchanged
#> 665 11 15 4 2.72 1.471 0.141 unchanged
#> 666 13 13 0 2.72 0.000 1 unchanged
#> 667 10 12 2 2.72 0.735 0.462 unchanged
#> 668 11 12 1 2.72 0.368 0.713 unchanged
#> 669 8 11 3 2.72 1.103 0.27 unchanged
#> 670 8 5 -3 2.72 -1.103 0.27 unchanged
#> 671 12 11 -1 2.72 -0.368 0.713 unchanged
#> 672 10 10 0 2.72 0.000 1 unchanged
#> 673 9 10 1 2.72 0.368 0.713 unchanged
#> 674 12 15 3 2.72 1.103 0.27 unchanged
#> 675 7 11 4 2.72 1.471 0.141 unchanged
#> 676 4 2 -2 2.72 -0.735 0.462 unchanged
#> 677 15 17 2 2.72 0.735 0.462 unchanged
#> 678 9 6 -3 2.72 -1.103 0.27 unchanged
#> 679 11 11 0 2.72 0.000 1 unchanged
#> 680 17 16 -1 2.72 -0.368 0.713 unchanged
#> 681 19 19 0 2.72 0.000 1 unchanged
#> 682 9 10 1 2.72 0.368 0.713 unchanged
#> 683 19 18 -1 2.72 -0.368 0.713 unchanged
#> 684 5 1 -4 2.72 -1.471 0.141 unchanged
#> 685 12 10 -2 2.72 -0.735 0.462 unchanged
#> 686 16 13 -3 2.72 -1.103 0.27 unchanged
#> 687 9 10 1 2.72 0.368 0.713 unchanged
#> 688 7 6 -1 2.72 -0.368 0.713 unchanged
#> 689 4 2 -2 2.72 -0.735 0.462 unchanged
#> 690 14 15 1 2.72 0.368 0.713 unchanged
#> 691 12 14 2 2.72 0.735 0.462 unchanged
#> 692 4 8 4 2.72 1.471 0.141 unchanged
#> 693 10 9 -1 2.72 -0.368 0.713 unchanged
#> 694 13 9 -4 2.72 -1.471 0.141 unchanged
#> 695 16 17 1 2.72 0.368 0.713 unchanged
#> 696 14 13 -1 2.72 -0.368 0.713 unchanged
#> 697 9 9 0 2.72 0.000 1 unchanged
#> 698 3 5 2 2.72 0.735 0.462 unchanged
#> 699 5 3 -2 2.72 -0.735 0.462 unchanged
#> 700 10 13 3 2.72 1.103 0.27 unchanged
#> 701 2 4 2 2.72 0.735 0.462 unchanged
#> 702 14 11 -3 2.72 -1.103 0.27 unchanged
#> 703 13 11 -2 2.72 -0.735 0.462 unchanged
#> 704 12 13 1 2.72 0.368 0.713 unchanged
#> 705 16 17 1 2.72 0.368 0.713 unchanged
#> 706 15 17 2 2.72 0.735 0.462 unchanged
#> 707 5 1 -4 2.72 -1.471 0.141 unchanged
#> 708 13 13 0 2.72 0.000 1 unchanged
#> 709 13 17 4 2.72 1.471 0.141 unchanged
#> 710 8 6 -2 2.72 -0.735 0.462 unchanged
#> 711 17 20 3 2.72 1.103 0.27 unchanged
#> 712 8 6 -2 2.72 -0.735 0.462 unchanged
#> 713 13 12 -1 2.72 -0.368 0.713 unchanged
#> 714 3 5 2 2.72 0.735 0.462 unchanged
#> 715 6 3 -3 2.72 -1.103 0.27 unchanged
#> 716 15 16 1 2.72 0.368 0.713 unchanged
#> 717 10 9 -1 2.72 -0.368 0.713 unchanged
#> 718 9 12 3 2.72 1.103 0.27 unchanged
#> 719 18 15 -3 2.72 -1.103 0.27 unchanged
#> 720 5 6 1 2.72 0.368 0.713 unchanged
#> 721 11 9 -2 2.72 -0.735 0.462 unchanged
#> 722 7 7 0 2.72 0.000 1 unchanged
#> 723 16 18 2 2.72 0.735 0.462 unchanged
#> 724 6 13 7 2.72 2.573 0.01 increased
#> 725 9 7 -2 2.72 -0.735 0.462 unchanged
#> 726 4 4 0 2.72 0.000 1 unchanged
#> 727 4 3 -1 2.72 -0.368 0.713 unchanged
#> 728 9 10 1 2.72 0.368 0.713 unchanged
#> 729 7 5 -2 2.72 -0.735 0.462 unchanged
#> 730 9 10 1 2.72 0.368 0.713 unchanged
#> 731 14 16 2 2.72 0.735 0.462 unchanged
#> 732 2 4 2 2.72 0.735 0.462 unchanged
#> 733 10 8 -2 2.72 -0.735 0.462 unchanged
#> 734 17 12 -5 2.72 -1.838 0.066 unchanged
#> 735 12 12 0 2.72 0.000 1 unchanged
#> 736 11 10 -1 2.72 -0.368 0.713 unchanged
#> 737 13 14 1 2.72 0.368 0.713 unchanged
#> 738 12 13 1 2.72 0.368 0.713 unchanged
#> 739 7 7 0 2.72 0.000 1 unchanged
#> 740 9 8 -1 2.72 -0.368 0.713 unchanged
#> 741 7 4 -3 2.72 -1.103 0.27 unchanged
#> 742 8 7 -1 2.72 -0.368 0.713 unchanged
#> 743 20 18 -2 2.72 -0.735 0.462 unchanged
#> 744 12 10 -2 2.72 -0.735 0.462 unchanged
#> 745 10 10 0 2.72 0.000 1 unchanged
#> 746 18 19 1 2.72 0.368 0.713 unchanged
#> 747 7 7 0 2.72 0.000 1 unchanged
#> 748 16 17 1 2.72 0.368 0.713 unchanged
#> 749 7 8 1 2.72 0.368 0.713 unchanged
#> 750 20 18 -2 2.72 -0.735 0.462 unchanged
#> 751 8 8 0 2.72 0.000 1 unchanged
#> 752 8 10 2 2.72 0.735 0.462 unchanged
#> 753 12 14 2 2.72 0.735 0.462 unchanged
#> 754 15 17 2 2.72 0.735 0.462 unchanged
#> 755 9 11 2 2.72 0.735 0.462 unchanged
#> 756 10 8 -2 2.72 -0.735 0.462 unchanged
#> 757 1 2 1 2.72 0.368 0.713 unchanged
#> 758 4 6 2 2.72 0.735 0.462 unchanged
#> 759 13 14 1 2.72 0.368 0.713 unchanged
#> 760 15 17 2 2.72 0.735 0.462 unchanged
#> 761 6 4 -2 2.72 -0.735 0.462 unchanged
#> 762 17 11 -6 2.72 -2.206 0.027 decreased
#> 763 13 13 0 2.72 0.000 1 unchanged
#> 764 13 15 2 2.72 0.735 0.462 unchanged
#> 765 13 14 1 2.72 0.368 0.713 unchanged
#> 766 13 13 0 2.72 0.000 1 unchanged
#> 767 17 14 -3 2.72 -1.103 0.27 unchanged
#> 768 2 2 0 2.72 0.000 1 unchanged
#> 769 18 16 -2 2.72 -0.735 0.462 unchanged
#> 770 19 20 1 2.72 0.368 0.713 unchanged
#> 771 3 4 1 2.72 0.368 0.713 unchanged
#> 772 17 11 -6 2.72 -2.206 0.027 decreased
#> 773 15 15 0 2.72 0.000 1 unchanged
#> 774 13 14 1 2.72 0.368 0.713 unchanged
#> 775 3 1 -2 2.72 -0.735 0.462 unchanged
#> 776 18 16 -2 2.72 -0.735 0.462 unchanged
#> 777 12 12 0 2.72 0.000 1 unchanged
#> 778 12 14 2 2.72 0.735 0.462 unchanged
#> 779 5 5 0 2.72 0.000 1 unchanged
#> 780 9 8 -1 2.72 -0.368 0.713 unchanged
#> 781 20 17 -3 2.72 -1.103 0.27 unchanged
#> 782 12 8 -4 2.72 -1.471 0.141 unchanged
#> 783 2 1 -1 2.72 -0.368 0.713 unchanged
#> 784 7 6 -1 2.72 -0.368 0.713 unchanged
#> 785 14 14 0 2.72 0.000 1 unchanged
#> 786 12 10 -2 2.72 -0.735 0.462 unchanged
#> 787 14 12 -2 2.72 -0.735 0.462 unchanged
#> 788 13 14 1 2.72 0.368 0.713 unchanged
#> 789 9 12 3 2.72 1.103 0.27 unchanged
#> 790 11 7 -4 2.72 -1.471 0.141 unchanged
#> 791 10 9 -1 2.72 -0.368 0.713 unchanged
#> 792 14 14 0 2.72 0.000 1 unchanged
#> 793 8 5 -3 2.72 -1.103 0.27 unchanged
#> 794 19 18 -1 2.72 -0.368 0.713 unchanged
#> 795 12 12 0 2.72 0.000 1 unchanged
#> 796 13 15 2 2.72 0.735 0.462 unchanged
#> 797 10 6 -4 2.72 -1.471 0.141 unchanged
#> 798 7 4 -3 2.72 -1.103 0.27 unchanged
#> 799 6 2 -4 2.72 -1.471 0.141 unchanged
#> 800 4 8 4 2.72 1.471 0.141 unchanged
#> 801 20 17 -3 2.72 -1.103 0.27 unchanged
#> 802 5 6 1 2.72 0.368 0.713 unchanged
#> 803 18 17 -1 2.72 -0.368 0.713 unchanged
#> 804 11 13 2 2.72 0.735 0.462 unchanged
#> 805 9 6 -3 2.72 -1.103 0.27 unchanged
#> 806 6 4 -2 2.72 -0.735 0.462 unchanged
#> 807 6 6 0 2.72 0.000 1 unchanged
#> 808 9 10 1 2.72 0.368 0.713 unchanged
#> 809 11 11 0 2.72 0.000 1 unchanged
#> 810 4 7 3 2.72 1.103 0.27 unchanged
#> 811 4 6 2 2.72 0.735 0.462 unchanged
#> 812 11 12 1 2.72 0.368 0.713 unchanged
#> 813 18 20 2 2.72 0.735 0.462 unchanged
#> 814 6 7 1 2.72 0.368 0.713 unchanged
#> 815 14 13 -1 2.72 -0.368 0.713 unchanged
#> 816 11 12 1 2.72 0.368 0.713 unchanged
#> 817 8 7 -1 2.72 -0.368 0.713 unchanged
#> 818 16 19 3 2.72 1.103 0.27 unchanged
#> 819 5 3 -2 2.72 -0.735 0.462 unchanged
#> 820 17 13 -4 2.72 -1.471 0.141 unchanged
#> 821 11 14 3 2.72 1.103 0.27 unchanged
#> 822 10 10 0 2.72 0.000 1 unchanged
#> 823 10 16 6 2.72 2.206 0.027 increased
#> 824 11 12 1 2.72 0.368 0.713 unchanged
#> 825 8 13 5 2.72 1.838 0.066 unchanged
#> 826 13 15 2 2.72 0.735 0.462 unchanged
#> 827 14 10 -4 2.72 -1.471 0.141 unchanged
#> 828 14 13 -1 2.72 -0.368 0.713 unchanged
#> 829 7 13 6 2.72 2.206 0.027 increased
#> 830 10 11 1 2.72 0.368 0.713 unchanged
#> 831 6 6 0 2.72 0.000 1 unchanged
#> 832 5 6 1 2.72 0.368 0.713 unchanged
#> 833 15 16 1 2.72 0.368 0.713 unchanged
#> 834 5 9 4 2.72 1.471 0.141 unchanged
#> 835 10 3 -7 2.72 -2.573 0.01 decreased
#> 836 14 15 1 2.72 0.368 0.713 unchanged
#> 837 2 6 4 2.72 1.471 0.141 unchanged
#> 838 1 0 -1 2.72 -0.368 0.713 unchanged
#> 839 19 19 0 2.72 0.000 1 unchanged
#> 840 7 7 0 2.72 0.000 1 unchanged
#> 841 16 14 -2 2.72 -0.735 0.462 unchanged
#> 842 18 17 -1 2.72 -0.368 0.713 unchanged
#> 843 18 17 -1 2.72 -0.368 0.713 unchanged
#> 844 11 10 -1 2.72 -0.368 0.713 unchanged
#> 845 16 15 -1 2.72 -0.368 0.713 unchanged
#> 846 10 11 1 2.72 0.368 0.713 unchanged
#> 847 15 16 1 2.72 0.368 0.713 unchanged
#> 848 15 11 -4 2.72 -1.471 0.141 unchanged
#> 849 18 15 -3 2.72 -1.103 0.27 unchanged
#> 850 13 15 2 2.72 0.735 0.462 unchanged
#> 851 16 17 1 2.72 0.368 0.713 unchanged
#> 852 13 16 3 2.72 1.103 0.27 unchanged
#> 853 6 9 3 2.72 1.103 0.27 unchanged
#> 854 14 16 2 2.72 0.735 0.462 unchanged
#> 855 12 11 -1 2.72 -0.368 0.713 unchanged
#> 856 5 6 1 2.72 0.368 0.713 unchanged
#> 857 6 7 1 2.72 0.368 0.713 unchanged
#> 858 7 13 6 2.72 2.206 0.027 increased
#> 859 18 18 0 2.72 0.000 1 unchanged
#> 860 11 13 2 2.72 0.735 0.462 unchanged
#> 861 11 10 -1 2.72 -0.368 0.713 unchanged
#> 862 9 6 -3 2.72 -1.103 0.27 unchanged
#> 863 8 7 -1 2.72 -0.368 0.713 unchanged
#> 864 9 7 -2 2.72 -0.735 0.462 unchanged
#> 865 15 13 -2 2.72 -0.735 0.462 unchanged
#> 866 12 9 -3 2.72 -1.103 0.27 unchanged
#> 867 10 12 2 2.72 0.735 0.462 unchanged
#> 868 17 12 -5 2.72 -1.838 0.066 unchanged
#> 869 6 8 2 2.72 0.735 0.462 unchanged
#> 870 4 4 0 2.72 0.000 1 unchanged
#> 871 16 15 -1 2.72 -0.368 0.713 unchanged
#> 872 7 3 -4 2.72 -1.471 0.141 unchanged
#> 873 4 7 3 2.72 1.103 0.27 unchanged
#> 874 12 12 0 2.72 0.000 1 unchanged
#> 875 14 12 -2 2.72 -0.735 0.462 unchanged
#> 876 17 13 -4 2.72 -1.471 0.141 unchanged
#> 877 12 11 -1 2.72 -0.368 0.713 unchanged
#> 878 6 6 0 2.72 0.000 1 unchanged
#> 879 8 13 5 2.72 1.838 0.066 unchanged
#> 880 15 17 2 2.72 0.735 0.462 unchanged
#> 881 7 10 3 2.72 1.103 0.27 unchanged
#> 882 2 1 -1 2.72 -0.368 0.713 unchanged
#> 883 13 18 5 2.72 1.838 0.066 unchanged
#> 884 17 18 1 2.72 0.368 0.713 unchanged
#> 885 8 10 2 2.72 0.735 0.462 unchanged
#> 886 18 19 1 2.72 0.368 0.713 unchanged
#> 887 17 16 -1 2.72 -0.368 0.713 unchanged
#> 888 14 11 -3 2.72 -1.103 0.27 unchanged
#> 889 6 6 0 2.72 0.000 1 unchanged
#> 890 4 3 -1 2.72 -0.368 0.713 unchanged
#> 891 12 10 -2 2.72 -0.735 0.462 unchanged
#> 892 11 12 1 2.72 0.368 0.713 unchanged
#> 893 5 7 2 2.72 0.735 0.462 unchanged
#> 894 15 17 2 2.72 0.735 0.462 unchanged
#> 895 6 11 5 2.72 1.838 0.066 unchanged
#> 896 11 7 -4 2.72 -1.471 0.141 unchanged
#> 897 11 13 2 2.72 0.735 0.462 unchanged
#> 898 6 5 -1 2.72 -0.368 0.713 unchanged
#> 899 13 11 -2 2.72 -0.735 0.462 unchanged
#> 900 5 9 4 2.72 1.471 0.141 unchanged
#> 901 10 10 0 2.72 0.000 1 unchanged
#> 902 17 18 1 2.72 0.368 0.713 unchanged
#> 903 15 14 -1 2.72 -0.368 0.713 unchanged
#> 904 8 11 3 2.72 1.103 0.27 unchanged
#> 905 17 16 -1 2.72 -0.368 0.713 unchanged
#> 906 14 17 3 2.72 1.103 0.27 unchanged
#> 907 9 10 1 2.72 0.368 0.713 unchanged
#> 908 13 8 -5 2.72 -1.838 0.066 unchanged
#> 909 7 5 -2 2.72 -0.735 0.462 unchanged
#> 910 8 6 -2 2.72 -0.735 0.462 unchanged
#> 911 18 19 1 2.72 0.368 0.713 unchanged
#> 912 15 17 2 2.72 0.735 0.462 unchanged
#> 913 11 12 1 2.72 0.368 0.713 unchanged
#> 914 10 10 0 2.72 0.000 1 unchanged
#> 915 18 19 1 2.72 0.368 0.713 unchanged
#> 916 18 16 -2 2.72 -0.735 0.462 unchanged
#> 917 10 10 0 2.72 0.000 1 unchanged
#> 918 2 1 -1 2.72 -0.368 0.713 unchanged
#> 919 16 17 1 2.72 0.368 0.713 unchanged
#> 920 2 1 -1 2.72 -0.368 0.713 unchanged
#> 921 20 20 0 2.72 0.000 1 unchanged
#> 922 6 2 -4 2.72 -1.471 0.141 unchanged
#> 923 18 17 -1 2.72 -0.368 0.713 unchanged
#> 924 13 19 6 2.72 2.206 0.027 increased
#> 925 14 11 -3 2.72 -1.103 0.27 unchanged
#> 926 18 17 -1 2.72 -0.368 0.713 unchanged
#> 927 16 15 -1 2.72 -0.368 0.713 unchanged
#> 928 18 11 -7 2.72 -2.573 0.01 decreased
#> 929 15 12 -3 2.72 -1.103 0.27 unchanged
#> 930 9 5 -4 2.72 -1.471 0.141 unchanged
#> 931 9 9 0 2.72 0.000 1 unchanged
#> 932 10 10 0 2.72 0.000 1 unchanged
#> 933 16 18 2 2.72 0.735 0.462 unchanged
#> 934 5 7 2 2.72 0.735 0.462 unchanged
#> 935 16 17 1 2.72 0.368 0.713 unchanged
#> 936 8 10 2 2.72 0.735 0.462 unchanged
#> 937 5 4 -1 2.72 -0.368 0.713 unchanged
#> 938 16 15 -1 2.72 -0.368 0.713 unchanged
#> 939 13 10 -3 2.72 -1.103 0.27 unchanged
#> 940 10 13 3 2.72 1.103 0.27 unchanged
#> 941 14 14 0 2.72 0.000 1 unchanged
#> 942 10 14 4 2.72 1.471 0.141 unchanged
#> 943 4 3 -1 2.72 -0.368 0.713 unchanged
#> 944 20 18 -2 2.72 -0.735 0.462 unchanged
#> 945 6 8 2 2.72 0.735 0.462 unchanged
#> 946 8 5 -3 2.72 -1.103 0.27 unchanged
#> 947 7 17 10 2.72 3.676 0 increased
#> 948 7 3 -4 2.72 -1.471 0.141 unchanged
#> 949 14 14 0 2.72 0.000 1 unchanged
#> 950 14 13 -1 2.72 -0.368 0.713 unchanged
#> 951 14 13 -1 2.72 -0.368 0.713 unchanged
#> 952 14 10 -4 2.72 -1.471 0.141 unchanged
#> 953 12 9 -3 2.72 -1.103 0.27 unchanged
#> 954 8 8 0 2.72 0.000 1 unchanged
#> 955 14 11 -3 2.72 -1.103 0.27 unchanged
#> 956 10 12 2 2.72 0.735 0.462 unchanged
#> 957 11 9 -2 2.72 -0.735 0.462 unchanged
#> 958 4 4 0 2.72 0.000 1 unchanged
#> 959 9 10 1 2.72 0.368 0.713 unchanged
#> 960 5 7 2 2.72 0.735 0.462 unchanged
#> 961 16 13 -3 2.72 -1.103 0.27 unchanged
#> 962 7 5 -2 2.72 -0.735 0.462 unchanged
#> 963 6 7 1 2.72 0.368 0.713 unchanged
#> 964 5 6 1 2.72 0.368 0.713 unchanged
#> 965 5 2 -3 2.72 -1.103 0.27 unchanged
#> 966 2 5 3 2.72 1.103 0.27 unchanged
#> 967 7 6 -1 2.72 -0.368 0.713 unchanged
#> 968 16 19 3 2.72 1.103 0.27 unchanged
#> 969 8 4 -4 2.72 -1.471 0.141 unchanged
#> 970 4 1 -3 2.72 -1.103 0.27 unchanged
#> 971 12 10 -2 2.72 -0.735 0.462 unchanged
#> 972 3 9 6 2.72 2.206 0.027 increased
#> 973 14 16 2 2.72 0.735 0.462 unchanged
#> 974 7 5 -2 2.72 -0.735 0.462 unchanged
#> 975 16 16 0 2.72 0.000 1 unchanged
#> 976 15 16 1 2.72 0.368 0.713 unchanged
#> 977 11 14 3 2.72 1.103 0.27 unchanged
#> 978 14 13 -1 2.72 -0.368 0.713 unchanged
#> 979 17 18 1 2.72 0.368 0.713 unchanged
#> 980 10 10 0 2.72 0.000 1 unchanged
#> 981 17 18 1 2.72 0.368 0.713 unchanged
#> 982 3 2 -1 2.72 -0.368 0.713 unchanged
#> 983 6 7 1 2.72 0.368 0.713 unchanged
#> 984 4 3 -1 2.72 -0.368 0.713 unchanged
#> 985 14 16 2 2.72 0.735 0.462 unchanged
#> 986 11 11 0 2.72 0.000 1 unchanged
#> 987 5 3 -2 2.72 -0.735 0.462 unchanged
#> 988 1 2 1 2.72 0.368 0.713 unchanged
#> 989 10 11 1 2.72 0.368 0.713 unchanged
#> 990 4 2 -2 2.72 -0.735 0.462 unchanged
#> 991 5 4 -1 2.72 -0.368 0.713 unchanged
#> 992 12 14 2 2.72 0.735 0.462 unchanged
#> 993 20 14 -6 2.72 -2.206 0.027 decreased
#> 994 15 12 -3 2.72 -1.103 0.27 unchanged
#> 995 8 14 6 2.72 2.206 0.027 increased
#> 996 18 17 -1 2.72 -0.368 0.713 unchanged
#> 997 9 13 4 2.72 1.471 0.141 unchanged
#> 998 12 9 -3 2.72 -1.103 0.27 unchanged
#> 999 9 6 -3 2.72 -1.103 0.27 unchanged
#> 1000 10 8 -2 2.72 -0.735 0.462 unchanged
# allows SEM.post != SEM.pre
(istats.post <- itemstats(dat_post)$overall)
#> N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
#> 1000 10.515 4.977 0.224 0.066 0.854 1.901
SEM.alpha.post <- istats.post$SEM.alpha
RCI(predat = dat_pre, postdat = dat_post,
SEM.pre=SEM.alpha, SEM.post=SEM.alpha.post)
#> pre.score post.score diff SE z p
#> 1 15 9 -6 2.705 -2.218 0.027
#> 2 4 0 -4 2.705 -1.479 0.139
#> 3 4 3 -1 2.705 -0.370 0.712
#> 4 6 4 -2 2.705 -0.739 0.46
#> 5 4 5 1 2.705 0.370 0.712
#> 6 6 7 1 2.705 0.370 0.712
#> 7 3 8 5 2.705 1.849 0.065
#> 8 13 12 -1 2.705 -0.370 0.712
#> 9 17 16 -1 2.705 -0.370 0.712
#> 10 16 17 1 2.705 0.370 0.712
#> 11 13 14 1 2.705 0.370 0.712
#> 12 16 12 -4 2.705 -1.479 0.139
#> 13 12 11 -1 2.705 -0.370 0.712
#> 14 9 3 -6 2.705 -2.218 0.027
#> 15 6 6 0 2.705 0.000 1
#> 16 13 13 0 2.705 0.000 1
#> 17 13 11 -2 2.705 -0.739 0.46
#> 18 0 4 4 2.705 1.479 0.139
#> 19 6 8 2 2.705 0.739 0.46
#> 20 4 5 1 2.705 0.370 0.712
#> 21 16 13 -3 2.705 -1.109 0.267
#> 22 12 12 0 2.705 0.000 1
#> 23 13 10 -3 2.705 -1.109 0.267
#> 24 18 17 -1 2.705 -0.370 0.712
#> 25 3 3 0 2.705 0.000 1
#> 26 12 13 1 2.705 0.370 0.712
#> 27 17 15 -2 2.705 -0.739 0.46
#> 28 14 15 1 2.705 0.370 0.712
#> 29 13 17 4 2.705 1.479 0.139
#> 30 10 7 -3 2.705 -1.109 0.267
#> 31 15 13 -2 2.705 -0.739 0.46
#> 32 3 3 0 2.705 0.000 1
#> 33 8 12 4 2.705 1.479 0.139
#> 34 17 18 1 2.705 0.370 0.712
#> 35 6 10 4 2.705 1.479 0.139
#> 36 18 18 0 2.705 0.000 1
#> 37 10 7 -3 2.705 -1.109 0.267
#> 38 17 13 -4 2.705 -1.479 0.139
#> 39 10 3 -7 2.705 -2.588 0.01
#> 40 0 2 2 2.705 0.739 0.46
#> 41 12 10 -2 2.705 -0.739 0.46
#> 42 19 20 1 2.705 0.370 0.712
#> 43 11 10 -1 2.705 -0.370 0.712
#> 44 5 3 -2 2.705 -0.739 0.46
#> 45 16 15 -1 2.705 -0.370 0.712
#> 46 8 12 4 2.705 1.479 0.139
#> 47 17 17 0 2.705 0.000 1
#> 48 12 10 -2 2.705 -0.739 0.46
#> 49 20 16 -4 2.705 -1.479 0.139
#> 50 8 7 -1 2.705 -0.370 0.712
#> 51 9 11 2 2.705 0.739 0.46
#> 52 7 5 -2 2.705 -0.739 0.46
#> 53 13 10 -3 2.705 -1.109 0.267
#> 54 6 10 4 2.705 1.479 0.139
#> 55 7 6 -1 2.705 -0.370 0.712
#> 56 7 9 2 2.705 0.739 0.46
#> 57 5 7 2 2.705 0.739 0.46
#> 58 11 3 -8 2.705 -2.958 0.003
#> 59 13 10 -3 2.705 -1.109 0.267
#> 60 18 18 0 2.705 0.000 1
#> 61 7 7 0 2.705 0.000 1
#> 62 15 16 1 2.705 0.370 0.712
#> 63 11 11 0 2.705 0.000 1
#> 64 7 8 1 2.705 0.370 0.712
#> 65 2 7 5 2.705 1.849 0.065
#> 66 7 4 -3 2.705 -1.109 0.267
#> 67 5 4 -1 2.705 -0.370 0.712
#> 68 9 12 3 2.705 1.109 0.267
#> 69 11 17 6 2.705 2.218 0.027
#> 70 12 11 -1 2.705 -0.370 0.712
#> 71 19 18 -1 2.705 -0.370 0.712
#> 72 15 16 1 2.705 0.370 0.712
#> 73 9 5 -4 2.705 -1.479 0.139
#> 74 8 10 2 2.705 0.739 0.46
#> 75 7 5 -2 2.705 -0.739 0.46
#> 76 16 17 1 2.705 0.370 0.712
#> 77 9 7 -2 2.705 -0.739 0.46
#> 78 12 9 -3 2.705 -1.109 0.267
#> 79 20 18 -2 2.705 -0.739 0.46
#> 80 6 8 2 2.705 0.739 0.46
#> 81 16 16 0 2.705 0.000 1
#> 82 8 12 4 2.705 1.479 0.139
#> 83 7 8 1 2.705 0.370 0.712
#> 84 16 15 -1 2.705 -0.370 0.712
#> 85 17 13 -4 2.705 -1.479 0.139
#> 86 5 6 1 2.705 0.370 0.712
#> 87 11 11 0 2.705 0.000 1
#> 88 17 15 -2 2.705 -0.739 0.46
#> 89 17 11 -6 2.705 -2.218 0.027
#> 90 12 8 -4 2.705 -1.479 0.139
#> 91 13 15 2 2.705 0.739 0.46
#> 92 13 14 1 2.705 0.370 0.712
#> 93 5 3 -2 2.705 -0.739 0.46
#> 94 13 13 0 2.705 0.000 1
#> 95 7 10 3 2.705 1.109 0.267
#> 96 8 10 2 2.705 0.739 0.46
#> 97 14 9 -5 2.705 -1.849 0.065
#> 98 8 6 -2 2.705 -0.739 0.46
#> 99 11 11 0 2.705 0.000 1
#> 100 5 5 0 2.705 0.000 1
#> 101 5 11 6 2.705 2.218 0.027
#> 102 5 0 -5 2.705 -1.849 0.065
#> 103 11 11 0 2.705 0.000 1
#> 104 16 19 3 2.705 1.109 0.267
#> 105 7 6 -1 2.705 -0.370 0.712
#> 106 4 6 2 2.705 0.739 0.46
#> 107 5 7 2 2.705 0.739 0.46
#> 108 9 11 2 2.705 0.739 0.46
#> 109 14 10 -4 2.705 -1.479 0.139
#> 110 6 5 -1 2.705 -0.370 0.712
#> 111 14 19 5 2.705 1.849 0.065
#> 112 11 10 -1 2.705 -0.370 0.712
#> 113 12 11 -1 2.705 -0.370 0.712
#> 114 4 2 -2 2.705 -0.739 0.46
#> 115 7 7 0 2.705 0.000 1
#> 116 17 15 -2 2.705 -0.739 0.46
#> 117 4 1 -3 2.705 -1.109 0.267
#> 118 12 14 2 2.705 0.739 0.46
#> 119 4 7 3 2.705 1.109 0.267
#> 120 14 13 -1 2.705 -0.370 0.712
#> 121 9 9 0 2.705 0.000 1
#> 122 15 18 3 2.705 1.109 0.267
#> 123 4 6 2 2.705 0.739 0.46
#> 124 13 16 3 2.705 1.109 0.267
#> 125 15 13 -2 2.705 -0.739 0.46
#> 126 10 5 -5 2.705 -1.849 0.065
#> 127 3 2 -1 2.705 -0.370 0.712
#> 128 15 13 -2 2.705 -0.739 0.46
#> 129 9 2 -7 2.705 -2.588 0.01
#> 130 12 13 1 2.705 0.370 0.712
#> 131 5 3 -2 2.705 -0.739 0.46
#> 132 5 6 1 2.705 0.370 0.712
#> 133 2 3 1 2.705 0.370 0.712
#> 134 15 13 -2 2.705 -0.739 0.46
#> 135 20 17 -3 2.705 -1.109 0.267
#> 136 14 13 -1 2.705 -0.370 0.712
#> 137 11 14 3 2.705 1.109 0.267
#> 138 17 14 -3 2.705 -1.109 0.267
#> 139 13 15 2 2.705 0.739 0.46
#> 140 12 11 -1 2.705 -0.370 0.712
#> 141 4 1 -3 2.705 -1.109 0.267
#> 142 16 20 4 2.705 1.479 0.139
#> 143 15 14 -1 2.705 -0.370 0.712
#> 144 5 6 1 2.705 0.370 0.712
#> 145 10 15 5 2.705 1.849 0.065
#> 146 16 16 0 2.705 0.000 1
#> 147 12 8 -4 2.705 -1.479 0.139
#> 148 8 13 5 2.705 1.849 0.065
#> 149 9 8 -1 2.705 -0.370 0.712
#> 150 17 15 -2 2.705 -0.739 0.46
#> 151 16 15 -1 2.705 -0.370 0.712
#> 152 14 11 -3 2.705 -1.109 0.267
#> 153 13 13 0 2.705 0.000 1
#> 154 6 6 0 2.705 0.000 1
#> 155 0 1 1 2.705 0.370 0.712
#> 156 7 2 -5 2.705 -1.849 0.065
#> 157 10 7 -3 2.705 -1.109 0.267
#> 158 11 18 7 2.705 2.588 0.01
#> 159 8 6 -2 2.705 -0.739 0.46
#> 160 8 8 0 2.705 0.000 1
#> 161 4 2 -2 2.705 -0.739 0.46
#> 162 4 4 0 2.705 0.000 1
#> 163 6 7 1 2.705 0.370 0.712
#> 164 15 15 0 2.705 0.000 1
#> 165 14 15 1 2.705 0.370 0.712
#> 166 18 16 -2 2.705 -0.739 0.46
#> 167 9 5 -4 2.705 -1.479 0.139
#> 168 12 10 -2 2.705 -0.739 0.46
#> 169 18 18 0 2.705 0.000 1
#> 170 9 5 -4 2.705 -1.479 0.139
#> 171 9 9 0 2.705 0.000 1
#> 172 2 1 -1 2.705 -0.370 0.712
#> 173 13 7 -6 2.705 -2.218 0.027
#> 174 9 9 0 2.705 0.000 1
#> 175 7 10 3 2.705 1.109 0.267
#> 176 18 12 -6 2.705 -2.218 0.027
#> 177 17 18 1 2.705 0.370 0.712
#> 178 5 2 -3 2.705 -1.109 0.267
#> 179 3 3 0 2.705 0.000 1
#> 180 0 2 2 2.705 0.739 0.46
#> 181 19 20 1 2.705 0.370 0.712
#> 182 16 12 -4 2.705 -1.479 0.139
#> 183 10 5 -5 2.705 -1.849 0.065
#> 184 10 15 5 2.705 1.849 0.065
#> 185 7 10 3 2.705 1.109 0.267
#> 186 16 17 1 2.705 0.370 0.712
#> 187 3 8 5 2.705 1.849 0.065
#> 188 16 19 3 2.705 1.109 0.267
#> 189 13 9 -4 2.705 -1.479 0.139
#> 190 7 8 1 2.705 0.370 0.712
#> 191 3 2 -1 2.705 -0.370 0.712
#> 192 10 8 -2 2.705 -0.739 0.46
#> 193 3 12 9 2.705 3.328 0.001
#> 194 11 11 0 2.705 0.000 1
#> 195 3 7 4 2.705 1.479 0.139
#> 196 6 7 1 2.705 0.370 0.712
#> 197 13 11 -2 2.705 -0.739 0.46
#> 198 17 17 0 2.705 0.000 1
#> 199 9 7 -2 2.705 -0.739 0.46
#> 200 16 18 2 2.705 0.739 0.46
#> 201 10 4 -6 2.705 -2.218 0.027
#> 202 9 9 0 2.705 0.000 1
#> 203 4 3 -1 2.705 -0.370 0.712
#> 204 6 2 -4 2.705 -1.479 0.139
#> 205 12 12 0 2.705 0.000 1
#> 206 5 4 -1 2.705 -0.370 0.712
#> 207 2 3 1 2.705 0.370 0.712
#> 208 15 19 4 2.705 1.479 0.139
#> 209 6 2 -4 2.705 -1.479 0.139
#> 210 16 18 2 2.705 0.739 0.46
#> 211 12 13 1 2.705 0.370 0.712
#> 212 2 3 1 2.705 0.370 0.712
#> 213 11 10 -1 2.705 -0.370 0.712
#> 214 12 13 1 2.705 0.370 0.712
#> 215 14 15 1 2.705 0.370 0.712
#> 216 19 19 0 2.705 0.000 1
#> 217 16 15 -1 2.705 -0.370 0.712
#> 218 19 20 1 2.705 0.370 0.712
#> 219 1 0 -1 2.705 -0.370 0.712
#> 220 13 12 -1 2.705 -0.370 0.712
#> 221 14 11 -3 2.705 -1.109 0.267
#> 222 19 16 -3 2.705 -1.109 0.267
#> 223 3 5 2 2.705 0.739 0.46
#> 224 2 1 -1 2.705 -0.370 0.712
#> 225 16 13 -3 2.705 -1.109 0.267
#> 226 12 11 -1 2.705 -0.370 0.712
#> 227 6 6 0 2.705 0.000 1
#> 228 5 8 3 2.705 1.109 0.267
#> 229 1 0 -1 2.705 -0.370 0.712
#> 230 12 13 1 2.705 0.370 0.712
#> 231 3 4 1 2.705 0.370 0.712
#> 232 10 7 -3 2.705 -1.109 0.267
#> 233 12 10 -2 2.705 -0.739 0.46
#> 234 14 16 2 2.705 0.739 0.46
#> 235 18 16 -2 2.705 -0.739 0.46
#> 236 10 10 0 2.705 0.000 1
#> 237 11 6 -5 2.705 -1.849 0.065
#> 238 14 19 5 2.705 1.849 0.065
#> 239 3 2 -1 2.705 -0.370 0.712
#> 240 8 4 -4 2.705 -1.479 0.139
#> 241 13 15 2 2.705 0.739 0.46
#> 242 12 13 1 2.705 0.370 0.712
#> 243 17 16 -1 2.705 -0.370 0.712
#> 244 9 7 -2 2.705 -0.739 0.46
#> 245 7 6 -1 2.705 -0.370 0.712
#> 246 10 8 -2 2.705 -0.739 0.46
#> 247 14 12 -2 2.705 -0.739 0.46
#> 248 11 11 0 2.705 0.000 1
#> 249 11 10 -1 2.705 -0.370 0.712
#> 250 18 19 1 2.705 0.370 0.712
#> 251 4 5 1 2.705 0.370 0.712
#> 252 1 3 2 2.705 0.739 0.46
#> 253 4 1 -3 2.705 -1.109 0.267
#> 254 8 10 2 2.705 0.739 0.46
#> 255 10 10 0 2.705 0.000 1
#> 256 17 18 1 2.705 0.370 0.712
#> 257 18 20 2 2.705 0.739 0.46
#> 258 11 10 -1 2.705 -0.370 0.712
#> 259 17 17 0 2.705 0.000 1
#> 260 12 13 1 2.705 0.370 0.712
#> 261 11 12 1 2.705 0.370 0.712
#> 262 9 11 2 2.705 0.739 0.46
#> 263 13 11 -2 2.705 -0.739 0.46
#> 264 17 16 -1 2.705 -0.370 0.712
#> 265 11 11 0 2.705 0.000 1
#> 266 19 18 -1 2.705 -0.370 0.712
#> 267 10 10 0 2.705 0.000 1
#> 268 5 9 4 2.705 1.479 0.139
#> 269 11 12 1 2.705 0.370 0.712
#> 270 17 14 -3 2.705 -1.109 0.267
#> 271 17 13 -4 2.705 -1.479 0.139
#> 272 20 19 -1 2.705 -0.370 0.712
#> 273 8 7 -1 2.705 -0.370 0.712
#> 274 16 19 3 2.705 1.109 0.267
#> 275 14 13 -1 2.705 -0.370 0.712
#> 276 4 8 4 2.705 1.479 0.139
#> 277 16 13 -3 2.705 -1.109 0.267
#> 278 11 11 0 2.705 0.000 1
#> 279 8 8 0 2.705 0.000 1
#> 280 2 4 2 2.705 0.739 0.46
#> 281 7 3 -4 2.705 -1.479 0.139
#> 282 5 10 5 2.705 1.849 0.065
#> 283 18 19 1 2.705 0.370 0.712
#> 284 10 14 4 2.705 1.479 0.139
#> 285 1 1 0 2.705 0.000 1
#> 286 5 10 5 2.705 1.849 0.065
#> 287 3 2 -1 2.705 -0.370 0.712
#> 288 7 13 6 2.705 2.218 0.027
#> 289 14 18 4 2.705 1.479 0.139
#> 290 17 17 0 2.705 0.000 1
#> 291 14 12 -2 2.705 -0.739 0.46
#> 292 16 11 -5 2.705 -1.849 0.065
#> 293 4 3 -1 2.705 -0.370 0.712
#> 294 19 17 -2 2.705 -0.739 0.46
#> 295 8 12 4 2.705 1.479 0.139
#> 296 17 15 -2 2.705 -0.739 0.46
#> 297 16 18 2 2.705 0.739 0.46
#> 298 18 17 -1 2.705 -0.370 0.712
#> 299 10 10 0 2.705 0.000 1
#> 300 16 15 -1 2.705 -0.370 0.712
#> 301 8 11 3 2.705 1.109 0.267
#> 302 3 2 -1 2.705 -0.370 0.712
#> 303 13 11 -2 2.705 -0.739 0.46
#> 304 8 5 -3 2.705 -1.109 0.267
#> 305 11 11 0 2.705 0.000 1
#> 306 17 17 0 2.705 0.000 1
#> 307 12 8 -4 2.705 -1.479 0.139
#> 308 18 18 0 2.705 0.000 1
#> 309 3 2 -1 2.705 -0.370 0.712
#> 310 9 11 2 2.705 0.739 0.46
#> 311 8 9 1 2.705 0.370 0.712
#> 312 8 2 -6 2.705 -2.218 0.027
#> 313 20 20 0 2.705 0.000 1
#> 314 9 9 0 2.705 0.000 1
#> 315 16 15 -1 2.705 -0.370 0.712
#> 316 15 11 -4 2.705 -1.479 0.139
#> 317 11 8 -3 2.705 -1.109 0.267
#> 318 4 9 5 2.705 1.849 0.065
#> 319 5 5 0 2.705 0.000 1
#> 320 18 19 1 2.705 0.370 0.712
#> 321 14 11 -3 2.705 -1.109 0.267
#> 322 6 6 0 2.705 0.000 1
#> 323 14 10 -4 2.705 -1.479 0.139
#> 324 9 8 -1 2.705 -0.370 0.712
#> 325 11 10 -1 2.705 -0.370 0.712
#> 326 12 8 -4 2.705 -1.479 0.139
#> 327 8 6 -2 2.705 -0.739 0.46
#> 328 10 8 -2 2.705 -0.739 0.46
#> 329 14 13 -1 2.705 -0.370 0.712
#> 330 14 11 -3 2.705 -1.109 0.267
#> 331 13 13 0 2.705 0.000 1
#> 332 2 1 -1 2.705 -0.370 0.712
#> 333 12 10 -2 2.705 -0.739 0.46
#> 334 16 16 0 2.705 0.000 1
#> 335 9 15 6 2.705 2.218 0.027
#> 336 3 7 4 2.705 1.479 0.139
#> 337 8 8 0 2.705 0.000 1
#> 338 13 14 1 2.705 0.370 0.712
#> 339 11 9 -2 2.705 -0.739 0.46
#> 340 14 13 -1 2.705 -0.370 0.712
#> 341 8 10 2 2.705 0.739 0.46
#> 342 13 15 2 2.705 0.739 0.46
#> 343 15 7 -8 2.705 -2.958 0.003
#> 344 14 12 -2 2.705 -0.739 0.46
#> 345 9 11 2 2.705 0.739 0.46
#> 346 14 14 0 2.705 0.000 1
#> 347 15 16 1 2.705 0.370 0.712
#> 348 9 12 3 2.705 1.109 0.267
#> 349 16 18 2 2.705 0.739 0.46
#> 350 14 10 -4 2.705 -1.479 0.139
#> 351 7 7 0 2.705 0.000 1
#> 352 12 14 2 2.705 0.739 0.46
#> 353 7 9 2 2.705 0.739 0.46
#> 354 11 7 -4 2.705 -1.479 0.139
#> 355 11 13 2 2.705 0.739 0.46
#> 356 14 12 -2 2.705 -0.739 0.46
#> 357 6 12 6 2.705 2.218 0.027
#> 358 7 5 -2 2.705 -0.739 0.46
#> 359 11 10 -1 2.705 -0.370 0.712
#> 360 9 8 -1 2.705 -0.370 0.712
#> 361 15 18 3 2.705 1.109 0.267
#> 362 5 6 1 2.705 0.370 0.712
#> 363 8 10 2 2.705 0.739 0.46
#> 364 16 17 1 2.705 0.370 0.712
#> 365 14 17 3 2.705 1.109 0.267
#> 366 11 13 2 2.705 0.739 0.46
#> 367 9 11 2 2.705 0.739 0.46
#> 368 1 4 3 2.705 1.109 0.267
#> 369 11 9 -2 2.705 -0.739 0.46
#> 370 9 4 -5 2.705 -1.849 0.065
#> 371 16 19 3 2.705 1.109 0.267
#> 372 6 8 2 2.705 0.739 0.46
#> 373 16 16 0 2.705 0.000 1
#> 374 7 9 2 2.705 0.739 0.46
#> 375 18 18 0 2.705 0.000 1
#> 376 6 4 -2 2.705 -0.739 0.46
#> 377 13 14 1 2.705 0.370 0.712
#> 378 12 10 -2 2.705 -0.739 0.46
#> 379 13 15 2 2.705 0.739 0.46
#> 380 18 16 -2 2.705 -0.739 0.46
#> 381 9 11 2 2.705 0.739 0.46
#> 382 10 10 0 2.705 0.000 1
#> 383 6 6 0 2.705 0.000 1
#> 384 8 9 1 2.705 0.370 0.712
#> 385 15 17 2 2.705 0.739 0.46
#> 386 15 16 1 2.705 0.370 0.712
#> 387 6 13 7 2.705 2.588 0.01
#> 388 4 2 -2 2.705 -0.739 0.46
#> 389 9 11 2 2.705 0.739 0.46
#> 390 9 9 0 2.705 0.000 1
#> 391 4 10 6 2.705 2.218 0.027
#> 392 9 8 -1 2.705 -0.370 0.712
#> 393 6 4 -2 2.705 -0.739 0.46
#> 394 5 5 0 2.705 0.000 1
#> 395 1 3 2 2.705 0.739 0.46
#> 396 13 13 0 2.705 0.000 1
#> 397 15 17 2 2.705 0.739 0.46
#> 398 6 7 1 2.705 0.370 0.712
#> 399 1 1 0 2.705 0.000 1
#> 400 16 17 1 2.705 0.370 0.712
#> 401 9 9 0 2.705 0.000 1
#> 402 3 4 1 2.705 0.370 0.712
#> 403 3 2 -1 2.705 -0.370 0.712
#> 404 10 10 0 2.705 0.000 1
#> 405 15 17 2 2.705 0.739 0.46
#> 406 17 13 -4 2.705 -1.479 0.139
#> 407 3 8 5 2.705 1.849 0.065
#> 408 10 14 4 2.705 1.479 0.139
#> 409 15 8 -7 2.705 -2.588 0.01
#> 410 12 10 -2 2.705 -0.739 0.46
#> 411 8 6 -2 2.705 -0.739 0.46
#> 412 9 9 0 2.705 0.000 1
#> 413 14 17 3 2.705 1.109 0.267
#> 414 3 2 -1 2.705 -0.370 0.712
#> 415 5 3 -2 2.705 -0.739 0.46
#> 416 9 9 0 2.705 0.000 1
#> 417 12 8 -4 2.705 -1.479 0.139
#> 418 16 12 -4 2.705 -1.479 0.139
#> 419 9 9 0 2.705 0.000 1
#> 420 5 5 0 2.705 0.000 1
#> 421 14 16 2 2.705 0.739 0.46
#> 422 5 3 -2 2.705 -0.739 0.46
#> 423 18 19 1 2.705 0.370 0.712
#> 424 10 10 0 2.705 0.000 1
#> 425 9 12 3 2.705 1.109 0.267
#> 426 15 16 1 2.705 0.370 0.712
#> 427 4 6 2 2.705 0.739 0.46
#> 428 11 8 -3 2.705 -1.109 0.267
#> 429 14 14 0 2.705 0.000 1
#> 430 5 6 1 2.705 0.370 0.712
#> 431 19 19 0 2.705 0.000 1
#> 432 13 12 -1 2.705 -0.370 0.712
#> 433 14 20 6 2.705 2.218 0.027
#> 434 12 15 3 2.705 1.109 0.267
#> 435 16 16 0 2.705 0.000 1
#> 436 11 12 1 2.705 0.370 0.712
#> 437 11 10 -1 2.705 -0.370 0.712
#> 438 10 11 1 2.705 0.370 0.712
#> 439 9 7 -2 2.705 -0.739 0.46
#> 440 18 15 -3 2.705 -1.109 0.267
#> 441 2 3 1 2.705 0.370 0.712
#> 442 4 5 1 2.705 0.370 0.712
#> 443 15 11 -4 2.705 -1.479 0.139
#> 444 2 4 2 2.705 0.739 0.46
#> 445 16 9 -7 2.705 -2.588 0.01
#> 446 4 5 1 2.705 0.370 0.712
#> 447 10 13 3 2.705 1.109 0.267
#> 448 15 14 -1 2.705 -0.370 0.712
#> 449 11 8 -3 2.705 -1.109 0.267
#> 450 16 18 2 2.705 0.739 0.46
#> 451 3 3 0 2.705 0.000 1
#> 452 10 10 0 2.705 0.000 1
#> 453 17 19 2 2.705 0.739 0.46
#> 454 18 18 0 2.705 0.000 1
#> 455 16 18 2 2.705 0.739 0.46
#> 456 2 3 1 2.705 0.370 0.712
#> 457 13 14 1 2.705 0.370 0.712
#> 458 6 11 5 2.705 1.849 0.065
#> 459 5 4 -1 2.705 -0.370 0.712
#> 460 20 18 -2 2.705 -0.739 0.46
#> 461 9 5 -4 2.705 -1.479 0.139
#> 462 11 13 2 2.705 0.739 0.46
#> 463 10 11 1 2.705 0.370 0.712
#> 464 15 19 4 2.705 1.479 0.139
#> 465 10 9 -1 2.705 -0.370 0.712
#> 466 9 3 -6 2.705 -2.218 0.027
#> 467 3 4 1 2.705 0.370 0.712
#> 468 3 2 -1 2.705 -0.370 0.712
#> 469 18 19 1 2.705 0.370 0.712
#> 470 17 13 -4 2.705 -1.479 0.139
#> 471 12 13 1 2.705 0.370 0.712
#> 472 11 15 4 2.705 1.479 0.139
#> 473 15 12 -3 2.705 -1.109 0.267
#> 474 8 8 0 2.705 0.000 1
#> 475 4 6 2 2.705 0.739 0.46
#> 476 18 16 -2 2.705 -0.739 0.46
#> 477 4 5 1 2.705 0.370 0.712
#> 478 2 3 1 2.705 0.370 0.712
#> 479 14 17 3 2.705 1.109 0.267
#> 480 9 5 -4 2.705 -1.479 0.139
#> 481 6 8 2 2.705 0.739 0.46
#> 482 20 20 0 2.705 0.000 1
#> 483 8 8 0 2.705 0.000 1
#> 484 2 3 1 2.705 0.370 0.712
#> 485 15 12 -3 2.705 -1.109 0.267
#> 486 15 16 1 2.705 0.370 0.712
#> 487 9 12 3 2.705 1.109 0.267
#> 488 8 6 -2 2.705 -0.739 0.46
#> 489 13 17 4 2.705 1.479 0.139
#> 490 12 9 -3 2.705 -1.109 0.267
#> 491 14 10 -4 2.705 -1.479 0.139
#> 492 19 18 -1 2.705 -0.370 0.712
#> 493 14 10 -4 2.705 -1.479 0.139
#> 494 11 6 -5 2.705 -1.849 0.065
#> 495 5 4 -1 2.705 -0.370 0.712
#> 496 12 12 0 2.705 0.000 1
#> 497 13 14 1 2.705 0.370 0.712
#> 498 19 18 -1 2.705 -0.370 0.712
#> 499 7 8 1 2.705 0.370 0.712
#> 500 20 20 0 2.705 0.000 1
#> 501 6 8 2 2.705 0.739 0.46
#> 502 17 18 1 2.705 0.370 0.712
#> 503 9 9 0 2.705 0.000 1
#> 504 12 13 1 2.705 0.370 0.712
#> 505 8 13 5 2.705 1.849 0.065
#> 506 9 11 2 2.705 0.739 0.46
#> 507 9 8 -1 2.705 -0.370 0.712
#> 508 6 5 -1 2.705 -0.370 0.712
#> 509 15 14 -1 2.705 -0.370 0.712
#> 510 15 12 -3 2.705 -1.109 0.267
#> 511 14 14 0 2.705 0.000 1
#> 512 1 0 -1 2.705 -0.370 0.712
#> 513 5 11 6 2.705 2.218 0.027
#> 514 5 4 -1 2.705 -0.370 0.712
#> 515 15 11 -4 2.705 -1.479 0.139
#> 516 19 18 -1 2.705 -0.370 0.712
#> 517 16 15 -1 2.705 -0.370 0.712
#> 518 6 6 0 2.705 0.000 1
#> 519 9 14 5 2.705 1.849 0.065
#> 520 11 5 -6 2.705 -2.218 0.027
#> 521 8 11 3 2.705 1.109 0.267
#> 522 3 4 1 2.705 0.370 0.712
#> 523 11 9 -2 2.705 -0.739 0.46
#> 524 16 13 -3 2.705 -1.109 0.267
#> 525 16 16 0 2.705 0.000 1
#> 526 14 13 -1 2.705 -0.370 0.712
#> 527 11 12 1 2.705 0.370 0.712
#> 528 17 16 -1 2.705 -0.370 0.712
#> 529 7 10 3 2.705 1.109 0.267
#> 530 11 11 0 2.705 0.000 1
#> 531 7 5 -2 2.705 -0.739 0.46
#> 532 12 17 5 2.705 1.849 0.065
#> 533 10 16 6 2.705 2.218 0.027
#> 534 15 14 -1 2.705 -0.370 0.712
#> 535 16 14 -2 2.705 -0.739 0.46
#> 536 8 15 7 2.705 2.588 0.01
#> 537 19 16 -3 2.705 -1.109 0.267
#> 538 14 14 0 2.705 0.000 1
#> 539 10 8 -2 2.705 -0.739 0.46
#> 540 11 9 -2 2.705 -0.739 0.46
#> 541 20 19 -1 2.705 -0.370 0.712
#> 542 17 18 1 2.705 0.370 0.712
#> 543 9 8 -1 2.705 -0.370 0.712
#> 544 18 20 2 2.705 0.739 0.46
#> 545 12 10 -2 2.705 -0.739 0.46
#> 546 10 14 4 2.705 1.479 0.139
#> 547 8 8 0 2.705 0.000 1
#> 548 10 11 1 2.705 0.370 0.712
#> 549 15 8 -7 2.705 -2.588 0.01
#> 550 5 4 -1 2.705 -0.370 0.712
#> 551 5 6 1 2.705 0.370 0.712
#> 552 6 7 1 2.705 0.370 0.712
#> 553 9 13 4 2.705 1.479 0.139
#> 554 8 5 -3 2.705 -1.109 0.267
#> 555 12 10 -2 2.705 -0.739 0.46
#> 556 15 15 0 2.705 0.000 1
#> 557 9 13 4 2.705 1.479 0.139
#> 558 11 14 3 2.705 1.109 0.267
#> 559 12 13 1 2.705 0.370 0.712
#> 560 4 5 1 2.705 0.370 0.712
#> 561 13 14 1 2.705 0.370 0.712
#> 562 11 13 2 2.705 0.739 0.46
#> 563 14 10 -4 2.705 -1.479 0.139
#> 564 1 4 3 2.705 1.109 0.267
#> 565 13 14 1 2.705 0.370 0.712
#> 566 15 14 -1 2.705 -0.370 0.712
#> 567 8 7 -1 2.705 -0.370 0.712
#> 568 15 16 1 2.705 0.370 0.712
#> 569 19 19 0 2.705 0.000 1
#> 570 13 11 -2 2.705 -0.739 0.46
#> 571 15 14 -1 2.705 -0.370 0.712
#> 572 5 6 1 2.705 0.370 0.712
#> 573 2 3 1 2.705 0.370 0.712
#> 574 19 14 -5 2.705 -1.849 0.065
#> 575 3 1 -2 2.705 -0.739 0.46
#> 576 17 18 1 2.705 0.370 0.712
#> 577 2 3 1 2.705 0.370 0.712
#> 578 19 17 -2 2.705 -0.739 0.46
#> 579 13 13 0 2.705 0.000 1
#> 580 20 15 -5 2.705 -1.849 0.065
#> 581 6 5 -1 2.705 -0.370 0.712
#> 582 17 18 1 2.705 0.370 0.712
#> 583 7 6 -1 2.705 -0.370 0.712
#> 584 6 4 -2 2.705 -0.739 0.46
#> 585 16 12 -4 2.705 -1.479 0.139
#> 586 13 13 0 2.705 0.000 1
#> 587 18 17 -1 2.705 -0.370 0.712
#> 588 9 7 -2 2.705 -0.739 0.46
#> 589 12 10 -2 2.705 -0.739 0.46
#> 590 12 14 2 2.705 0.739 0.46
#> 591 9 12 3 2.705 1.109 0.267
#> 592 12 16 4 2.705 1.479 0.139
#> 593 17 15 -2 2.705 -0.739 0.46
#> 594 4 3 -1 2.705 -0.370 0.712
#> 595 8 8 0 2.705 0.000 1
#> 596 11 9 -2 2.705 -0.739 0.46
#> 597 8 10 2 2.705 0.739 0.46
#> 598 10 12 2 2.705 0.739 0.46
#> 599 13 13 0 2.705 0.000 1
#> 600 12 16 4 2.705 1.479 0.139
#> 601 15 19 4 2.705 1.479 0.139
#> 602 11 9 -2 2.705 -0.739 0.46
#> 603 5 3 -2 2.705 -0.739 0.46
#> 604 7 9 2 2.705 0.739 0.46
#> 605 7 2 -5 2.705 -1.849 0.065
#> 606 2 6 4 2.705 1.479 0.139
#> 607 10 8 -2 2.705 -0.739 0.46
#> 608 14 14 0 2.705 0.000 1
#> 609 11 12 1 2.705 0.370 0.712
#> 610 12 7 -5 2.705 -1.849 0.065
#> 611 13 12 -1 2.705 -0.370 0.712
#> 612 10 9 -1 2.705 -0.370 0.712
#> 613 11 13 2 2.705 0.739 0.46
#> 614 5 6 1 2.705 0.370 0.712
#> 615 12 12 0 2.705 0.000 1
#> 616 4 1 -3 2.705 -1.109 0.267
#> 617 4 7 3 2.705 1.109 0.267
#> 618 5 5 0 2.705 0.000 1
#> 619 16 18 2 2.705 0.739 0.46
#> 620 4 6 2 2.705 0.739 0.46
#> 621 19 16 -3 2.705 -1.109 0.267
#> 622 13 12 -1 2.705 -0.370 0.712
#> 623 17 19 2 2.705 0.739 0.46
#> 624 8 5 -3 2.705 -1.109 0.267
#> 625 9 11 2 2.705 0.739 0.46
#> 626 5 4 -1 2.705 -0.370 0.712
#> 627 5 5 0 2.705 0.000 1
#> 628 4 1 -3 2.705 -1.109 0.267
#> 629 7 8 1 2.705 0.370 0.712
#> 630 8 13 5 2.705 1.849 0.065
#> 631 14 18 4 2.705 1.479 0.139
#> 632 8 3 -5 2.705 -1.849 0.065
#> 633 16 16 0 2.705 0.000 1
#> 634 13 14 1 2.705 0.370 0.712
#> 635 15 11 -4 2.705 -1.479 0.139
#> 636 13 9 -4 2.705 -1.479 0.139
#> 637 6 7 1 2.705 0.370 0.712
#> 638 12 7 -5 2.705 -1.849 0.065
#> 639 6 6 0 2.705 0.000 1
#> 640 3 2 -1 2.705 -0.370 0.712
#> 641 9 7 -2 2.705 -0.739 0.46
#> 642 7 7 0 2.705 0.000 1
#> 643 16 16 0 2.705 0.000 1
#> 644 13 13 0 2.705 0.000 1
#> 645 12 15 3 2.705 1.109 0.267
#> 646 2 3 1 2.705 0.370 0.712
#> 647 18 14 -4 2.705 -1.479 0.139
#> 648 5 7 2 2.705 0.739 0.46
#> 649 6 4 -2 2.705 -0.739 0.46
#> 650 19 18 -1 2.705 -0.370 0.712
#> 651 8 4 -4 2.705 -1.479 0.139
#> 652 10 12 2 2.705 0.739 0.46
#> 653 6 10 4 2.705 1.479 0.139
#> 654 4 5 1 2.705 0.370 0.712
#> 655 6 6 0 2.705 0.000 1
#> 656 7 5 -2 2.705 -0.739 0.46
#> 657 13 12 -1 2.705 -0.370 0.712
#> 658 10 13 3 2.705 1.109 0.267
#> 659 18 17 -1 2.705 -0.370 0.712
#> 660 11 8 -3 2.705 -1.109 0.267
#> 661 10 7 -3 2.705 -1.109 0.267
#> 662 19 18 -1 2.705 -0.370 0.712
#> 663 12 14 2 2.705 0.739 0.46
#> 664 17 19 2 2.705 0.739 0.46
#> 665 11 15 4 2.705 1.479 0.139
#> 666 13 13 0 2.705 0.000 1
#> 667 10 12 2 2.705 0.739 0.46
#> 668 11 12 1 2.705 0.370 0.712
#> 669 8 11 3 2.705 1.109 0.267
#> 670 8 5 -3 2.705 -1.109 0.267
#> 671 12 11 -1 2.705 -0.370 0.712
#> 672 10 10 0 2.705 0.000 1
#> 673 9 10 1 2.705 0.370 0.712
#> 674 12 15 3 2.705 1.109 0.267
#> 675 7 11 4 2.705 1.479 0.139
#> 676 4 2 -2 2.705 -0.739 0.46
#> 677 15 17 2 2.705 0.739 0.46
#> 678 9 6 -3 2.705 -1.109 0.267
#> 679 11 11 0 2.705 0.000 1
#> 680 17 16 -1 2.705 -0.370 0.712
#> 681 19 19 0 2.705 0.000 1
#> 682 9 10 1 2.705 0.370 0.712
#> 683 19 18 -1 2.705 -0.370 0.712
#> 684 5 1 -4 2.705 -1.479 0.139
#> 685 12 10 -2 2.705 -0.739 0.46
#> 686 16 13 -3 2.705 -1.109 0.267
#> 687 9 10 1 2.705 0.370 0.712
#> 688 7 6 -1 2.705 -0.370 0.712
#> 689 4 2 -2 2.705 -0.739 0.46
#> 690 14 15 1 2.705 0.370 0.712
#> 691 12 14 2 2.705 0.739 0.46
#> 692 4 8 4 2.705 1.479 0.139
#> 693 10 9 -1 2.705 -0.370 0.712
#> 694 13 9 -4 2.705 -1.479 0.139
#> 695 16 17 1 2.705 0.370 0.712
#> 696 14 13 -1 2.705 -0.370 0.712
#> 697 9 9 0 2.705 0.000 1
#> 698 3 5 2 2.705 0.739 0.46
#> 699 5 3 -2 2.705 -0.739 0.46
#> 700 10 13 3 2.705 1.109 0.267
#> 701 2 4 2 2.705 0.739 0.46
#> 702 14 11 -3 2.705 -1.109 0.267
#> 703 13 11 -2 2.705 -0.739 0.46
#> 704 12 13 1 2.705 0.370 0.712
#> 705 16 17 1 2.705 0.370 0.712
#> 706 15 17 2 2.705 0.739 0.46
#> 707 5 1 -4 2.705 -1.479 0.139
#> 708 13 13 0 2.705 0.000 1
#> 709 13 17 4 2.705 1.479 0.139
#> 710 8 6 -2 2.705 -0.739 0.46
#> 711 17 20 3 2.705 1.109 0.267
#> 712 8 6 -2 2.705 -0.739 0.46
#> 713 13 12 -1 2.705 -0.370 0.712
#> 714 3 5 2 2.705 0.739 0.46
#> 715 6 3 -3 2.705 -1.109 0.267
#> 716 15 16 1 2.705 0.370 0.712
#> 717 10 9 -1 2.705 -0.370 0.712
#> 718 9 12 3 2.705 1.109 0.267
#> 719 18 15 -3 2.705 -1.109 0.267
#> 720 5 6 1 2.705 0.370 0.712
#> 721 11 9 -2 2.705 -0.739 0.46
#> 722 7 7 0 2.705 0.000 1
#> 723 16 18 2 2.705 0.739 0.46
#> 724 6 13 7 2.705 2.588 0.01
#> 725 9 7 -2 2.705 -0.739 0.46
#> 726 4 4 0 2.705 0.000 1
#> 727 4 3 -1 2.705 -0.370 0.712
#> 728 9 10 1 2.705 0.370 0.712
#> 729 7 5 -2 2.705 -0.739 0.46
#> 730 9 10 1 2.705 0.370 0.712
#> 731 14 16 2 2.705 0.739 0.46
#> 732 2 4 2 2.705 0.739 0.46
#> 733 10 8 -2 2.705 -0.739 0.46
#> 734 17 12 -5 2.705 -1.849 0.065
#> 735 12 12 0 2.705 0.000 1
#> 736 11 10 -1 2.705 -0.370 0.712
#> 737 13 14 1 2.705 0.370 0.712
#> 738 12 13 1 2.705 0.370 0.712
#> 739 7 7 0 2.705 0.000 1
#> 740 9 8 -1 2.705 -0.370 0.712
#> 741 7 4 -3 2.705 -1.109 0.267
#> 742 8 7 -1 2.705 -0.370 0.712
#> 743 20 18 -2 2.705 -0.739 0.46
#> 744 12 10 -2 2.705 -0.739 0.46
#> 745 10 10 0 2.705 0.000 1
#> 746 18 19 1 2.705 0.370 0.712
#> 747 7 7 0 2.705 0.000 1
#> 748 16 17 1 2.705 0.370 0.712
#> 749 7 8 1 2.705 0.370 0.712
#> 750 20 18 -2 2.705 -0.739 0.46
#> 751 8 8 0 2.705 0.000 1
#> 752 8 10 2 2.705 0.739 0.46
#> 753 12 14 2 2.705 0.739 0.46
#> 754 15 17 2 2.705 0.739 0.46
#> 755 9 11 2 2.705 0.739 0.46
#> 756 10 8 -2 2.705 -0.739 0.46
#> 757 1 2 1 2.705 0.370 0.712
#> 758 4 6 2 2.705 0.739 0.46
#> 759 13 14 1 2.705 0.370 0.712
#> 760 15 17 2 2.705 0.739 0.46
#> 761 6 4 -2 2.705 -0.739 0.46
#> 762 17 11 -6 2.705 -2.218 0.027
#> 763 13 13 0 2.705 0.000 1
#> 764 13 15 2 2.705 0.739 0.46
#> 765 13 14 1 2.705 0.370 0.712
#> 766 13 13 0 2.705 0.000 1
#> 767 17 14 -3 2.705 -1.109 0.267
#> 768 2 2 0 2.705 0.000 1
#> 769 18 16 -2 2.705 -0.739 0.46
#> 770 19 20 1 2.705 0.370 0.712
#> 771 3 4 1 2.705 0.370 0.712
#> 772 17 11 -6 2.705 -2.218 0.027
#> 773 15 15 0 2.705 0.000 1
#> 774 13 14 1 2.705 0.370 0.712
#> 775 3 1 -2 2.705 -0.739 0.46
#> 776 18 16 -2 2.705 -0.739 0.46
#> 777 12 12 0 2.705 0.000 1
#> 778 12 14 2 2.705 0.739 0.46
#> 779 5 5 0 2.705 0.000 1
#> 780 9 8 -1 2.705 -0.370 0.712
#> 781 20 17 -3 2.705 -1.109 0.267
#> 782 12 8 -4 2.705 -1.479 0.139
#> 783 2 1 -1 2.705 -0.370 0.712
#> 784 7 6 -1 2.705 -0.370 0.712
#> 785 14 14 0 2.705 0.000 1
#> 786 12 10 -2 2.705 -0.739 0.46
#> 787 14 12 -2 2.705 -0.739 0.46
#> 788 13 14 1 2.705 0.370 0.712
#> 789 9 12 3 2.705 1.109 0.267
#> 790 11 7 -4 2.705 -1.479 0.139
#> 791 10 9 -1 2.705 -0.370 0.712
#> 792 14 14 0 2.705 0.000 1
#> 793 8 5 -3 2.705 -1.109 0.267
#> 794 19 18 -1 2.705 -0.370 0.712
#> 795 12 12 0 2.705 0.000 1
#> 796 13 15 2 2.705 0.739 0.46
#> 797 10 6 -4 2.705 -1.479 0.139
#> 798 7 4 -3 2.705 -1.109 0.267
#> 799 6 2 -4 2.705 -1.479 0.139
#> 800 4 8 4 2.705 1.479 0.139
#> 801 20 17 -3 2.705 -1.109 0.267
#> 802 5 6 1 2.705 0.370 0.712
#> 803 18 17 -1 2.705 -0.370 0.712
#> 804 11 13 2 2.705 0.739 0.46
#> 805 9 6 -3 2.705 -1.109 0.267
#> 806 6 4 -2 2.705 -0.739 0.46
#> 807 6 6 0 2.705 0.000 1
#> 808 9 10 1 2.705 0.370 0.712
#> 809 11 11 0 2.705 0.000 1
#> 810 4 7 3 2.705 1.109 0.267
#> 811 4 6 2 2.705 0.739 0.46
#> 812 11 12 1 2.705 0.370 0.712
#> 813 18 20 2 2.705 0.739 0.46
#> 814 6 7 1 2.705 0.370 0.712
#> 815 14 13 -1 2.705 -0.370 0.712
#> 816 11 12 1 2.705 0.370 0.712
#> 817 8 7 -1 2.705 -0.370 0.712
#> 818 16 19 3 2.705 1.109 0.267
#> 819 5 3 -2 2.705 -0.739 0.46
#> 820 17 13 -4 2.705 -1.479 0.139
#> 821 11 14 3 2.705 1.109 0.267
#> 822 10 10 0 2.705 0.000 1
#> 823 10 16 6 2.705 2.218 0.027
#> 824 11 12 1 2.705 0.370 0.712
#> 825 8 13 5 2.705 1.849 0.065
#> 826 13 15 2 2.705 0.739 0.46
#> 827 14 10 -4 2.705 -1.479 0.139
#> 828 14 13 -1 2.705 -0.370 0.712
#> 829 7 13 6 2.705 2.218 0.027
#> 830 10 11 1 2.705 0.370 0.712
#> 831 6 6 0 2.705 0.000 1
#> 832 5 6 1 2.705 0.370 0.712
#> 833 15 16 1 2.705 0.370 0.712
#> 834 5 9 4 2.705 1.479 0.139
#> 835 10 3 -7 2.705 -2.588 0.01
#> 836 14 15 1 2.705 0.370 0.712
#> 837 2 6 4 2.705 1.479 0.139
#> 838 1 0 -1 2.705 -0.370 0.712
#> 839 19 19 0 2.705 0.000 1
#> 840 7 7 0 2.705 0.000 1
#> 841 16 14 -2 2.705 -0.739 0.46
#> 842 18 17 -1 2.705 -0.370 0.712
#> 843 18 17 -1 2.705 -0.370 0.712
#> 844 11 10 -1 2.705 -0.370 0.712
#> 845 16 15 -1 2.705 -0.370 0.712
#> 846 10 11 1 2.705 0.370 0.712
#> 847 15 16 1 2.705 0.370 0.712
#> 848 15 11 -4 2.705 -1.479 0.139
#> 849 18 15 -3 2.705 -1.109 0.267
#> 850 13 15 2 2.705 0.739 0.46
#> 851 16 17 1 2.705 0.370 0.712
#> 852 13 16 3 2.705 1.109 0.267
#> 853 6 9 3 2.705 1.109 0.267
#> 854 14 16 2 2.705 0.739 0.46
#> 855 12 11 -1 2.705 -0.370 0.712
#> 856 5 6 1 2.705 0.370 0.712
#> 857 6 7 1 2.705 0.370 0.712
#> 858 7 13 6 2.705 2.218 0.027
#> 859 18 18 0 2.705 0.000 1
#> 860 11 13 2 2.705 0.739 0.46
#> 861 11 10 -1 2.705 -0.370 0.712
#> 862 9 6 -3 2.705 -1.109 0.267
#> 863 8 7 -1 2.705 -0.370 0.712
#> 864 9 7 -2 2.705 -0.739 0.46
#> 865 15 13 -2 2.705 -0.739 0.46
#> 866 12 9 -3 2.705 -1.109 0.267
#> 867 10 12 2 2.705 0.739 0.46
#> 868 17 12 -5 2.705 -1.849 0.065
#> 869 6 8 2 2.705 0.739 0.46
#> 870 4 4 0 2.705 0.000 1
#> 871 16 15 -1 2.705 -0.370 0.712
#> 872 7 3 -4 2.705 -1.479 0.139
#> 873 4 7 3 2.705 1.109 0.267
#> 874 12 12 0 2.705 0.000 1
#> 875 14 12 -2 2.705 -0.739 0.46
#> 876 17 13 -4 2.705 -1.479 0.139
#> 877 12 11 -1 2.705 -0.370 0.712
#> 878 6 6 0 2.705 0.000 1
#> 879 8 13 5 2.705 1.849 0.065
#> 880 15 17 2 2.705 0.739 0.46
#> 881 7 10 3 2.705 1.109 0.267
#> 882 2 1 -1 2.705 -0.370 0.712
#> 883 13 18 5 2.705 1.849 0.065
#> 884 17 18 1 2.705 0.370 0.712
#> 885 8 10 2 2.705 0.739 0.46
#> 886 18 19 1 2.705 0.370 0.712
#> 887 17 16 -1 2.705 -0.370 0.712
#> 888 14 11 -3 2.705 -1.109 0.267
#> 889 6 6 0 2.705 0.000 1
#> 890 4 3 -1 2.705 -0.370 0.712
#> 891 12 10 -2 2.705 -0.739 0.46
#> 892 11 12 1 2.705 0.370 0.712
#> 893 5 7 2 2.705 0.739 0.46
#> 894 15 17 2 2.705 0.739 0.46
#> 895 6 11 5 2.705 1.849 0.065
#> 896 11 7 -4 2.705 -1.479 0.139
#> 897 11 13 2 2.705 0.739 0.46
#> 898 6 5 -1 2.705 -0.370 0.712
#> 899 13 11 -2 2.705 -0.739 0.46
#> 900 5 9 4 2.705 1.479 0.139
#> 901 10 10 0 2.705 0.000 1
#> 902 17 18 1 2.705 0.370 0.712
#> 903 15 14 -1 2.705 -0.370 0.712
#> 904 8 11 3 2.705 1.109 0.267
#> 905 17 16 -1 2.705 -0.370 0.712
#> 906 14 17 3 2.705 1.109 0.267
#> 907 9 10 1 2.705 0.370 0.712
#> 908 13 8 -5 2.705 -1.849 0.065
#> 909 7 5 -2 2.705 -0.739 0.46
#> 910 8 6 -2 2.705 -0.739 0.46
#> 911 18 19 1 2.705 0.370 0.712
#> 912 15 17 2 2.705 0.739 0.46
#> 913 11 12 1 2.705 0.370 0.712
#> 914 10 10 0 2.705 0.000 1
#> 915 18 19 1 2.705 0.370 0.712
#> 916 18 16 -2 2.705 -0.739 0.46
#> 917 10 10 0 2.705 0.000 1
#> 918 2 1 -1 2.705 -0.370 0.712
#> 919 16 17 1 2.705 0.370 0.712
#> 920 2 1 -1 2.705 -0.370 0.712
#> 921 20 20 0 2.705 0.000 1
#> 922 6 2 -4 2.705 -1.479 0.139
#> 923 18 17 -1 2.705 -0.370 0.712
#> 924 13 19 6 2.705 2.218 0.027
#> 925 14 11 -3 2.705 -1.109 0.267
#> 926 18 17 -1 2.705 -0.370 0.712
#> 927 16 15 -1 2.705 -0.370 0.712
#> 928 18 11 -7 2.705 -2.588 0.01
#> 929 15 12 -3 2.705 -1.109 0.267
#> 930 9 5 -4 2.705 -1.479 0.139
#> 931 9 9 0 2.705 0.000 1
#> 932 10 10 0 2.705 0.000 1
#> 933 16 18 2 2.705 0.739 0.46
#> 934 5 7 2 2.705 0.739 0.46
#> 935 16 17 1 2.705 0.370 0.712
#> 936 8 10 2 2.705 0.739 0.46
#> 937 5 4 -1 2.705 -0.370 0.712
#> 938 16 15 -1 2.705 -0.370 0.712
#> 939 13 10 -3 2.705 -1.109 0.267
#> 940 10 13 3 2.705 1.109 0.267
#> 941 14 14 0 2.705 0.000 1
#> 942 10 14 4 2.705 1.479 0.139
#> 943 4 3 -1 2.705 -0.370 0.712
#> 944 20 18 -2 2.705 -0.739 0.46
#> 945 6 8 2 2.705 0.739 0.46
#> 946 8 5 -3 2.705 -1.109 0.267
#> 947 7 17 10 2.705 3.697 0
#> 948 7 3 -4 2.705 -1.479 0.139
#> 949 14 14 0 2.705 0.000 1
#> 950 14 13 -1 2.705 -0.370 0.712
#> 951 14 13 -1 2.705 -0.370 0.712
#> 952 14 10 -4 2.705 -1.479 0.139
#> 953 12 9 -3 2.705 -1.109 0.267
#> 954 8 8 0 2.705 0.000 1
#> 955 14 11 -3 2.705 -1.109 0.267
#> 956 10 12 2 2.705 0.739 0.46
#> 957 11 9 -2 2.705 -0.739 0.46
#> 958 4 4 0 2.705 0.000 1
#> 959 9 10 1 2.705 0.370 0.712
#> 960 5 7 2 2.705 0.739 0.46
#> 961 16 13 -3 2.705 -1.109 0.267
#> 962 7 5 -2 2.705 -0.739 0.46
#> 963 6 7 1 2.705 0.370 0.712
#> 964 5 6 1 2.705 0.370 0.712
#> 965 5 2 -3 2.705 -1.109 0.267
#> 966 2 5 3 2.705 1.109 0.267
#> 967 7 6 -1 2.705 -0.370 0.712
#> 968 16 19 3 2.705 1.109 0.267
#> 969 8 4 -4 2.705 -1.479 0.139
#> 970 4 1 -3 2.705 -1.109 0.267
#> 971 12 10 -2 2.705 -0.739 0.46
#> 972 3 9 6 2.705 2.218 0.027
#> 973 14 16 2 2.705 0.739 0.46
#> 974 7 5 -2 2.705 -0.739 0.46
#> 975 16 16 0 2.705 0.000 1
#> 976 15 16 1 2.705 0.370 0.712
#> 977 11 14 3 2.705 1.109 0.267
#> 978 14 13 -1 2.705 -0.370 0.712
#> 979 17 18 1 2.705 0.370 0.712
#> 980 10 10 0 2.705 0.000 1
#> 981 17 18 1 2.705 0.370 0.712
#> 982 3 2 -1 2.705 -0.370 0.712
#> 983 6 7 1 2.705 0.370 0.712
#> 984 4 3 -1 2.705 -0.370 0.712
#> 985 14 16 2 2.705 0.739 0.46
#> 986 11 11 0 2.705 0.000 1
#> 987 5 3 -2 2.705 -0.739 0.46
#> 988 1 2 1 2.705 0.370 0.712
#> 989 10 11 1 2.705 0.370 0.712
#> 990 4 2 -2 2.705 -0.739 0.46
#> 991 5 4 -1 2.705 -0.370 0.712
#> 992 12 14 2 2.705 0.739 0.46
#> 993 20 14 -6 2.705 -2.218 0.027
#> 994 15 12 -3 2.705 -1.109 0.267
#> 995 8 14 6 2.705 2.218 0.027
#> 996 18 17 -1 2.705 -0.370 0.712
#> 997 9 13 4 2.705 1.479 0.139
#> 998 12 9 -3 2.705 -1.109 0.267
#> 999 9 6 -3 2.705 -1.109 0.267
#> 1000 10 8 -2 2.705 -0.739 0.46
######
# interactive shiny interfaces for live scoring
mod_pre <- mirt(Science)
#>
Iteration: 1, Log-Lik: -1629.361, Max-Change: 0.50660
Iteration: 2, Log-Lik: -1617.374, Max-Change: 0.25442
Iteration: 3, Log-Lik: -1612.894, Max-Change: 0.16991
Iteration: 4, Log-Lik: -1610.306, Max-Change: 0.10461
Iteration: 5, Log-Lik: -1609.814, Max-Change: 0.09162
Iteration: 6, Log-Lik: -1609.534, Max-Change: 0.07363
Iteration: 7, Log-Lik: -1609.030, Max-Change: 0.03677
Iteration: 8, Log-Lik: -1608.988, Max-Change: 0.03200
Iteration: 9, Log-Lik: -1608.958, Max-Change: 0.02754
Iteration: 10, Log-Lik: -1608.878, Max-Change: 0.01443
Iteration: 11, Log-Lik: -1608.875, Max-Change: 0.00847
Iteration: 12, Log-Lik: -1608.873, Max-Change: 0.00515
Iteration: 13, Log-Lik: -1608.872, Max-Change: 0.00550
Iteration: 14, Log-Lik: -1608.872, Max-Change: 0.00318
Iteration: 15, Log-Lik: -1608.871, Max-Change: 0.00462
Iteration: 16, Log-Lik: -1608.871, Max-Change: 0.00277
Iteration: 17, Log-Lik: -1608.870, Max-Change: 0.00145
Iteration: 18, Log-Lik: -1608.870, Max-Change: 0.00175
Iteration: 19, Log-Lik: -1608.870, Max-Change: 0.00126
Iteration: 20, Log-Lik: -1608.870, Max-Change: 0.00025
Iteration: 21, Log-Lik: -1608.870, Max-Change: 0.00285
Iteration: 22, Log-Lik: -1608.870, Max-Change: 0.00108
Iteration: 23, Log-Lik: -1608.870, Max-Change: 0.00022
Iteration: 24, Log-Lik: -1608.870, Max-Change: 0.00059
Iteration: 25, Log-Lik: -1608.870, Max-Change: 0.00014
Iteration: 26, Log-Lik: -1608.870, Max-Change: 0.00068
Iteration: 27, Log-Lik: -1608.870, Max-Change: 0.00065
Iteration: 28, Log-Lik: -1608.870, Max-Change: 0.00019
Iteration: 29, Log-Lik: -1608.870, Max-Change: 0.00061
Iteration: 30, Log-Lik: -1608.870, Max-Change: 0.00012
Iteration: 31, Log-Lik: -1608.870, Max-Change: 0.00012
Iteration: 32, Log-Lik: -1608.870, Max-Change: 0.00058
Iteration: 33, Log-Lik: -1608.870, Max-Change: 0.00055
Iteration: 34, Log-Lik: -1608.870, Max-Change: 0.00015
Iteration: 35, Log-Lik: -1608.870, Max-Change: 0.00052
Iteration: 36, Log-Lik: -1608.870, Max-Change: 0.00010
# (optional) setup mod_post to have medium effect size change (d = 0.5)
sv <- mod2values(mod_pre)
sv$value[sv$name == 'MEAN_1'] <- 0.5
mod_post <- mirt(Science, pars=sv, TOL=NA)
# only use pre-test model for scoring
if(interactive()){
RCI(mod_pre=mod_pre, shiny=TRUE)
# use both pre-test and post-test models for including empirical priors
RCI(mod_pre=mod_pre, mod_post=mod_post, shiny=TRUE,
main='Perceptions of Science and Technology')
}
############################
# Example where individuals take completely different item set pre-post
# but prior calibration has been performed to equate the items
dat <- key2binary(SAT12,
key = c(1,4,5,2,3,1,2,1,3,1,2,4,2,1,5,3,4,4,1,4,3,3,4,1,3,5,1,3,1,5,4,5))
mod <- mirt(dat)
#>
Iteration: 1, Log-Lik: -9647.510, Max-Change: 0.81958
Iteration: 2, Log-Lik: -9501.953, Max-Change: 0.61213
Iteration: 3, Log-Lik: -9491.324, Max-Change: 0.30029
Iteration: 4, Log-Lik: -9489.773, Max-Change: 0.17556
Iteration: 5, Log-Lik: -9489.311, Max-Change: 0.05283
Iteration: 6, Log-Lik: -9489.122, Max-Change: 0.03138
Iteration: 7, Log-Lik: -9489.045, Max-Change: 0.01853
Iteration: 8, Log-Lik: -9489.000, Max-Change: 0.01225
Iteration: 9, Log-Lik: -9488.978, Max-Change: 0.00708
Iteration: 10, Log-Lik: -9488.964, Max-Change: 0.00300
Iteration: 11, Log-Lik: -9488.961, Max-Change: 0.00284
Iteration: 12, Log-Lik: -9488.959, Max-Change: 0.00186
Iteration: 13, Log-Lik: -9488.958, Max-Change: 0.00149
Iteration: 14, Log-Lik: -9488.957, Max-Change: 0.00118
Iteration: 15, Log-Lik: -9488.956, Max-Change: 0.00173
Iteration: 16, Log-Lik: -9488.956, Max-Change: 0.00086
Iteration: 17, Log-Lik: -9488.955, Max-Change: 0.00026
Iteration: 18, Log-Lik: -9488.955, Max-Change: 0.00020
Iteration: 19, Log-Lik: -9488.955, Max-Change: 0.00017
Iteration: 20, Log-Lik: -9488.955, Max-Change: 0.00015
Iteration: 21, Log-Lik: -9488.955, Max-Change: 0.00014
Iteration: 22, Log-Lik: -9488.955, Max-Change: 0.00045
Iteration: 23, Log-Lik: -9488.955, Max-Change: 0.00004
# with N=5 individuals under investigation
predat <- postdat <- dat[1:5,]
predat[, 17:32] <- NA
postdat[, 1:16] <- NA
head(predat)
#> Item.1 Item.2 Item.3 Item.4 Item.5 Item.6 Item.7 Item.8 Item.9 Item.10
#> [1,] 1 1 1 1 1 1 1 1 1 1
#> [2,] 0 1 0 0 1 0 1 0 1 1
#> [3,] 1 1 1 0 1 0 1 0 1 0
#> [4,] 0 1 0 1 1 0 1 0 1 0
#> [5,] 0 1 1 1 1 0 1 1 0 0
#> Item.11 Item.12 Item.13 Item.14 Item.15 Item.16 Item.17 Item.18 Item.19
#> [1,] 1 1 1 1 1 1 NA NA NA
#> [2,] 1 0 1 1 1 0 NA NA NA
#> [3,] 1 0 0 1 1 0 NA NA NA
#> [4,] 1 1 1 1 1 0 NA NA NA
#> [5,] 1 1 1 1 1 0 NA NA NA
#> Item.20 Item.21 Item.22 Item.23 Item.24 Item.25 Item.26 Item.27 Item.28
#> [1,] NA NA NA NA NA NA NA NA NA
#> [2,] NA NA NA NA NA NA NA NA NA
#> [3,] NA NA NA NA NA NA NA NA NA
#> [4,] NA NA NA NA NA NA NA NA NA
#> [5,] NA NA NA NA NA NA NA NA NA
#> Item.29 Item.30 Item.31 Item.32
#> [1,] NA NA NA NA
#> [2,] NA NA NA NA
#> [3,] NA NA NA NA
#> [4,] NA NA NA NA
#> [5,] NA NA NA NA
head(postdat)
#> Item.1 Item.2 Item.3 Item.4 Item.5 Item.6 Item.7 Item.8 Item.9 Item.10
#> [1,] NA NA NA NA NA NA NA NA NA NA
#> [2,] NA NA NA NA NA NA NA NA NA NA
#> [3,] NA NA NA NA NA NA NA NA NA NA
#> [4,] NA NA NA NA NA NA NA NA NA NA
#> [5,] NA NA NA NA NA NA NA NA NA NA
#> Item.11 Item.12 Item.13 Item.14 Item.15 Item.16 Item.17 Item.18 Item.19
#> [1,] NA NA NA NA NA NA 1 1 1
#> [2,] NA NA NA NA NA NA 1 0 1
#> [3,] NA NA NA NA NA NA 1 0 0
#> [4,] NA NA NA NA NA NA 1 0 0
#> [5,] NA NA NA NA NA NA 1 0 1
#> Item.20 Item.21 Item.22 Item.23 Item.24 Item.25 Item.26 Item.27 Item.28
#> [1,] 1 1 1 1 1 1 1 1 1
#> [2,] 1 1 1 0 1 0 0 1 0
#> [3,] 1 1 1 0 1 1 0 1 1
#> [4,] 1 1 0 0 0 0 0 1 1
#> [5,] 1 1 1 0 1 0 1 1 1
#> Item.29 Item.30 Item.31 Item.32
#> [1,] 1 1 1 1
#> [2,] 0 0 1 0
#> [3,] 0 0 1 0
#> [4,] 0 0 1 0
#> [5,] 1 0 1 0
RCI(mod, predat, postdat)
#> pre.score post.score converged diff SE z p
#> 1 2.206 1.808 TRUE -0.398 0.951 -0.419 0.675
#> 2 0.373 -0.344 TRUE -0.717 0.720 -0.995 0.32
#> 3 0.303 -0.115 TRUE -0.419 0.728 -0.575 0.566
#> 4 0.295 -0.864 TRUE -1.159 0.699 -1.658 0.097
#> 5 0.670 0.513 TRUE -0.157 0.772 -0.203 0.839
######
# Two-dimensional IRT model for each time point, 20 items (no DIF)
J <- 20
N <- 500
slopes <- rlnorm(J, .2, .2)
a <- matrix(c(slopes, numeric(J*2), slopes),J*2)
ints <- rnorm(J)
d <- matrix(c(ints, ints), ncol=1)
data.frame(a=a, d=d)
#> a.1 a.2 d
#> 1 1.2554861 0.0000000 -0.12846703
#> 2 1.0857174 0.0000000 1.18697902
#> 3 0.8334051 0.0000000 -0.15585153
#> 4 1.2310383 0.0000000 0.27722946
#> 5 1.2082373 0.0000000 0.40603314
#> 6 1.1097763 0.0000000 0.56435149
#> 7 1.1896749 0.0000000 0.26112625
#> 8 1.2362598 0.0000000 -1.00007777
#> 9 0.8527464 0.0000000 -0.40224190
#> 10 1.1552393 0.0000000 -0.63265649
#> 11 0.7725387 0.0000000 -0.23498495
#> 12 1.1911807 0.0000000 -0.23365145
#> 13 1.5201541 0.0000000 -0.09858223
#> 14 1.1752077 0.0000000 0.83519448
#> 15 1.0858223 0.0000000 -0.43051228
#> 16 1.6628731 0.0000000 0.41443651
#> 17 1.1012075 0.0000000 1.41245283
#> 18 1.0354140 0.0000000 0.84976955
#> 19 1.3580607 0.0000000 0.17070288
#> 20 0.9164153 0.0000000 -0.24230045
#> 21 0.0000000 1.2554861 -0.12846703
#> 22 0.0000000 1.0857174 1.18697902
#> 23 0.0000000 0.8334051 -0.15585153
#> 24 0.0000000 1.2310383 0.27722946
#> 25 0.0000000 1.2082373 0.40603314
#> 26 0.0000000 1.1097763 0.56435149
#> 27 0.0000000 1.1896749 0.26112625
#> 28 0.0000000 1.2362598 -1.00007777
#> 29 0.0000000 0.8527464 -0.40224190
#> 30 0.0000000 1.1552393 -0.63265649
#> 31 0.0000000 0.7725387 -0.23498495
#> 32 0.0000000 1.1911807 -0.23365145
#> 33 0.0000000 1.5201541 -0.09858223
#> 34 0.0000000 1.1752077 0.83519448
#> 35 0.0000000 1.0858223 -0.43051228
#> 36 0.0000000 1.6628731 0.41443651
#> 37 0.0000000 1.1012075 1.41245283
#> 38 0.0000000 1.0354140 0.84976955
#> 39 0.0000000 1.3580607 0.17070288
#> 40 0.0000000 0.9164153 -0.24230045
# mean effects across time
mu <- c(0, -1/2)
sigma <- matrix(c(1, .7, .7, 1), 2,2)
dat <- simdata(a, d, N, mu=mu, sigma=sigma, itemtype = '2PL')
# build equality constraints across time points
constr <- NULL
for(i in (1:J)){
constr <- c(constr, paste0("(", i, ',', i+J, ",a1,a2)"))
constr <- c(constr, paste0("(", i, ',', i+J, ",d)"))
}
constr <- paste0(constr, collapse=',')
# define model where item parameters constrained over time, and
# latent trait has potential scale-location changes (e.g., regression to the
# mean effects)
model <- sprintf("
thetapre = 1-%i,
thetapost = %i-%i,
COV = thetapre*thetapost, thetapost*thetapost
MEAN = thetapost
CONSTRAIN = %s", J, J+1, 2*J, constr)
cat(model)
#>
#> thetapre = 1-20,
#> thetapost = 21-40,
#> COV = thetapre*thetapost, thetapost*thetapost
#> MEAN = thetapost
#> CONSTRAIN = (1,21,a1,a2),(1,21,d),(2,22,a1,a2),(2,22,d),(3,23,a1,a2),(3,23,d),(4,24,a1,a2),(4,24,d),(5,25,a1,a2),(5,25,d),(6,26,a1,a2),(6,26,d),(7,27,a1,a2),(7,27,d),(8,28,a1,a2),(8,28,d),(9,29,a1,a2),(9,29,d),(10,30,a1,a2),(10,30,d),(11,31,a1,a2),(11,31,d),(12,32,a1,a2),(12,32,d),(13,33,a1,a2),(13,33,d),(14,34,a1,a2),(14,34,d),(15,35,a1,a2),(15,35,d),(16,36,a1,a2),(16,36,d),(17,37,a1,a2),(17,37,d),(18,38,a1,a2),(18,38,d),(19,39,a1,a2),(19,39,d),(20,40,a1,a2),(20,40,d)
# fit the model to calibration data
mod <- mirt(dat, model = model, SE=TRUE)
#>
Iteration: 1, Log-Lik: -11949.167, Max-Change: 0.50780
Iteration: 2, Log-Lik: -11801.923, Max-Change: 0.19294
Iteration: 3, Log-Lik: -11780.996, Max-Change: 0.08437
Iteration: 4, Log-Lik: -11773.517, Max-Change: 0.04518
Iteration: 5, Log-Lik: -11769.089, Max-Change: 0.03736
Iteration: 6, Log-Lik: -11765.989, Max-Change: 0.03369
Iteration: 7, Log-Lik: -11759.064, Max-Change: 0.07225
Iteration: 8, Log-Lik: -11757.431, Max-Change: 0.03093
Iteration: 9, Log-Lik: -11756.875, Max-Change: 0.01639
Iteration: 10, Log-Lik: -11756.414, Max-Change: 0.01175
Iteration: 11, Log-Lik: -11756.223, Max-Change: 0.00866
Iteration: 12, Log-Lik: -11756.085, Max-Change: 0.00793
Iteration: 13, Log-Lik: -11755.737, Max-Change: 0.01193
Iteration: 14, Log-Lik: -11755.669, Max-Change: 0.00576
Iteration: 15, Log-Lik: -11755.641, Max-Change: 0.00321
Iteration: 16, Log-Lik: -11755.608, Max-Change: 0.00254
Iteration: 17, Log-Lik: -11755.598, Max-Change: 0.00203
Iteration: 18, Log-Lik: -11755.591, Max-Change: 0.00187
Iteration: 19, Log-Lik: -11755.572, Max-Change: 0.00216
Iteration: 20, Log-Lik: -11755.569, Max-Change: 0.00105
Iteration: 21, Log-Lik: -11755.567, Max-Change: 0.00071
Iteration: 22, Log-Lik: -11755.565, Max-Change: 0.00049
Iteration: 23, Log-Lik: -11755.564, Max-Change: 0.00044
Iteration: 24, Log-Lik: -11755.564, Max-Change: 0.00041
Iteration: 25, Log-Lik: -11755.563, Max-Change: 0.00031
Iteration: 26, Log-Lik: -11755.563, Max-Change: 0.00017
Iteration: 27, Log-Lik: -11755.563, Max-Change: 0.00017
Iteration: 28, Log-Lik: -11755.563, Max-Change: 0.00015
Iteration: 29, Log-Lik: -11755.563, Max-Change: 0.00007
#>
#> Calculating information matrix...
coef(mod, printSE=TRUE)
#> $Item_1
#> a1 a2 d logit(g) logit(u)
#> par 1.221 0 -0.220 -999 999
#> SE 0.113 NA 0.094 NA NA
#>
#> $Item_2
#> a1 a2 d logit(g) logit(u)
#> par 1.046 0 1.161 -999 999
#> SE 0.105 NA 0.104 NA NA
#>
#> $Item_3
#> a1 a2 d logit(g) logit(u)
#> par 0.978 0 -0.112 -999 999
#> SE 0.098 NA 0.085 NA NA
#>
#> $Item_4
#> a1 a2 d logit(g) logit(u)
#> par 1.304 0 0.293 -999 999
#> SE 0.117 NA 0.099 NA NA
#>
#> $Item_5
#> a1 a2 d logit(g) logit(u)
#> par 1.173 0 0.402 -999 999
#> SE 0.109 NA 0.095 NA NA
#>
#> $Item_6
#> a1 a2 d logit(g) logit(u)
#> par 1.187 0 0.490 -999 999
#> SE 0.109 NA 0.097 NA NA
#>
#> $Item_7
#> a1 a2 d logit(g) logit(u)
#> par 1.122 0 0.218 -999 999
#> SE 0.105 NA 0.092 NA NA
#>
#> $Item_8
#> a1 a2 d logit(g) logit(u)
#> par 1.041 0 -0.930 -999 999
#> SE 0.108 NA 0.093 NA NA
#>
#> $Item_9
#> a1 a2 d logit(g) logit(u)
#> par 0.765 0 -0.441 -999 999
#> SE 0.088 NA 0.079 NA NA
#>
#> $Item_10
#> a1 a2 d logit(g) logit(u)
#> par 1.253 0 -0.666 -999 999
#> SE 0.119 NA 0.098 NA NA
#>
#> $Item_11
#> a1 a2 d logit(g) logit(u)
#> par 0.813 0 -0.276 -999 999
#> SE 0.089 NA 0.080 NA NA
#>
#> $Item_12
#> a1 a2 d logit(g) logit(u)
#> par 1.127 0 -0.086 -999 999
#> SE 0.107 NA 0.091 NA NA
#>
#> $Item_13
#> a1 a2 d logit(g) logit(u)
#> par 1.450 0 -0.097 -999 999
#> SE 0.129 NA 0.103 NA NA
#>
#> $Item_14
#> a1 a2 d logit(g) logit(u)
#> par 1.158 0 0.796 -999 999
#> SE 0.109 NA 0.100 NA NA
#>
#> $Item_15
#> a1 a2 d logit(g) logit(u)
#> par 1.088 0 -0.506 -999 999
#> SE 0.107 NA 0.090 NA NA
#>
#> $Item_16
#> a1 a2 d logit(g) logit(u)
#> par 1.862 0 0.474 -999 999
#> SE 0.161 NA 0.125 NA NA
#>
#> $Item_17
#> a1 a2 d logit(g) logit(u)
#> par 0.911 0 1.207 -999 999
#> SE 0.098 NA 0.100 NA NA
#>
#> $Item_18
#> a1 a2 d logit(g) logit(u)
#> par 1.041 0 0.768 -999 999
#> SE 0.102 NA 0.095 NA NA
#>
#> $Item_19
#> a1 a2 d logit(g) logit(u)
#> par 1.397 0 0.170 -999 999
#> SE 0.124 NA 0.102 NA NA
#>
#> $Item_20
#> a1 a2 d logit(g) logit(u)
#> par 0.774 0 -0.247 -999 999
#> SE 0.087 NA 0.079 NA NA
#>
#> $Item_21
#> a1 a2 d logit(g) logit(u)
#> par 0 1.221 -0.220 -999 999
#> SE NA 0.113 0.094 NA NA
#>
#> $Item_22
#> a1 a2 d logit(g) logit(u)
#> par 0 1.046 1.161 -999 999
#> SE NA 0.105 0.104 NA NA
#>
#> $Item_23
#> a1 a2 d logit(g) logit(u)
#> par 0 0.978 -0.112 -999 999
#> SE NA 0.098 0.085 NA NA
#>
#> $Item_24
#> a1 a2 d logit(g) logit(u)
#> par 0 1.304 0.293 -999 999
#> SE NA 0.117 0.099 NA NA
#>
#> $Item_25
#> a1 a2 d logit(g) logit(u)
#> par 0 1.173 0.402 -999 999
#> SE NA 0.109 0.095 NA NA
#>
#> $Item_26
#> a1 a2 d logit(g) logit(u)
#> par 0 1.187 0.490 -999 999
#> SE NA 0.109 0.097 NA NA
#>
#> $Item_27
#> a1 a2 d logit(g) logit(u)
#> par 0 1.122 0.218 -999 999
#> SE NA 0.105 0.092 NA NA
#>
#> $Item_28
#> a1 a2 d logit(g) logit(u)
#> par 0 1.041 -0.930 -999 999
#> SE NA 0.108 0.093 NA NA
#>
#> $Item_29
#> a1 a2 d logit(g) logit(u)
#> par 0 0.765 -0.441 -999 999
#> SE NA 0.088 0.079 NA NA
#>
#> $Item_30
#> a1 a2 d logit(g) logit(u)
#> par 0 1.253 -0.666 -999 999
#> SE NA 0.119 0.098 NA NA
#>
#> $Item_31
#> a1 a2 d logit(g) logit(u)
#> par 0 0.813 -0.276 -999 999
#> SE NA 0.089 0.080 NA NA
#>
#> $Item_32
#> a1 a2 d logit(g) logit(u)
#> par 0 1.127 -0.086 -999 999
#> SE NA 0.107 0.091 NA NA
#>
#> $Item_33
#> a1 a2 d logit(g) logit(u)
#> par 0 1.450 -0.097 -999 999
#> SE NA 0.129 0.103 NA NA
#>
#> $Item_34
#> a1 a2 d logit(g) logit(u)
#> par 0 1.158 0.796 -999 999
#> SE NA 0.109 0.100 NA NA
#>
#> $Item_35
#> a1 a2 d logit(g) logit(u)
#> par 0 1.088 -0.506 -999 999
#> SE NA 0.107 0.090 NA NA
#>
#> $Item_36
#> a1 a2 d logit(g) logit(u)
#> par 0 1.862 0.474 -999 999
#> SE NA 0.161 0.125 NA NA
#>
#> $Item_37
#> a1 a2 d logit(g) logit(u)
#> par 0 0.911 1.207 -999 999
#> SE NA 0.098 0.100 NA NA
#>
#> $Item_38
#> a1 a2 d logit(g) logit(u)
#> par 0 1.041 0.768 -999 999
#> SE NA 0.102 0.095 NA NA
#>
#> $Item_39
#> a1 a2 d logit(g) logit(u)
#> par 0 1.397 0.170 -999 999
#> SE NA 0.124 0.102 NA NA
#>
#> $Item_40
#> a1 a2 d logit(g) logit(u)
#> par 0 0.774 -0.247 -999 999
#> SE NA 0.087 0.079 NA NA
#>
#> $GroupPars
#> MEAN_1 MEAN_2 COV_11 COV_21 COV_22
#> par 0 -0.556 1 0.738 1.074
#> SE NA 0.051 NA 0.050 0.109
#>
coef(mod, simplify=TRUE)
#> $items
#> a1 a2 d g u
#> Item_1 1.221 0.000 -0.220 0 1
#> Item_2 1.046 0.000 1.161 0 1
#> Item_3 0.978 0.000 -0.112 0 1
#> Item_4 1.304 0.000 0.293 0 1
#> Item_5 1.173 0.000 0.402 0 1
#> Item_6 1.187 0.000 0.490 0 1
#> Item_7 1.122 0.000 0.218 0 1
#> Item_8 1.041 0.000 -0.930 0 1
#> Item_9 0.765 0.000 -0.441 0 1
#> Item_10 1.253 0.000 -0.666 0 1
#> Item_11 0.813 0.000 -0.276 0 1
#> Item_12 1.127 0.000 -0.086 0 1
#> Item_13 1.450 0.000 -0.097 0 1
#> Item_14 1.158 0.000 0.796 0 1
#> Item_15 1.088 0.000 -0.506 0 1
#> Item_16 1.862 0.000 0.474 0 1
#> Item_17 0.911 0.000 1.207 0 1
#> Item_18 1.041 0.000 0.768 0 1
#> Item_19 1.397 0.000 0.170 0 1
#> Item_20 0.774 0.000 -0.247 0 1
#> Item_21 0.000 1.221 -0.220 0 1
#> Item_22 0.000 1.046 1.161 0 1
#> Item_23 0.000 0.978 -0.112 0 1
#> Item_24 0.000 1.304 0.293 0 1
#> Item_25 0.000 1.173 0.402 0 1
#> Item_26 0.000 1.187 0.490 0 1
#> Item_27 0.000 1.122 0.218 0 1
#> Item_28 0.000 1.041 -0.930 0 1
#> Item_29 0.000 0.765 -0.441 0 1
#> Item_30 0.000 1.253 -0.666 0 1
#> Item_31 0.000 0.813 -0.276 0 1
#> Item_32 0.000 1.127 -0.086 0 1
#> Item_33 0.000 1.450 -0.097 0 1
#> Item_34 0.000 1.158 0.796 0 1
#> Item_35 0.000 1.088 -0.506 0 1
#> Item_36 0.000 1.862 0.474 0 1
#> Item_37 0.000 0.911 1.207 0 1
#> Item_38 0.000 1.041 0.768 0 1
#> Item_39 0.000 1.397 0.170 0 1
#> Item_40 0.000 0.774 -0.247 0 1
#>
#> $means
#> thetapre thetapost
#> 0.000 -0.556
#>
#> $cov
#> thetapre thetapost
#> thetapre 1.000 0.738
#> thetapost 0.738 1.074
#>
summary(mod)
#> thetapre thetapost h2
#> Item_1 0.583 0.340
#> Item_2 0.524 0.274
#> Item_3 0.498 0.248
#> Item_4 0.608 0.370
#> Item_5 0.568 0.322
#> Item_6 0.572 0.327
#> Item_7 0.550 0.303
#> Item_8 0.522 0.272
#> Item_9 0.410 0.168
#> Item_10 0.593 0.351
#> Item_11 0.431 0.186
#> Item_12 0.552 0.305
#> Item_13 0.649 0.421
#> Item_14 0.562 0.316
#> Item_15 0.539 0.290
#> Item_16 0.738 0.545
#> Item_17 0.472 0.223
#> Item_18 0.522 0.272
#> Item_19 0.634 0.402
#> Item_20 0.414 0.171
#> Item_21 0.597 0.356
#> Item_22 0.537 0.289
#> Item_23 0.512 0.262
#> Item_24 0.622 0.387
#> Item_25 0.581 0.338
#> Item_26 0.586 0.343
#> Item_27 0.564 0.318
#> Item_28 0.535 0.286
#> Item_29 0.422 0.178
#> Item_30 0.606 0.368
#> Item_31 0.444 0.197
#> Item_32 0.566 0.320
#> Item_33 0.662 0.438
#> Item_34 0.576 0.332
#> Item_35 0.552 0.305
#> Item_36 0.750 0.563
#> Item_37 0.485 0.235
#> Item_38 0.535 0.287
#> Item_39 0.648 0.420
#> Item_40 0.426 0.182
#>
#> SE.thetapre SE.thetapost
#> Item_1 0.036
#> Item_2 0.038
#> Item_3 0.037
#> Item_4 0.034
#> Item_5 0.036
#> Item_6 0.035
#> Item_7 0.036
#> Item_8 0.039
#> Item_9 0.039
#> Item_10 0.037
#> Item_11 0.039
#> Item_12 0.036
#> Item_13 0.033
#> Item_14 0.036
#> Item_15 0.037
#> Item_16 0.029
#> Item_17 0.039
#> Item_18 0.037
#> Item_19 0.034
#> Item_20 0.039
#> Item_21 0.036
#> Item_22 0.038
#> Item_23 0.038
#> Item_24 0.034
#> Item_25 0.036
#> Item_26 0.035
#> Item_27 0.036
#> Item_28 0.040
#> Item_29 0.040
#> Item_30 0.036
#> Item_31 0.039
#> Item_32 0.036
#> Item_33 0.033
#> Item_34 0.036
#> Item_35 0.038
#> Item_36 0.028
#> Item_37 0.040
#> Item_38 0.037
#> Item_39 0.033
#> Item_40 0.039
#>
#> SS loadings: 6.107 6.403
#> Proportion Var: 0.153 0.16
#>
#> Factor correlations:
#>
#> thetapre thetapost
#> thetapre 1.000
#> thetapost 0.712 1
# test data
Theta <- cbind(c(0, 1, 2), c(0,1,2))
nochange <- simdata(a, d, itemtype = '2PL', Theta = Theta)
change <- simdata(a, d, itemtype = '2PL', Theta = Theta +
cbind(0, c(-1, -1, -1)))
# total score differences
data.frame(pre=rowSums(nochange[,1:J]),
post=rowSums(nochange[,1:J + J]))
#> pre post
#> 1 11 10
#> 2 12 18
#> 3 20 18
data.frame(pre=rowSums(change[,1:J]),
post=rowSums(change[,1:J + J]))
#> pre post
#> 1 10 7
#> 2 13 9
#> 3 19 17
RCI(mod, predat = nochange)
#> pre.score post.score converged diff SE z p
#> 1 0.155 -0.142 TRUE 0.297 0.537 0.554 0.58
#> 2 0.235 1.473 TRUE -1.238 0.633 -1.958 0.05
#> 3 2.145 1.300 TRUE 0.844 0.766 1.102 0.271
RCI(mod, predat = change)
#> pre.score post.score converged diff SE z p
#> 1 -0.054 -0.759 TRUE 0.705 0.550 1.282 0.2
#> 2 0.507 -0.318 TRUE 0.826 0.551 1.500 0.134
#> 3 1.753 1.174 TRUE 0.579 0.710 0.815 0.415
# }