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: -11650.156, Max-Change: 0.58673
Iteration: 2, Log-Lik: -11516.282, Max-Change: 0.27259
Iteration: 3, Log-Lik: -11491.324, Max-Change: 0.14644
Iteration: 4, Log-Lik: -11482.976, Max-Change: 0.08499
Iteration: 5, Log-Lik: -11479.654, Max-Change: 0.05299
Iteration: 6, Log-Lik: -11478.236, Max-Change: 0.03410
Iteration: 7, Log-Lik: -11477.241, Max-Change: 0.01166
Iteration: 8, Log-Lik: -11477.164, Max-Change: 0.00770
Iteration: 9, Log-Lik: -11477.127, Max-Change: 0.00528
Iteration: 10, Log-Lik: -11477.095, Max-Change: 0.00123
Iteration: 11, Log-Lik: -11477.094, Max-Change: 0.00075
Iteration: 12, Log-Lik: -11477.093, Max-Change: 0.00046
Iteration: 13, Log-Lik: -11477.093, Max-Change: 0.00034
Iteration: 14, Log-Lik: -11477.093, Max-Change: 0.00029
Iteration: 15, Log-Lik: -11477.093, Max-Change: 0.00025
Iteration: 16, Log-Lik: -11477.093, Max-Change: 0.00019
Iteration: 17, Log-Lik: -11477.093, Max-Change: 0.00015
Iteration: 18, Log-Lik: -11477.093, Max-Change: 0.00012
Iteration: 19, Log-Lik: -11477.093, Max-Change: 0.00009
# 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 1.714 1.970 TRUE 0.256 0.759 0.337 0.736
#> 2 1.406 -0.120 TRUE -1.526 0.582 -2.620 0.009
#> 3 0.960 -0.150 TRUE -1.111 0.536 -2.073 0.038
#> 4 0.302 0.202 TRUE -0.100 0.496 -0.202 0.84
#> 5 -0.973 -0.906 TRUE 0.067 0.548 0.122 0.903
#> 6 -0.797 -0.298 TRUE 0.499 0.508 0.983 0.326
#> 7 0.151 -0.466 TRUE -0.617 0.492 -1.253 0.21
#> 8 0.111 1.052 TRUE 0.940 0.547 1.721 0.085
#> 9 -1.367 -1.355 TRUE 0.013 0.626 0.020 0.984
#> 10 -0.946 -0.416 TRUE 0.530 0.521 1.016 0.31
#> 11 -1.876 -0.774 TRUE 1.101 0.646 1.705 0.088
#> 12 1.258 0.788 TRUE -0.470 0.599 -0.786 0.432
#> 13 0.342 0.038 TRUE -0.303 0.494 -0.615 0.539
#> 14 0.201 -0.033 TRUE -0.234 0.488 -0.480 0.631
#> 15 1.434 1.527 TRUE 0.094 0.683 0.137 0.891
#> 16 -1.862 -1.179 TRUE 0.683 0.671 1.018 0.309
#> 17 0.141 -0.291 TRUE -0.432 0.487 -0.886 0.376
#> 18 0.196 0.222 TRUE 0.026 0.493 0.054 0.957
#> 19 1.084 0.421 TRUE -0.663 0.560 -1.185 0.236
#> 20 0.912 0.037 TRUE -0.875 0.532 -1.644 0.1
#> 21 -0.526 -0.624 TRUE -0.098 0.504 -0.195 0.846
#> 22 -0.371 0.377 TRUE 0.748 0.497 1.503 0.133
#> 23 -1.486 -0.978 TRUE 0.508 0.606 0.838 0.402
#> 24 -0.742 -0.495 TRUE 0.247 0.509 0.484 0.628
#> 25 0.798 0.923 TRUE 0.124 0.568 0.219 0.827
#> 26 -0.207 -0.503 TRUE -0.296 0.491 -0.603 0.547
#> 27 1.265 1.233 TRUE -0.032 0.637 -0.051 0.959
#> 28 -1.011 -0.104 TRUE 0.907 0.523 1.736 0.083
#> 29 0.671 1.011 TRUE 0.340 0.567 0.600 0.549
#> 30 -1.045 -0.551 TRUE 0.494 0.534 0.925 0.355
#> 31 -1.481 -2.133 TRUE -0.651 0.737 -0.883 0.377
#> 32 -0.158 -0.636 TRUE -0.478 0.496 -0.963 0.335
#> 33 2.251 2.251 TRUE 0.000 0.846 0.000 1
#> 34 -0.255 -0.541 TRUE -0.286 0.493 -0.581 0.561
#> 35 -1.237 -1.002 TRUE 0.235 0.580 0.405 0.685
#> 36 0.789 1.120 TRUE 0.331 0.585 0.565 0.572
#> 37 -0.252 -0.135 TRUE 0.118 0.484 0.243 0.808
#> 38 1.078 0.586 TRUE -0.492 0.568 -0.867 0.386
#> 39 -0.022 0.480 TRUE 0.502 0.500 1.004 0.315
#> 40 1.691 1.629 TRUE -0.062 0.720 -0.086 0.931
#> 41 0.252 -0.130 TRUE -0.382 0.489 -0.782 0.434
#> 42 0.162 -0.282 TRUE -0.443 0.488 -0.909 0.363
#> 43 -0.287 -0.374 TRUE -0.087 0.488 -0.179 0.858
#> 44 -0.016 0.057 TRUE 0.074 0.484 0.152 0.879
#> 45 -0.406 -0.159 TRUE 0.247 0.487 0.507 0.612
#> 46 -0.363 -0.140 TRUE 0.223 0.486 0.458 0.647
#> 47 -0.548 -0.161 TRUE 0.387 0.492 0.786 0.432
#> 48 -0.657 -0.344 TRUE 0.313 0.500 0.626 0.531
#> 49 -0.642 -0.206 TRUE 0.436 0.497 0.877 0.381
#> 50 -0.390 0.102 TRUE 0.492 0.489 1.006 0.314
#> 51 0.676 1.310 TRUE 0.634 0.597 1.063 0.288
#> 52 -0.601 -0.481 TRUE 0.120 0.501 0.239 0.811
#> 53 1.972 0.685 TRUE -1.287 0.675 -1.906 0.057
#> 54 -0.606 0.133 TRUE 0.740 0.498 1.486 0.137
#> 55 -0.147 -0.157 TRUE -0.010 0.483 -0.022 0.983
#> 56 -0.400 -0.318 TRUE 0.082 0.489 0.167 0.867
#> 57 -0.246 -0.602 TRUE -0.356 0.496 -0.718 0.473
#> 58 -1.014 -1.271 TRUE -0.257 0.584 -0.440 0.66
#> 59 0.090 -0.219 TRUE -0.310 0.485 -0.638 0.523
#> 60 0.781 0.685 TRUE -0.096 0.548 -0.175 0.861
#> 61 0.477 0.424 TRUE -0.053 0.513 -0.103 0.918
#> 62 1.066 0.712 TRUE -0.354 0.574 -0.616 0.538
#> 63 0.419 0.486 TRUE 0.067 0.513 0.130 0.896
#> 64 -0.863 -0.870 TRUE -0.007 0.538 -0.012 0.99
#> 65 -0.866 -0.907 TRUE -0.041 0.540 -0.076 0.94
#> 66 -0.863 -1.125 TRUE -0.262 0.559 -0.470 0.639
#> 67 1.714 0.792 TRUE -0.922 0.650 -1.419 0.156
#> 68 -0.136 -0.445 TRUE -0.309 0.488 -0.633 0.527
#> 69 0.184 -0.046 TRUE -0.231 0.487 -0.473 0.636
#> 70 1.972 1.470 TRUE -0.502 0.735 -0.682 0.495
#> 71 -0.153 -0.738 TRUE -0.586 0.502 -1.166 0.244
#> 72 1.290 0.929 TRUE -0.361 0.612 -0.590 0.555
#> 73 -0.041 0.003 TRUE 0.044 0.484 0.090 0.928
#> 74 0.156 0.281 TRUE 0.125 0.494 0.252 0.801
#> 75 0.590 0.043 TRUE -0.547 0.507 -1.078 0.281
#> 76 0.818 0.796 TRUE -0.022 0.559 -0.039 0.969
#> 77 -0.693 -0.942 TRUE -0.249 0.532 -0.468 0.64
#> 78 0.237 0.147 TRUE -0.090 0.492 -0.182 0.855
#> 79 0.852 -0.057 TRUE -0.909 0.526 -1.727 0.084
#> 80 0.297 0.201 TRUE -0.097 0.495 -0.195 0.845
#> 81 -0.117 -0.324 TRUE -0.207 0.485 -0.426 0.67
#> 82 0.499 0.262 TRUE -0.236 0.507 -0.466 0.641
#> 83 0.297 0.112 TRUE -0.185 0.493 -0.375 0.707
#> 84 -0.821 -1.876 TRUE -1.055 0.648 -1.627 0.104
#> 85 -0.500 -0.136 TRUE 0.363 0.490 0.741 0.459
#> 86 -0.554 0.157 TRUE 0.711 0.496 1.434 0.152
#> 87 -1.099 -0.542 TRUE 0.557 0.539 1.033 0.302
#> 88 -0.200 0.099 TRUE 0.299 0.485 0.615 0.538
#> 89 -0.297 -0.068 TRUE 0.229 0.485 0.473 0.636
#> 90 0.372 0.170 TRUE -0.202 0.498 -0.406 0.685
#> 91 -0.634 -1.629 TRUE -0.995 0.604 -1.646 0.1
#> 92 -0.666 -0.443 TRUE 0.223 0.503 0.444 0.657
#> 93 -1.257 -0.891 TRUE 0.366 0.573 0.638 0.524
#> 94 0.197 0.503 TRUE 0.307 0.505 0.607 0.544
#> 95 1.648 1.090 TRUE -0.558 0.664 -0.840 0.401
#> 96 -0.162 -0.492 TRUE -0.329 0.490 -0.672 0.501
#> 97 -0.390 0.107 TRUE 0.497 0.489 1.017 0.309
#> 98 -0.520 -0.462 TRUE 0.058 0.497 0.117 0.907
#> 99 0.268 0.095 TRUE -0.173 0.492 -0.352 0.725
#> 100 -0.113 -0.109 TRUE 0.004 0.483 0.007 0.994
#> 101 -0.782 -0.793 TRUE -0.011 0.527 -0.021 0.983
#> 102 0.897 1.091 TRUE 0.194 0.590 0.329 0.743
#> 103 -0.105 -0.130 TRUE -0.025 0.483 -0.053 0.958
#> 104 -0.364 0.941 TRUE 1.305 0.537 2.431 0.015
#> 105 -1.638 -1.441 TRUE 0.198 0.666 0.297 0.767
#> 106 -0.453 -0.084 TRUE 0.369 0.489 0.756 0.45
#> 107 0.294 0.262 TRUE -0.033 0.497 -0.066 0.947
#> 108 -1.638 -1.503 TRUE 0.135 0.673 0.201 0.841
#> 109 0.567 0.431 TRUE -0.137 0.518 -0.263 0.792
#> 110 -0.501 -0.961 TRUE -0.460 0.525 -0.876 0.381
#> 111 0.754 -0.118 TRUE -0.872 0.518 -1.683 0.092
#> 112 -0.804 -0.828 TRUE -0.023 0.531 -0.044 0.965
#> 113 1.003 1.654 TRUE 0.652 0.658 0.990 0.322
#> 114 -1.492 -2.133 TRUE -0.640 0.738 -0.867 0.386
#> 115 -0.190 0.455 TRUE 0.646 0.498 1.295 0.195
#> 116 0.804 0.776 TRUE -0.028 0.556 -0.051 0.96
#> 117 -0.203 -0.434 TRUE -0.231 0.488 -0.473 0.636
#> 118 -0.684 -0.888 TRUE -0.204 0.528 -0.386 0.7
#> 119 0.478 -0.047 TRUE -0.525 0.500 -1.051 0.293
#> 120 -0.386 -1.201 TRUE -0.815 0.544 -1.497 0.134
#> 121 -0.165 0.462 TRUE 0.627 0.499 1.257 0.209
#> 122 -1.403 -0.744 TRUE 0.660 0.581 1.136 0.256
#> 123 -0.280 -0.537 TRUE -0.257 0.493 -0.521 0.602
#> 124 -1.451 -0.856 TRUE 0.595 0.593 1.003 0.316
#> 125 0.345 0.253 TRUE -0.092 0.499 -0.185 0.854
#> 126 1.234 1.972 TRUE 0.738 0.714 1.033 0.302
#> 127 0.603 0.776 TRUE 0.173 0.542 0.318 0.75
#> 128 0.656 0.738 TRUE 0.082 0.543 0.152 0.879
#> 129 0.685 0.722 TRUE 0.037 0.544 0.069 0.945
#> 130 -0.316 0.634 TRUE 0.949 0.511 1.857 0.063
#> 131 0.268 0.009 TRUE -0.260 0.490 -0.530 0.596
#> 132 -1.131 -1.242 TRUE -0.112 0.591 -0.189 0.85
#> 133 0.936 0.862 TRUE -0.075 0.574 -0.130 0.896
#> 134 1.707 1.955 TRUE 0.248 0.757 0.327 0.743
#> 135 -1.495 -0.960 TRUE 0.535 0.605 0.884 0.377
#> 136 0.386 -0.097 TRUE -0.484 0.495 -0.978 0.328
#> 137 0.428 0.471 TRUE 0.043 0.513 0.084 0.933
#> 138 -0.469 -1.073 TRUE -0.604 0.534 -1.131 0.258
#> 139 0.609 0.070 TRUE -0.539 0.509 -1.059 0.289
#> 140 -0.253 -0.848 TRUE -0.594 0.510 -1.164 0.244
#> 141 1.650 1.431 TRUE -0.218 0.695 -0.314 0.754
#> 142 0.860 0.826 TRUE -0.034 0.565 -0.061 0.952
#> 143 -0.471 -0.057 TRUE 0.415 0.489 0.847 0.397
#> 144 0.643 -0.130 TRUE -0.772 0.510 -1.515 0.13
#> 145 -1.411 -0.965 TRUE 0.446 0.596 0.749 0.454
#> 146 -1.736 -1.536 TRUE 0.200 0.689 0.290 0.772
#> 147 -0.848 -0.577 TRUE 0.271 0.520 0.521 0.602
#> 148 -0.279 -0.351 TRUE -0.072 0.487 -0.148 0.882
#> 149 0.510 0.886 TRUE 0.376 0.546 0.689 0.491
#> 150 -0.174 -0.160 TRUE 0.014 0.483 0.028 0.977
#> 151 -0.440 -0.313 TRUE 0.127 0.490 0.258 0.796
#> 152 -1.513 -1.876 TRUE -0.362 0.705 -0.514 0.607
#> 153 -1.120 -1.223 TRUE -0.103 0.588 -0.175 0.861
#> 154 -0.576 -0.927 TRUE -0.351 0.526 -0.669 0.504
#> 155 1.141 0.518 TRUE -0.623 0.570 -1.093 0.275
#> 156 -0.197 0.304 TRUE 0.501 0.491 1.019 0.308
#> 157 0.826 1.407 TRUE 0.581 0.617 0.942 0.346
#> 158 -0.111 -0.823 TRUE -0.712 0.508 -1.403 0.161
#> 159 -0.270 -0.091 TRUE 0.179 0.484 0.370 0.712
#> 160 1.481 0.197 TRUE -1.284 0.595 -2.159 0.031
#> 161 0.693 -0.442 TRUE -1.135 0.519 -2.189 0.029
#> 162 -0.416 -0.250 TRUE 0.166 0.488 0.340 0.734
#> 163 -1.237 -0.850 TRUE 0.387 0.569 0.681 0.496
#> 164 1.236 -0.394 TRUE -1.630 0.567 -2.875 0.004
#> 165 -0.030 -0.357 TRUE -0.327 0.486 -0.673 0.501
#> 166 -0.427 -0.285 TRUE 0.143 0.489 0.291 0.771
#> 167 1.077 1.036 TRUE -0.040 0.601 -0.067 0.947
#> 168 1.046 1.691 TRUE 0.645 0.666 0.968 0.333
#> 169 -1.220 -1.363 TRUE -0.143 0.612 -0.233 0.815
#> 170 -1.876 -1.638 TRUE 0.237 0.718 0.331 0.741
#> 171 -1.449 -2.133 TRUE -0.684 0.734 -0.931 0.352
#> 172 2.251 1.020 TRUE -1.231 0.731 -1.683 0.092
#> 173 0.054 0.386 TRUE 0.332 0.496 0.670 0.503
#> 174 -0.176 -1.199 TRUE -1.024 0.541 -1.893 0.058
#> 175 -0.798 0.984 TRUE 1.781 0.559 3.187 0.001
#> 176 -0.305 -0.533 TRUE -0.227 0.493 -0.461 0.645
#> 177 0.820 1.071 TRUE 0.250 0.583 0.430 0.667
#> 178 -1.645 -0.911 TRUE 0.735 0.621 1.182 0.237
#> 179 1.675 2.251 TRUE 0.576 0.787 0.732 0.464
#> 180 -0.043 -0.341 TRUE -0.297 0.486 -0.613 0.54
#> 181 -0.639 -0.688 TRUE -0.049 0.513 -0.096 0.923
#> 182 -1.247 -0.804 TRUE 0.442 0.567 0.781 0.435
#> 183 0.019 -0.488 TRUE -0.507 0.491 -1.033 0.301
#> 184 -0.346 0.020 TRUE 0.367 0.486 0.754 0.451
#> 185 -0.786 -1.155 TRUE -0.369 0.556 -0.662 0.508
#> 186 -0.537 -0.933 TRUE -0.396 0.524 -0.756 0.45
#> 187 -0.400 -1.088 TRUE -0.688 0.533 -1.290 0.197
#> 188 -0.069 -0.136 TRUE -0.067 0.483 -0.139 0.89
#> 189 1.306 0.482 TRUE -0.824 0.586 -1.408 0.159
#> 190 -1.299 -1.122 TRUE 0.177 0.596 0.297 0.767
#> 191 0.834 1.047 TRUE 0.213 0.581 0.366 0.714
#> 192 -0.534 -0.061 TRUE 0.473 0.492 0.962 0.336
#> 193 -0.013 0.406 TRUE 0.420 0.496 0.846 0.398
#> 194 -1.449 -0.607 TRUE 0.842 0.580 1.452 0.146
#> 195 -1.046 -1.390 TRUE -0.345 0.600 -0.575 0.565
#> 196 0.280 -0.244 TRUE -0.524 0.491 -1.068 0.286
#> 197 -0.719 -1.629 TRUE -0.910 0.608 -1.495 0.135
#> 198 -0.864 -1.645 TRUE -0.781 0.618 -1.263 0.206
#> 199 1.356 1.427 TRUE 0.071 0.665 0.107 0.915
#> 200 -0.813 -1.227 TRUE -0.414 0.565 -0.732 0.464
#> 201 0.455 0.406 TRUE -0.049 0.511 -0.096 0.923
#> 202 0.809 0.356 TRUE -0.453 0.532 -0.851 0.395
#> 203 -1.403 -1.384 TRUE 0.020 0.633 0.031 0.975
#> 204 0.082 -0.052 TRUE -0.133 0.485 -0.275 0.783
#> 205 -0.021 0.020 TRUE 0.041 0.484 0.085 0.932
#> 206 0.509 0.218 TRUE -0.291 0.506 -0.575 0.565
#> 207 1.331 1.628 TRUE 0.297 0.683 0.434 0.664
#> 208 0.824 1.009 TRUE 0.185 0.577 0.320 0.749
#> 209 1.662 1.707 TRUE 0.045 0.725 0.061 0.951
#> 210 -1.481 -2.133 TRUE -0.651 0.737 -0.883 0.377
#> 211 -0.151 0.141 TRUE 0.293 0.486 0.602 0.547
#> 212 0.268 0.477 TRUE 0.209 0.506 0.413 0.68
#> 213 1.175 0.763 TRUE -0.412 0.588 -0.700 0.484
#> 214 -1.554 -1.443 TRUE 0.111 0.656 0.170 0.865
#> 215 -1.395 -1.021 TRUE 0.374 0.598 0.626 0.532
#> 216 0.644 1.470 TRUE 0.826 0.612 1.350 0.177
#> 217 0.762 0.317 TRUE -0.445 0.527 -0.845 0.398
#> 218 -1.186 -0.858 TRUE 0.329 0.564 0.583 0.56
#> 219 -0.128 -0.455 TRUE -0.327 0.489 -0.669 0.503
#> 220 -2.133 -1.854 TRUE 0.279 0.778 0.358 0.72
#> 221 0.809 0.333 TRUE -0.476 0.531 -0.896 0.37
#> 222 -1.432 -1.660 TRUE -0.228 0.668 -0.341 0.733
#> 223 -0.774 -0.017 TRUE 0.757 0.505 1.500 0.133
#> 224 -0.236 0.910 TRUE 1.146 0.532 2.155 0.031
#> 225 0.411 0.628 TRUE 0.218 0.521 0.418 0.676
#> 226 0.741 0.542 TRUE -0.199 0.536 -0.372 0.71
#> 227 0.273 0.123 TRUE -0.150 0.492 -0.305 0.761
#> 228 -0.121 -0.127 TRUE -0.006 0.483 -0.013 0.99
#> 229 1.481 0.947 TRUE -0.534 0.634 -0.842 0.4
#> 230 -1.577 -1.495 TRUE 0.082 0.665 0.123 0.902
#> 231 -0.718 -0.224 TRUE 0.494 0.502 0.985 0.325
#> 232 0.073 0.782 TRUE 0.709 0.522 1.358 0.174
#> 233 0.424 0.548 TRUE 0.124 0.517 0.240 0.81
#> 234 0.424 1.400 TRUE 0.975 0.593 1.644 0.1
#> 235 0.510 -0.562 TRUE -1.071 0.511 -2.097 0.036
#> 236 -0.269 -0.372 TRUE -0.103 0.487 -0.211 0.833
#> 237 -0.318 -0.243 TRUE 0.075 0.486 0.155 0.877
#> 238 -0.579 0.279 TRUE 0.858 0.501 1.714 0.086
#> 239 -0.072 -0.135 TRUE -0.063 0.483 -0.130 0.896
#> 240 -0.539 0.226 TRUE 0.765 0.497 1.538 0.124
#> 241 1.353 1.662 TRUE 0.310 0.689 0.449 0.653
#> 242 -1.018 -1.260 TRUE -0.242 0.583 -0.414 0.679
#> 243 -1.793 -1.645 TRUE 0.148 0.708 0.209 0.834
#> 244 -1.305 -1.824 TRUE -0.519 0.677 -0.767 0.443
#> 245 -0.877 -0.782 TRUE 0.095 0.533 0.178 0.859
#> 246 -0.979 -1.136 TRUE -0.158 0.568 -0.278 0.781
#> 247 1.288 1.483 TRUE 0.195 0.664 0.293 0.769
#> 248 2.251 1.595 TRUE -0.656 0.779 -0.842 0.4
#> 249 -0.192 -0.129 TRUE 0.063 0.483 0.130 0.897
#> 250 0.804 1.461 TRUE 0.657 0.622 1.057 0.291
#> 251 0.843 0.406 TRUE -0.437 0.537 -0.814 0.416
#> 252 -0.204 -0.179 TRUE 0.025 0.483 0.053 0.958
#> 253 -0.379 -0.135 TRUE 0.244 0.486 0.502 0.616
#> 254 0.253 0.346 TRUE 0.093 0.499 0.186 0.852
#> 255 1.624 1.229 TRUE -0.395 0.674 -0.586 0.558
#> 256 -0.031 0.341 TRUE 0.372 0.493 0.755 0.45
#> 257 1.546 1.096 TRUE -0.450 0.653 -0.688 0.491
#> 258 0.004 0.183 TRUE 0.180 0.488 0.368 0.713
#> 259 -0.997 -1.336 TRUE -0.340 0.590 -0.576 0.564
#> 260 0.215 0.633 TRUE 0.417 0.514 0.812 0.417
#> 261 0.687 0.251 TRUE -0.436 0.519 -0.840 0.401
#> 262 0.779 0.500 TRUE -0.279 0.537 -0.519 0.604
#> 263 1.953 1.437 TRUE -0.517 0.730 -0.708 0.479
#> 264 -0.856 -0.750 TRUE 0.106 0.529 0.201 0.841
#> 265 1.482 1.433 TRUE -0.050 0.678 -0.073 0.942
#> 266 -0.179 0.385 TRUE 0.563 0.495 1.138 0.255
#> 267 -1.002 -0.592 TRUE 0.411 0.532 0.772 0.44
#> 268 0.860 0.373 TRUE -0.486 0.537 -0.905 0.365
#> 269 -0.348 -0.435 TRUE -0.087 0.491 -0.178 0.859
#> 270 -0.270 0.211 TRUE 0.481 0.489 0.983 0.326
#> 271 -1.862 -1.588 TRUE 0.274 0.711 0.385 0.7
#> 272 -0.369 -0.643 TRUE -0.274 0.500 -0.549 0.583
#> 273 -0.704 -0.665 TRUE 0.039 0.515 0.075 0.94
#> 274 1.431 1.112 TRUE -0.319 0.642 -0.496 0.62
#> 275 0.544 0.213 TRUE -0.331 0.508 -0.652 0.515
#> 276 -1.431 -1.876 TRUE -0.444 0.696 -0.638 0.523
#> 277 -0.233 -0.083 TRUE 0.151 0.483 0.312 0.755
#> 278 -1.633 -2.133 TRUE -0.500 0.753 -0.664 0.507
#> 279 0.208 0.290 TRUE 0.082 0.495 0.166 0.868
#> 280 1.163 1.427 TRUE 0.264 0.646 0.408 0.683
#> 281 0.988 1.280 TRUE 0.292 0.616 0.474 0.636
#> 282 0.796 1.009 TRUE 0.213 0.575 0.370 0.711
#> 283 1.019 1.064 TRUE 0.045 0.598 0.076 0.94
#> 284 -1.192 -1.861 TRUE -0.669 0.672 -0.996 0.319
#> 285 1.163 1.678 TRUE 0.515 0.674 0.764 0.445
#> 286 0.084 -0.365 TRUE -0.449 0.488 -0.920 0.358
#> 287 0.370 0.728 TRUE 0.358 0.526 0.680 0.496
#> 288 0.896 1.431 TRUE 0.535 0.625 0.856 0.392
#> 289 1.413 0.898 TRUE -0.514 0.623 -0.826 0.409
#> 290 0.878 0.408 TRUE -0.471 0.540 -0.871 0.384
#> 291 0.867 0.569 TRUE -0.299 0.548 -0.545 0.585
#> 292 0.083 0.002 TRUE -0.082 0.485 -0.168 0.866
#> 293 -2.133 -1.403 TRUE 0.729 0.730 0.999 0.318
#> 294 0.289 -0.243 TRUE -0.533 0.491 -1.084 0.278
#> 295 -1.058 -0.487 TRUE 0.571 0.533 1.070 0.284
#> 296 1.090 0.801 TRUE -0.290 0.583 -0.497 0.619
#> 297 1.574 1.297 TRUE -0.277 0.674 -0.411 0.681
#> 298 -0.235 -0.406 TRUE -0.171 0.488 -0.350 0.727
#> 299 1.635 0.461 TRUE -1.174 0.622 -1.887 0.059
#> 300 -2.133 -1.861 TRUE 0.272 0.779 0.349 0.727
#> 301 -0.984 0.084 TRUE 1.068 0.522 2.046 0.041
#> 302 -0.068 -0.273 TRUE -0.204 0.484 -0.422 0.673
#> 303 -0.845 -1.609 TRUE -0.764 0.612 -1.248 0.212
#> 304 1.972 1.476 TRUE -0.496 0.736 -0.675 0.5
#> 305 0.125 -0.538 TRUE -0.663 0.494 -1.340 0.18
#> 306 0.785 1.022 TRUE 0.237 0.576 0.412 0.681
#> 307 -0.048 0.324 TRUE 0.372 0.492 0.757 0.449
#> 308 0.251 -0.111 TRUE -0.362 0.489 -0.739 0.46
#> 309 -0.114 -0.508 TRUE -0.394 0.491 -0.803 0.422
#> 310 -0.238 -0.745 TRUE -0.507 0.503 -1.007 0.314
#> 311 0.837 0.901 TRUE 0.064 0.569 0.113 0.91
#> 312 1.010 0.146 TRUE -0.865 0.543 -1.592 0.111
#> 313 -0.809 -1.004 TRUE -0.194 0.544 -0.357 0.721
#> 314 0.255 0.215 TRUE -0.040 0.494 -0.081 0.935
#> 315 -0.380 -0.574 TRUE -0.194 0.497 -0.389 0.697
#> 316 -0.088 0.094 TRUE 0.182 0.485 0.376 0.707
#> 317 -0.480 0.272 TRUE 0.752 0.496 1.514 0.13
#> 318 -1.821 -0.874 TRUE 0.947 0.643 1.471 0.141
#> 319 0.011 0.000 TRUE -0.011 0.484 -0.023 0.982
#> 320 0.465 0.106 TRUE -0.358 0.501 -0.716 0.474
#> 321 0.483 -0.025 TRUE -0.508 0.500 -1.016 0.31
#> 322 0.603 -0.292 TRUE -0.895 0.509 -1.760 0.078
#> 323 -1.793 -1.495 TRUE 0.298 0.692 0.431 0.666
#> 324 0.575 0.654 TRUE 0.080 0.532 0.150 0.881
#> 325 0.496 0.624 TRUE 0.127 0.525 0.242 0.808
#> 326 0.683 0.552 TRUE -0.131 0.533 -0.246 0.806
#> 327 -0.578 -0.635 TRUE -0.057 0.507 -0.113 0.91
#> 328 -0.132 0.314 TRUE 0.447 0.491 0.909 0.364
#> 329 0.525 0.555 TRUE 0.030 0.523 0.058 0.954
#> 330 -0.648 0.534 TRUE 1.181 0.516 2.288 0.022
#> 331 0.358 0.783 TRUE 0.425 0.530 0.802 0.423
#> 332 -0.182 -0.859 TRUE -0.677 0.511 -1.326 0.185
#> 333 0.575 0.305 TRUE -0.269 0.513 -0.525 0.6
#> 334 0.543 0.792 TRUE 0.249 0.540 0.461 0.645
#> 335 -0.068 0.230 TRUE 0.297 0.488 0.608 0.543
#> 336 0.018 -0.276 TRUE -0.294 0.485 -0.606 0.545
#> 337 0.468 0.446 TRUE -0.022 0.513 -0.042 0.966
#> 338 1.082 0.610 TRUE -0.472 0.569 -0.828 0.408
#> 339 -0.797 -0.082 TRUE 0.715 0.506 1.413 0.158
#> 340 1.350 1.084 TRUE -0.266 0.631 -0.421 0.674
#> 341 0.407 0.718 TRUE 0.311 0.527 0.590 0.555
#> 342 -0.607 -0.720 TRUE -0.113 0.513 -0.220 0.826
#> 343 -0.949 -0.043 TRUE 0.906 0.517 1.751 0.08
#> 344 -0.688 -1.058 TRUE -0.370 0.542 -0.683 0.495
#> 345 -0.748 -0.283 TRUE 0.465 0.504 0.923 0.356
#> 346 0.379 -0.363 TRUE -0.742 0.497 -1.492 0.136
#> 347 0.169 0.343 TRUE 0.175 0.496 0.352 0.725
#> 348 -0.444 0.075 TRUE 0.518 0.490 1.058 0.29
#> 349 -0.861 -0.613 TRUE 0.249 0.522 0.477 0.634
#> 350 0.235 0.299 TRUE 0.064 0.497 0.129 0.897
#> 351 -0.268 -0.238 TRUE 0.030 0.485 0.063 0.95
#> 352 1.610 1.046 TRUE -0.564 0.656 -0.859 0.39
#> 353 -0.267 0.103 TRUE 0.369 0.486 0.760 0.447
#> 354 -0.962 -1.295 TRUE -0.333 0.583 -0.571 0.568
#> 355 0.393 1.483 TRUE 1.090 0.601 1.813 0.07
#> 356 1.016 0.671 TRUE -0.344 0.567 -0.607 0.544
#> 357 -0.203 0.359 TRUE 0.562 0.494 1.139 0.255
#> 358 0.033 -0.544 TRUE -0.577 0.493 -1.171 0.242
#> 359 -1.876 -1.197 TRUE 0.679 0.674 1.007 0.314
#> 360 -0.026 0.341 TRUE 0.368 0.493 0.746 0.455
#> 361 -0.752 -0.800 TRUE -0.048 0.526 -0.091 0.927
#> 362 0.706 0.838 TRUE 0.133 0.554 0.239 0.811
#> 363 -0.154 0.351 TRUE 0.505 0.493 1.024 0.306
#> 364 0.552 0.863 TRUE 0.311 0.546 0.569 0.569
#> 365 -0.232 -1.007 TRUE -0.775 0.523 -1.482 0.138
#> 366 1.229 1.309 TRUE 0.080 0.641 0.124 0.901
#> 367 -0.901 -1.513 TRUE -0.612 0.604 -1.015 0.31
#> 368 0.350 -0.035 TRUE -0.385 0.493 -0.781 0.435
#> 369 -1.293 -0.073 TRUE 1.220 0.551 2.214 0.027
#> 370 0.279 0.458 TRUE 0.179 0.505 0.354 0.723
#> 371 0.786 1.531 TRUE 0.745 0.628 1.187 0.235
#> 372 -0.170 0.296 TRUE 0.467 0.491 0.950 0.342
#> 373 -0.479 -0.199 TRUE 0.280 0.490 0.571 0.568
#> 374 -1.039 -0.627 TRUE 0.412 0.537 0.767 0.443
#> 375 0.097 -0.872 TRUE -0.970 0.513 -1.889 0.059
#> 376 1.252 0.813 TRUE -0.438 0.600 -0.731 0.465
#> 377 1.041 1.017 TRUE -0.023 0.596 -0.039 0.969
#> 378 0.526 0.448 TRUE -0.078 0.517 -0.152 0.88
#> 379 -2.133 -1.409 TRUE 0.723 0.730 0.990 0.322
#> 380 -0.630 -0.446 TRUE 0.184 0.501 0.367 0.714
#> 381 -0.659 -0.404 TRUE 0.254 0.502 0.507 0.612
#> 382 -0.538 -0.527 TRUE 0.012 0.500 0.023 0.982
#> 383 -0.701 -0.207 TRUE 0.494 0.500 0.987 0.324
#> 384 -1.109 -1.071 TRUE 0.038 0.573 0.065 0.948
#> 385 -1.214 -0.948 TRUE 0.265 0.573 0.463 0.643
#> 386 -1.577 -0.660 TRUE 0.917 0.598 1.533 0.125
#> 387 -0.237 -0.039 TRUE 0.198 0.484 0.409 0.682
#> 388 1.970 0.778 TRUE -1.192 0.680 -1.753 0.08
#> 389 -1.189 -0.742 TRUE 0.447 0.557 0.803 0.422
#> 390 -2.133 -1.492 TRUE 0.641 0.738 0.868 0.385
#> 391 1.056 0.679 TRUE -0.378 0.571 -0.661 0.509
#> 392 0.174 -1.067 TRUE -1.240 0.531 -2.335 0.02
#> 393 -1.005 -0.480 TRUE 0.525 0.528 0.995 0.32
#> 394 -1.459 -1.685 TRUE -0.226 0.674 -0.335 0.738
#> 395 -0.321 0.380 TRUE 0.701 0.497 1.412 0.158
#> 396 0.515 0.275 TRUE -0.240 0.509 -0.472 0.637
#> 397 0.900 0.892 TRUE -0.008 0.573 -0.013 0.989
#> 398 -1.495 -0.944 TRUE 0.551 0.604 0.911 0.362
#> 399 0.493 -0.680 TRUE -1.173 0.516 -2.275 0.023
#> 400 0.846 -0.109 TRUE -0.955 0.526 -1.817 0.069
#> 401 -0.437 -0.204 TRUE 0.233 0.488 0.478 0.633
#> 402 -1.117 -1.387 TRUE -0.270 0.605 -0.446 0.655
#> 403 -0.021 0.116 TRUE 0.137 0.486 0.283 0.777
#> 404 1.379 1.433 TRUE 0.053 0.668 0.080 0.936
#> 405 -1.876 -1.013 TRUE 0.862 0.660 1.306 0.192
#> 406 -1.097 -1.481 TRUE -0.384 0.614 -0.625 0.532
#> 407 -0.404 -0.073 TRUE 0.332 0.487 0.681 0.496
#> 408 -0.429 0.098 TRUE 0.527 0.490 1.076 0.282
#> 409 0.251 0.492 TRUE 0.241 0.506 0.477 0.634
#> 410 -0.212 -0.655 TRUE -0.443 0.498 -0.891 0.373
#> 411 -0.305 -1.038 TRUE -0.732 0.527 -1.390 0.164
#> 412 0.920 0.138 TRUE -0.782 0.535 -1.463 0.143
#> 413 -0.810 -1.296 TRUE -0.486 0.572 -0.848 0.396
#> 414 1.101 1.420 TRUE 0.319 0.640 0.498 0.618
#> 415 0.082 0.805 TRUE 0.723 0.524 1.380 0.167
#> 416 0.750 0.364 TRUE -0.385 0.528 -0.730 0.465
#> 417 0.665 0.872 TRUE 0.206 0.554 0.373 0.709
#> 418 -0.836 -0.634 TRUE 0.202 0.521 0.387 0.699
#> 419 -0.834 -0.041 TRUE 0.794 0.509 1.560 0.119
#> 420 0.134 0.592 TRUE 0.458 0.509 0.899 0.368
#> 421 -1.249 -1.645 TRUE -0.397 0.648 -0.612 0.54
#> 422 1.434 1.435 TRUE 0.001 0.673 0.002 0.998
#> 423 0.034 0.274 TRUE 0.240 0.491 0.489 0.625
#> 424 0.928 0.478 TRUE -0.451 0.548 -0.823 0.411
#> 425 1.093 -0.256 TRUE -1.348 0.549 -2.454 0.014
#> 426 0.826 1.069 TRUE 0.243 0.583 0.418 0.676
#> 427 0.155 -0.483 TRUE -0.638 0.493 -1.295 0.195
#> 428 -0.260 0.130 TRUE 0.390 0.487 0.802 0.423
#> 429 0.404 0.520 TRUE 0.116 0.514 0.226 0.822
#> 430 -0.198 0.085 TRUE 0.282 0.485 0.582 0.56
#> 431 1.015 0.756 TRUE -0.258 0.573 -0.451 0.652
#> 432 -1.876 -1.108 TRUE 0.768 0.667 1.151 0.25
#> 433 -1.189 -1.331 TRUE -0.142 0.605 -0.234 0.815
#> 434 0.276 0.784 TRUE 0.508 0.527 0.964 0.335
#> 435 -1.446 -1.143 TRUE 0.303 0.614 0.494 0.622
#> 436 -0.471 0.163 TRUE 0.634 0.493 1.287 0.198
#> 437 -1.418 -2.133 TRUE -0.714 0.731 -0.977 0.328
#> 438 0.564 0.693 TRUE 0.129 0.534 0.241 0.809
#> 439 1.592 0.623 TRUE -0.969 0.625 -1.549 0.121
#> 440 -0.591 0.379 TRUE 0.970 0.505 1.920 0.055
#> 441 0.763 0.389 TRUE -0.374 0.530 -0.705 0.481
#> 442 -1.090 -0.748 TRUE 0.342 0.548 0.625 0.532
#> 443 0.058 -0.020 TRUE -0.078 0.484 -0.161 0.872
#> 444 1.635 1.499 TRUE -0.136 0.701 -0.194 0.846
#> 445 1.379 1.211 TRUE -0.168 0.646 -0.260 0.795
#> 446 1.172 1.299 TRUE 0.127 0.634 0.201 0.841
#> 447 -2.133 -2.133 TRUE 0.000 0.814 0.000 1
#> 448 0.171 -0.076 TRUE -0.248 0.487 -0.509 0.611
#> 449 -1.035 -0.602 TRUE 0.433 0.536 0.808 0.419
#> 450 -1.710 -0.945 TRUE 0.765 0.632 1.210 0.226
#> 451 1.946 1.587 TRUE -0.359 0.743 -0.483 0.629
#> 452 -0.348 -0.893 TRUE -0.544 0.515 -1.056 0.291
#> 453 -0.248 0.158 TRUE 0.406 0.487 0.833 0.405
#> 454 -0.865 -0.051 TRUE 0.814 0.511 1.594 0.111
#> 455 1.527 1.389 TRUE -0.138 0.678 -0.204 0.839
#> 456 0.432 0.178 TRUE -0.254 0.501 -0.507 0.612
#> 457 -0.794 -0.264 TRUE 0.530 0.507 1.046 0.296
#> 458 -1.586 -0.841 TRUE 0.745 0.609 1.223 0.221
#> 459 -1.878 -1.587 TRUE 0.290 0.713 0.407 0.684
#> 460 1.909 1.652 TRUE -0.256 0.746 -0.344 0.731
#> 461 0.889 1.301 TRUE 0.412 0.610 0.675 0.5
#> 462 1.341 0.591 TRUE -0.750 0.595 -1.260 0.208
#> 463 0.457 0.746 TRUE 0.289 0.532 0.544 0.587
#> 464 0.713 0.733 TRUE 0.020 0.547 0.037 0.971
#> 465 -0.649 -0.029 TRUE 0.620 0.497 1.247 0.212
#> 466 -0.197 -0.976 TRUE -0.780 0.520 -1.500 0.134
#> 467 1.252 1.003 TRUE -0.248 0.615 -0.404 0.686
#> 468 -1.250 -1.442 TRUE -0.192 0.623 -0.308 0.758
#> 469 -1.629 -0.540 TRUE 1.089 0.601 1.813 0.07
#> 470 0.715 -0.029 TRUE -0.744 0.515 -1.445 0.149
#> 471 -0.998 -0.921 TRUE 0.076 0.551 0.139 0.89
#> 472 -0.582 -0.500 TRUE 0.081 0.501 0.163 0.871
#> 473 2.251 1.953 TRUE -0.297 0.815 -0.365 0.715
#> 474 -0.482 -0.279 TRUE 0.203 0.491 0.414 0.679
#> 475 -1.862 -1.629 TRUE 0.233 0.716 0.326 0.745
#> 476 0.921 0.585 TRUE -0.336 0.553 -0.608 0.543
#> 477 1.069 0.020 TRUE -1.050 0.547 -1.919 0.055
#> 478 1.009 0.246 TRUE -0.763 0.546 -1.398 0.162
#> 479 0.217 0.042 TRUE -0.175 0.489 -0.358 0.72
#> 480 0.994 0.881 TRUE -0.113 0.580 -0.194 0.846
#> 481 -0.312 -0.421 TRUE -0.109 0.489 -0.223 0.823
#> 482 0.909 0.378 TRUE -0.532 0.542 -0.981 0.326
#> 483 1.066 1.160 TRUE 0.095 0.611 0.155 0.877
#> 484 0.335 0.294 TRUE -0.041 0.500 -0.081 0.935
#> 485 0.277 0.171 TRUE -0.106 0.494 -0.215 0.83
#> 486 -0.893 -0.448 TRUE 0.445 0.518 0.858 0.391
#> 487 -0.054 0.407 TRUE 0.461 0.496 0.930 0.353
#> 488 0.350 0.643 TRUE 0.293 0.520 0.563 0.573
#> 489 1.205 1.483 TRUE 0.278 0.656 0.424 0.671
#> 490 -0.380 -0.342 TRUE 0.038 0.489 0.077 0.939
#> 491 1.913 1.691 TRUE -0.222 0.750 -0.296 0.767
#> 492 -0.964 -0.877 TRUE 0.087 0.545 0.160 0.873
#> 493 1.943 1.129 TRUE -0.814 0.702 -1.160 0.246
#> 494 -0.324 -0.101 TRUE 0.224 0.485 0.461 0.645
#> 495 0.035 0.922 TRUE 0.887 0.533 1.664 0.096
#> 496 -0.703 -0.681 TRUE 0.022 0.516 0.043 0.966
#> 497 0.352 -0.369 TRUE -0.720 0.496 -1.452 0.147
#> 498 -1.276 -0.186 TRUE 1.090 0.549 1.984 0.047
#> 499 -0.250 -0.190 TRUE 0.060 0.484 0.124 0.902
#> 500 -0.481 0.225 TRUE 0.706 0.495 1.426 0.154
#> 501 0.372 1.213 TRUE 0.841 0.571 1.474 0.14
#> 502 0.379 -0.077 TRUE -0.456 0.494 -0.921 0.357
#> 503 -2.133 -1.854 TRUE 0.279 0.778 0.358 0.72
#> 504 -1.143 -0.860 TRUE 0.283 0.560 0.504 0.614
#> 505 -1.026 -0.657 TRUE 0.369 0.537 0.686 0.493
#> 506 0.167 0.142 TRUE -0.025 0.489 -0.051 0.959
#> 507 1.540 1.252 TRUE -0.289 0.667 -0.433 0.665
#> 508 0.578 0.763 TRUE 0.185 0.540 0.342 0.733
#> 509 -0.724 -0.547 TRUE 0.177 0.510 0.347 0.728
#> 510 -0.371 0.078 TRUE 0.448 0.488 0.919 0.358
#> 511 -0.788 0.044 TRUE 0.832 0.506 1.642 0.101
#> 512 -0.383 -0.007 TRUE 0.376 0.487 0.772 0.44
#> 513 -0.862 -0.715 TRUE 0.147 0.528 0.279 0.78
#> 514 -0.802 -0.158 TRUE 0.644 0.506 1.272 0.203
#> 515 -0.100 0.190 TRUE 0.291 0.487 0.597 0.551
#> 516 1.452 1.364 TRUE -0.088 0.668 -0.132 0.895
#> 517 0.649 0.480 TRUE -0.169 0.526 -0.321 0.748
#> 518 -0.306 0.930 TRUE 1.237 0.535 2.313 0.021
#> 519 0.535 0.813 TRUE 0.278 0.541 0.514 0.607
#> 520 0.522 -0.375 TRUE -0.897 0.505 -1.776 0.076
#> 521 0.695 0.308 TRUE -0.386 0.522 -0.741 0.459
#> 522 -0.637 -1.638 TRUE -1.001 0.606 -1.653 0.098
#> 523 1.331 0.928 TRUE -0.403 0.617 -0.653 0.514
#> 524 0.546 0.643 TRUE 0.098 0.529 0.185 0.854
#> 525 0.704 0.739 TRUE 0.035 0.546 0.064 0.949
#> 526 1.209 0.427 TRUE -0.782 0.573 -1.365 0.172
#> 527 0.379 -0.010 TRUE -0.389 0.495 -0.786 0.432
#> 528 0.838 1.211 TRUE 0.374 0.597 0.625 0.532
#> 529 0.593 0.194 TRUE -0.399 0.511 -0.780 0.435
#> 530 0.020 0.090 TRUE 0.070 0.485 0.145 0.885
#> 531 0.203 -0.429 TRUE -0.632 0.492 -1.283 0.2
#> 532 2.251 2.251 TRUE 0.000 0.846 0.000 1
#> 533 1.245 0.443 TRUE -0.803 0.577 -1.391 0.164
#> 534 -0.528 -0.402 TRUE 0.127 0.495 0.255 0.798
#> 535 1.972 1.662 TRUE -0.310 0.754 -0.411 0.681
#> 536 0.332 0.387 TRUE 0.056 0.504 0.110 0.912
#> 537 -0.121 -0.518 TRUE -0.397 0.491 -0.809 0.419
#> 538 -0.691 -0.914 TRUE -0.223 0.530 -0.421 0.674
#> 539 -0.274 -0.317 TRUE -0.043 0.486 -0.088 0.93
#> 540 0.243 0.334 TRUE 0.091 0.498 0.183 0.855
#> 541 -1.086 -0.472 TRUE 0.614 0.535 1.148 0.251
#> 542 -1.503 -1.315 TRUE 0.188 0.637 0.295 0.768
#> 543 -0.783 -0.861 TRUE -0.078 0.532 -0.146 0.884
#> 544 0.389 0.053 TRUE -0.336 0.496 -0.678 0.498
#> 545 -0.874 -0.738 TRUE 0.136 0.530 0.256 0.798
#> 546 0.255 -0.022 TRUE -0.276 0.490 -0.565 0.572
#> 547 0.775 0.411 TRUE -0.365 0.532 -0.686 0.493
#> 548 0.621 1.013 TRUE 0.392 0.564 0.695 0.487
#> 549 0.400 -0.168 TRUE -0.568 0.495 -1.147 0.251
#> 550 0.238 0.260 TRUE 0.021 0.495 0.043 0.966
#> 551 -0.351 -1.496 TRUE -1.145 0.578 -1.981 0.048
#> 552 0.730 0.617 TRUE -0.113 0.540 -0.209 0.834
#> 553 0.138 0.902 TRUE 0.764 0.533 1.434 0.152
#> 554 0.582 0.407 TRUE -0.175 0.518 -0.338 0.736
#> 555 -1.418 -1.367 TRUE 0.052 0.632 0.082 0.935
#> 556 -0.275 0.317 TRUE 0.592 0.493 1.201 0.23
#> 557 0.015 0.366 TRUE 0.351 0.494 0.711 0.477
#> 558 -0.275 0.369 TRUE 0.644 0.495 1.300 0.193
#> 559 0.223 0.337 TRUE 0.114 0.498 0.229 0.819
#> 560 1.953 1.654 TRUE -0.299 0.751 -0.398 0.69
#> 561 0.361 0.280 TRUE -0.081 0.501 -0.161 0.872
#> 562 0.330 -0.254 TRUE -0.584 0.493 -1.185 0.236
#> 563 -1.228 -0.661 TRUE 0.567 0.557 1.018 0.309
#> 564 -1.058 -2.133 TRUE -1.075 0.701 -1.532 0.125
#> 565 0.741 0.497 TRUE -0.244 0.534 -0.458 0.647
#> 566 -1.165 -1.023 TRUE 0.142 0.574 0.247 0.805
#> 567 1.542 1.147 TRUE -0.395 0.657 -0.600 0.548
#> 568 -1.165 -1.363 TRUE -0.198 0.607 -0.326 0.744
#> 569 1.449 1.913 TRUE 0.464 0.726 0.639 0.523
#> 570 0.106 -0.181 TRUE -0.287 0.485 -0.592 0.554
#> 571 0.962 0.430 TRUE -0.532 0.549 -0.969 0.332
#> 572 -0.139 -0.427 TRUE -0.288 0.488 -0.590 0.555
#> 573 0.981 1.413 TRUE 0.432 0.629 0.686 0.493
#> 574 -0.474 0.294 TRUE 0.767 0.497 1.544 0.123
#> 575 -0.743 -1.588 TRUE -0.846 0.604 -1.400 0.161
#> 576 0.103 0.741 TRUE 0.638 0.519 1.229 0.219
#> 577 0.463 0.418 TRUE -0.045 0.512 -0.088 0.93
#> 578 1.481 0.628 TRUE -0.853 0.613 -1.393 0.164
#> 579 -0.748 -0.130 TRUE 0.618 0.503 1.230 0.219
#> 580 0.257 1.455 TRUE 1.197 0.594 2.017 0.044
#> 581 0.236 -0.064 TRUE -0.301 0.489 -0.615 0.538
#> 582 -0.637 0.411 TRUE 1.049 0.509 2.059 0.039
#> 583 0.094 0.433 TRUE 0.339 0.499 0.680 0.497
#> 584 1.215 1.517 TRUE 0.302 0.661 0.457 0.647
#> 585 -0.304 -0.499 TRUE -0.194 0.492 -0.395 0.693
#> 586 -0.435 -0.073 TRUE 0.362 0.488 0.741 0.458
#> 587 0.315 0.181 TRUE -0.134 0.496 -0.270 0.787
#> 588 -0.147 -0.331 TRUE -0.184 0.485 -0.379 0.705
#> 589 -0.121 -0.801 TRUE -0.680 0.506 -1.344 0.179
#> 590 0.676 0.559 TRUE -0.117 0.532 -0.220 0.825
#> 591 0.901 0.639 TRUE -0.261 0.555 -0.471 0.637
#> 592 1.913 1.036 TRUE -0.877 0.691 -1.269 0.205
#> 593 -0.701 -0.253 TRUE 0.449 0.501 0.895 0.371
#> 594 -0.922 -1.165 TRUE -0.242 0.566 -0.428 0.669
#> 595 -1.004 -0.647 TRUE 0.357 0.535 0.667 0.505
#> 596 -1.060 -1.065 TRUE -0.005 0.568 -0.009 0.993
#> 597 -0.914 -1.003 TRUE -0.088 0.551 -0.160 0.873
#> 598 -0.097 -0.722 TRUE -0.625 0.501 -1.247 0.213
#> 599 -0.118 0.737 TRUE 0.855 0.517 1.654 0.098
#> 600 -0.269 0.290 TRUE 0.560 0.492 1.138 0.255
#> 601 -0.051 0.470 TRUE 0.521 0.499 1.044 0.296
#> 602 0.229 0.035 TRUE -0.194 0.489 -0.396 0.692
#> 603 0.730 -0.024 TRUE -0.754 0.517 -1.461 0.144
#> 604 0.195 0.251 TRUE 0.056 0.494 0.113 0.91
#> 605 -1.398 -1.004 TRUE 0.394 0.597 0.659 0.51
#> 606 0.921 0.746 TRUE -0.175 0.564 -0.310 0.757
#> 607 -1.645 -1.876 TRUE -0.230 0.719 -0.320 0.749
#> 608 -1.379 -1.598 TRUE -0.219 0.655 -0.335 0.738
#> 609 -0.672 -0.803 TRUE -0.131 0.521 -0.251 0.802
#> 610 1.000 0.050 TRUE -0.950 0.541 -1.757 0.079
#> 611 -0.460 -0.658 TRUE -0.197 0.503 -0.392 0.695
#> 612 0.731 1.691 TRUE 0.960 0.643 1.492 0.136
#> 613 -0.333 0.703 TRUE 1.036 0.516 2.007 0.045
#> 614 1.628 0.936 TRUE -0.692 0.650 -1.065 0.287
#> 615 -0.274 -0.716 TRUE -0.442 0.502 -0.880 0.379
#> 616 0.386 0.085 TRUE -0.301 0.496 -0.607 0.544
#> 617 -0.730 -1.334 TRUE -0.604 0.572 -1.057 0.291
#> 618 -0.234 -0.437 TRUE -0.203 0.489 -0.414 0.679
#> 619 -1.232 -1.502 TRUE -0.270 0.629 -0.430 0.667
#> 620 -0.462 -1.092 TRUE -0.629 0.536 -1.175 0.24
#> 621 -0.197 0.066 TRUE 0.264 0.485 0.544 0.586
#> 622 1.224 1.218 TRUE -0.006 0.631 -0.009 0.993
#> 623 -0.952 -1.432 TRUE -0.481 0.597 -0.805 0.421
#> 624 0.552 0.836 TRUE 0.284 0.544 0.522 0.602
#> 625 0.293 0.176 TRUE -0.116 0.495 -0.235 0.814
#> 626 0.716 0.549 TRUE -0.166 0.535 -0.311 0.756
#> 627 -0.985 -0.284 TRUE 0.702 0.522 1.345 0.179
#> 628 -0.589 -0.347 TRUE 0.242 0.497 0.487 0.626
#> 629 0.885 -0.024 TRUE -0.909 0.529 -1.717 0.086
#> 630 -1.492 -1.331 TRUE 0.161 0.637 0.252 0.801
#> 631 -1.367 -1.336 TRUE 0.031 0.624 0.050 0.96
#> 632 -0.279 -0.738 TRUE -0.459 0.503 -0.912 0.362
#> 633 -0.351 -0.966 TRUE -0.614 0.521 -1.179 0.239
#> 634 0.462 1.675 TRUE 1.213 0.627 1.934 0.053
#> 635 1.049 0.838 TRUE -0.211 0.582 -0.362 0.717
#> 636 -0.067 0.125 TRUE 0.191 0.485 0.394 0.693
#> 637 -1.318 -1.331 TRUE -0.013 0.618 -0.021 0.983
#> 638 0.704 0.759 TRUE 0.055 0.548 0.100 0.92
#> 639 -0.050 -0.640 TRUE -0.590 0.497 -1.187 0.235
#> 640 -1.609 -0.909 TRUE 0.700 0.616 1.136 0.256
#> 641 0.910 1.482 TRUE 0.572 0.632 0.906 0.365
#> 642 -0.929 -1.645 TRUE -0.716 0.623 -1.150 0.25
#> 643 0.375 0.565 TRUE 0.190 0.516 0.368 0.713
#> 644 -0.030 -0.471 TRUE -0.441 0.489 -0.902 0.367
#> 645 -1.407 -1.070 TRUE 0.337 0.603 0.559 0.576
#> 646 -1.002 -1.645 TRUE -0.644 0.628 -1.025 0.305
#> 647 -1.471 -0.696 TRUE 0.774 0.587 1.320 0.187
#> 648 0.116 -0.240 TRUE -0.356 0.486 -0.732 0.464
#> 649 -0.181 -0.067 TRUE 0.113 0.483 0.235 0.814
#> 650 1.453 1.254 TRUE -0.199 0.658 -0.302 0.763
#> 651 -0.322 0.054 TRUE 0.376 0.486 0.774 0.439
#> 652 -0.192 -0.175 TRUE 0.017 0.483 0.035 0.972
#> 653 1.345 1.379 TRUE 0.034 0.659 0.052 0.959
#> 654 0.965 0.397 TRUE -0.568 0.547 -1.037 0.3
#> 655 0.880 1.972 TRUE 1.091 0.687 1.589 0.112
#> 656 -0.197 0.812 TRUE 1.008 0.523 1.928 0.054
#> 657 0.507 0.640 TRUE 0.133 0.527 0.252 0.801
#> 658 -0.456 0.369 TRUE 0.825 0.500 1.651 0.099
#> 659 0.111 0.217 TRUE 0.105 0.490 0.214 0.83
#> 660 0.526 0.093 TRUE -0.433 0.504 -0.858 0.391
#> 661 -0.484 -0.488 TRUE -0.004 0.497 -0.009 0.993
#> 662 -0.289 -0.752 TRUE -0.462 0.505 -0.917 0.359
#> 663 -0.383 -0.813 TRUE -0.430 0.511 -0.842 0.4
#> 664 0.586 -0.004 TRUE -0.590 0.506 -1.166 0.244
#> 665 1.407 1.835 TRUE 0.428 0.714 0.600 0.549
#> 666 -0.147 -0.641 TRUE -0.493 0.497 -0.993 0.321
#> 667 -1.346 -1.312 TRUE 0.034 0.619 0.055 0.956
#> 668 1.019 0.311 TRUE -0.708 0.549 -1.290 0.197
#> 669 -0.522 -0.349 TRUE 0.173 0.494 0.351 0.726
#> 670 0.242 0.450 TRUE 0.208 0.504 0.413 0.679
#> 671 0.602 0.536 TRUE -0.066 0.526 -0.125 0.901
#> 672 1.255 2.251 TRUE 0.996 0.749 1.329 0.184
#> 673 0.594 -0.166 TRUE -0.760 0.507 -1.500 0.134
#> 674 0.757 1.190 TRUE 0.433 0.590 0.735 0.463
#> 675 -0.478 -1.432 TRUE -0.954 0.573 -1.664 0.096
#> 676 -0.020 -0.632 TRUE -0.612 0.497 -1.232 0.218
#> 677 0.100 0.436 TRUE 0.336 0.499 0.673 0.501
#> 678 -0.399 -0.212 TRUE 0.186 0.487 0.383 0.702
#> 679 -1.058 -0.412 TRUE 0.646 0.531 1.216 0.224
#> 680 -1.485 -1.023 TRUE 0.461 0.609 0.758 0.449
#> 681 0.618 -0.023 TRUE -0.642 0.508 -1.262 0.207
#> 682 -0.911 0.454 TRUE 1.366 0.529 2.583 0.01
#> 683 -0.943 -0.748 TRUE 0.195 0.536 0.365 0.715
#> 684 -0.153 -0.451 TRUE -0.297 0.489 -0.609 0.543
#> 685 0.573 0.336 TRUE -0.236 0.514 -0.459 0.646
#> 686 1.455 1.943 TRUE 0.489 0.730 0.669 0.503
#> 687 0.087 0.394 TRUE 0.308 0.497 0.619 0.536
#> 688 -0.881 0.082 TRUE 0.963 0.514 1.875 0.061
#> 689 -0.626 -1.032 TRUE -0.405 0.536 -0.756 0.45
#> 690 -1.139 -0.756 TRUE 0.383 0.553 0.693 0.488
#> 691 0.306 0.724 TRUE 0.418 0.524 0.798 0.425
#> 692 -0.600 -1.586 TRUE -0.986 0.597 -1.651 0.099
#> 693 -0.375 0.047 TRUE 0.422 0.487 0.867 0.386
#> 694 0.473 0.095 TRUE -0.378 0.501 -0.754 0.451
#> 695 0.439 1.029 TRUE 0.590 0.555 1.063 0.288
#> 696 1.005 1.040 TRUE 0.035 0.595 0.059 0.953
#> 697 1.188 0.386 TRUE -0.802 0.569 -1.410 0.159
#> 698 -1.365 -1.360 TRUE 0.005 0.626 0.009 0.993
#> 699 0.120 0.897 TRUE 0.777 0.532 1.459 0.144
#> 700 0.318 0.863 TRUE 0.544 0.535 1.017 0.309
#> 701 -1.233 -1.258 TRUE -0.024 0.602 -0.040 0.968
#> 702 2.251 2.251 TRUE 0.000 0.846 0.000 1
#> 703 -0.510 0.053 TRUE 0.563 0.492 1.144 0.252
#> 704 -0.246 0.674 TRUE 0.920 0.513 1.794 0.073
#> 705 -0.700 -0.621 TRUE 0.079 0.512 0.154 0.877
#> 706 -1.511 -1.302 TRUE 0.209 0.636 0.329 0.742
#> 707 0.660 1.191 TRUE 0.532 0.583 0.912 0.362
#> 708 -0.753 -0.508 TRUE 0.244 0.511 0.479 0.632
#> 709 -0.247 -0.295 TRUE -0.048 0.485 -0.098 0.922
#> 710 0.946 1.648 TRUE 0.702 0.653 1.075 0.282
#> 711 -1.351 -1.710 TRUE -0.359 0.666 -0.539 0.59
#> 712 -0.675 -0.852 TRUE -0.177 0.525 -0.338 0.736
#> 713 -0.774 -1.044 TRUE -0.271 0.546 -0.496 0.62
#> 714 0.994 1.190 TRUE 0.196 0.608 0.323 0.747
#> 715 0.364 0.165 TRUE -0.198 0.497 -0.399 0.69
#> 716 -0.221 -0.748 TRUE -0.527 0.503 -1.047 0.295
#> 717 -0.917 -1.552 TRUE -0.635 0.610 -1.042 0.297
#> 718 -1.316 -0.954 TRUE 0.362 0.584 0.619 0.536
#> 719 -1.452 -0.519 TRUE 0.933 0.577 1.618 0.106
#> 720 -1.091 -0.700 TRUE 0.391 0.546 0.717 0.473
#> 721 0.115 0.341 TRUE 0.226 0.495 0.456 0.648
#> 722 1.150 0.604 TRUE -0.545 0.576 -0.947 0.344
#> 723 -1.331 -1.588 TRUE -0.257 0.649 -0.397 0.692
#> 724 0.350 -0.218 TRUE -0.568 0.494 -1.151 0.25
#> 725 1.288 0.920 TRUE -0.368 0.612 -0.602 0.547
#> 726 -0.385 -0.273 TRUE 0.112 0.488 0.230 0.818
#> 727 -0.237 -0.068 TRUE 0.169 0.484 0.349 0.727
#> 728 1.148 0.463 TRUE -0.686 0.568 -1.207 0.227
#> 729 0.274 0.899 TRUE 0.625 0.537 1.164 0.244
#> 730 -0.951 -0.291 TRUE 0.660 0.519 1.272 0.203
#> 731 -0.694 -0.765 TRUE -0.071 0.520 -0.136 0.892
#> 732 -0.998 -1.260 TRUE -0.262 0.582 -0.450 0.653
#> 733 -0.256 -0.708 TRUE -0.452 0.501 -0.902 0.367
#> 734 1.626 1.972 TRUE 0.346 0.750 0.461 0.645
#> 735 0.051 0.112 TRUE 0.061 0.486 0.125 0.9
#> 736 0.096 0.421 TRUE 0.324 0.498 0.651 0.515
#> 737 1.656 2.251 TRUE 0.595 0.785 0.758 0.449
#> 738 0.272 -0.694 TRUE -0.966 0.506 -1.907 0.056
#> 739 1.389 1.258 TRUE -0.131 0.651 -0.202 0.84
#> 740 -1.185 -0.865 TRUE 0.320 0.564 0.567 0.571
#> 741 1.104 0.817 TRUE -0.287 0.585 -0.490 0.624
#> 742 -0.185 -0.140 TRUE 0.046 0.483 0.094 0.925
#> 743 -0.131 -0.676 TRUE -0.545 0.498 -1.094 0.274
#> 744 1.233 0.388 TRUE -0.845 0.574 -1.474 0.14
#> 745 0.780 0.590 TRUE -0.191 0.542 -0.352 0.725
#> 746 -0.401 -0.644 TRUE -0.242 0.501 -0.484 0.628
#> 747 -0.958 -0.052 TRUE 0.906 0.518 1.748 0.08
#> 748 -1.267 -1.689 TRUE -0.422 0.655 -0.644 0.52
#> 749 -0.809 -0.426 TRUE 0.383 0.511 0.749 0.454
#> 750 1.388 0.537 TRUE -0.851 0.597 -1.424 0.154
#> 751 1.039 0.947 TRUE -0.092 0.590 -0.156 0.876
#> 752 -0.873 -0.645 TRUE 0.228 0.525 0.435 0.664
#> 753 0.054 0.368 TRUE 0.314 0.495 0.635 0.526
#> 754 1.211 0.546 TRUE -0.665 0.579 -1.150 0.25
#> 755 0.403 0.377 TRUE -0.026 0.507 -0.051 0.959
#> 756 0.477 0.660 TRUE 0.183 0.527 0.348 0.728
#> 757 0.786 -0.051 TRUE -0.837 0.521 -1.607 0.108
#> 758 0.230 0.796 TRUE 0.566 0.527 1.075 0.282
#> 759 -1.689 -2.133 TRUE -0.444 0.759 -0.584 0.559
#> 760 0.546 1.315 TRUE 0.769 0.590 1.304 0.192
#> 761 1.398 1.943 TRUE 0.546 0.725 0.752 0.452
#> 762 -1.050 -1.094 TRUE -0.044 0.570 -0.078 0.938
#> 763 0.088 -0.505 TRUE -0.593 0.492 -1.205 0.228
#> 764 1.031 0.858 TRUE -0.173 0.582 -0.297 0.766
#> 765 0.042 0.302 TRUE 0.261 0.492 0.530 0.596
#> 766 -1.401 -1.627 TRUE -0.225 0.660 -0.341 0.733
#> 767 1.008 0.958 TRUE -0.050 0.588 -0.085 0.932
#> 768 0.830 0.473 TRUE -0.356 0.539 -0.661 0.509
#> 769 1.013 0.691 TRUE -0.323 0.568 -0.568 0.57
#> 770 -0.479 -1.255 TRUE -0.776 0.553 -1.405 0.16
#> 771 -0.433 -1.192 TRUE -0.759 0.545 -1.394 0.163
#> 772 0.939 0.778 TRUE -0.160 0.568 -0.283 0.778
#> 773 0.150 0.295 TRUE 0.145 0.494 0.293 0.77
#> 774 -1.588 -1.862 TRUE -0.274 0.711 -0.385 0.7
#> 775 -1.295 -0.605 TRUE 0.690 0.562 1.228 0.219
#> 776 1.087 1.207 TRUE 0.119 0.617 0.193 0.847
#> 777 0.733 -0.209 TRUE -0.942 0.517 -1.822 0.068
#> 778 0.778 0.789 TRUE 0.011 0.555 0.020 0.984
#> 779 0.808 0.567 TRUE -0.242 0.543 -0.446 0.656
#> 780 0.606 0.012 TRUE -0.594 0.508 -1.169 0.242
#> 781 0.687 0.170 TRUE -0.517 0.517 -1.002 0.316
#> 782 -0.809 0.563 TRUE 1.372 0.528 2.601 0.009
#> 783 0.268 0.415 TRUE 0.147 0.503 0.293 0.769
#> 784 -0.424 -0.242 TRUE 0.182 0.488 0.373 0.709
#> 785 1.459 1.152 TRUE -0.307 0.649 -0.473 0.636
#> 786 0.191 0.045 TRUE -0.146 0.488 -0.299 0.765
#> 787 0.403 0.141 TRUE -0.262 0.498 -0.525 0.599
#> 788 -0.539 -0.191 TRUE 0.348 0.492 0.708 0.479
#> 789 -1.439 -1.627 TRUE -0.187 0.664 -0.282 0.778
#> 790 -1.736 -1.300 TRUE 0.436 0.664 0.656 0.512
#> 791 -1.336 -0.285 TRUE 1.051 0.557 1.887 0.059
#> 792 0.858 1.046 TRUE 0.188 0.583 0.323 0.747
#> 793 -0.993 -0.467 TRUE 0.526 0.527 0.999 0.318
#> 794 0.828 1.307 TRUE 0.479 0.607 0.789 0.43
#> 795 1.013 0.538 TRUE -0.475 0.559 -0.849 0.396
#> 796 -0.323 -0.472 TRUE -0.149 0.491 -0.304 0.761
#> 797 -0.558 -1.119 TRUE -0.561 0.542 -1.036 0.3
#> 798 -0.556 -0.604 TRUE -0.047 0.504 -0.094 0.925
#> 799 0.116 -0.123 TRUE -0.239 0.485 -0.493 0.622
#> 800 -0.155 0.220 TRUE 0.375 0.488 0.768 0.442
#> 801 -0.631 -1.284 TRUE -0.653 0.562 -1.163 0.245
#> 802 -0.420 -1.459 TRUE -1.040 0.575 -1.809 0.07
#> 803 -0.146 -0.121 TRUE 0.025 0.483 0.053 0.958
#> 804 1.320 0.787 TRUE -0.532 0.605 -0.880 0.379
#> 805 -0.598 -0.409 TRUE 0.189 0.499 0.379 0.705
#> 806 0.749 0.563 TRUE -0.186 0.538 -0.346 0.729
#> 807 -0.713 0.396 TRUE 1.109 0.513 2.163 0.031
#> 808 -0.561 -0.246 TRUE 0.315 0.494 0.639 0.523
#> 809 1.482 1.382 TRUE -0.100 0.673 -0.149 0.882
#> 810 -1.365 -0.660 TRUE 0.705 0.572 1.233 0.218
#> 811 1.035 1.486 TRUE 0.451 0.642 0.703 0.482
#> 812 0.053 0.095 TRUE 0.041 0.486 0.085 0.933
#> 813 -0.428 -1.645 TRUE -1.218 0.600 -2.031 0.042
#> 814 0.435 0.622 TRUE 0.187 0.522 0.359 0.72
#> 815 -0.318 -0.056 TRUE 0.262 0.485 0.540 0.589
#> 816 -0.273 -0.448 TRUE -0.175 0.490 -0.358 0.721
#> 817 1.041 -0.706 TRUE -1.747 0.559 -3.125 0.002
#> 818 0.108 0.189 TRUE 0.081 0.489 0.165 0.869
#> 819 -0.085 0.660 TRUE 0.745 0.511 1.459 0.145
#> 820 -0.566 -0.836 TRUE -0.270 0.518 -0.522 0.602
#> 821 0.455 0.427 TRUE -0.028 0.512 -0.054 0.957
#> 822 -0.163 0.496 TRUE 0.659 0.501 1.316 0.188
#> 823 -1.139 -1.117 TRUE 0.022 0.580 0.037 0.97
#> 824 1.382 1.691 TRUE 0.309 0.695 0.445 0.657
#> 825 -0.600 -0.701 TRUE -0.101 0.511 -0.197 0.844
#> 826 -0.806 -0.478 TRUE 0.329 0.513 0.641 0.521
#> 827 0.879 0.730 TRUE -0.148 0.559 -0.266 0.791
#> 828 -1.219 -0.412 TRUE 0.807 0.547 1.476 0.14
#> 829 -1.225 -1.329 TRUE -0.104 0.609 -0.171 0.864
#> 830 2.251 1.221 TRUE -1.029 0.746 -1.379 0.168
#> 831 -0.259 -0.839 TRUE -0.580 0.510 -1.138 0.255
#> 832 0.500 1.441 TRUE 0.941 0.601 1.565 0.118
#> 833 0.840 0.970 TRUE 0.131 0.575 0.227 0.82
#> 834 1.077 1.403 TRUE 0.327 0.636 0.513 0.608
#> 835 -0.578 -0.846 TRUE -0.268 0.520 -0.515 0.606
#> 836 1.234 1.145 TRUE -0.089 0.625 -0.143 0.887
#> 837 -0.229 -0.177 TRUE 0.053 0.484 0.109 0.913
#> 838 0.014 1.194 TRUE 1.180 0.560 2.108 0.035
#> 839 -0.100 0.305 TRUE 0.405 0.491 0.825 0.41
#> 840 1.207 1.266 TRUE 0.059 0.634 0.092 0.926
#> 841 0.806 0.971 TRUE 0.165 0.573 0.289 0.773
#> 842 0.451 0.358 TRUE -0.093 0.508 -0.183 0.855
#> 843 1.013 1.078 TRUE 0.065 0.599 0.109 0.913
#> 844 -0.058 -0.353 TRUE -0.294 0.486 -0.606 0.544
#> 845 0.221 -0.099 TRUE -0.320 0.488 -0.655 0.513
#> 846 0.114 0.463 TRUE 0.349 0.501 0.697 0.486
#> 847 -0.330 -0.571 TRUE -0.241 0.496 -0.486 0.627
#> 848 -0.461 -1.397 TRUE -0.936 0.568 -1.646 0.1
#> 849 -0.883 -0.892 TRUE -0.009 0.540 -0.017 0.986
#> 850 1.913 1.113 TRUE -0.799 0.697 -1.147 0.251
#> 851 0.872 0.853 TRUE -0.019 0.568 -0.033 0.973
#> 852 0.494 -0.364 TRUE -0.858 0.503 -1.705 0.088
#> 853 -0.079 0.008 TRUE 0.087 0.483 0.179 0.858
#> 854 -0.475 -0.220 TRUE 0.255 0.490 0.520 0.603
#> 855 -0.148 -0.304 TRUE -0.156 0.485 -0.322 0.747
#> 856 0.442 0.549 TRUE 0.106 0.518 0.206 0.837
#> 857 0.031 -0.432 TRUE -0.463 0.489 -0.946 0.344
#> 858 0.520 -0.123 TRUE -0.643 0.502 -1.281 0.2
#> 859 0.007 0.026 TRUE 0.018 0.484 0.038 0.97
#> 860 -0.936 -0.471 TRUE 0.465 0.522 0.890 0.374
#> 861 -0.997 -1.183 TRUE -0.186 0.574 -0.324 0.746
#> 862 0.455 0.660 TRUE 0.205 0.526 0.390 0.696
#> 863 -1.265 -0.726 TRUE 0.538 0.564 0.954 0.34
#> 864 -0.363 -0.956 TRUE -0.593 0.521 -1.139 0.255
#> 865 0.074 0.378 TRUE 0.304 0.496 0.614 0.539
#> 866 0.482 0.477 TRUE -0.005 0.516 -0.010 0.992
#> 867 -0.050 -0.009 TRUE 0.041 0.483 0.084 0.933
#> 868 0.435 0.509 TRUE 0.074 0.515 0.144 0.885
#> 869 -0.075 -0.572 TRUE -0.497 0.493 -1.008 0.313
#> 870 0.613 0.563 TRUE -0.050 0.528 -0.095 0.924
#> 871 0.563 0.482 TRUE -0.081 0.521 -0.155 0.877
#> 872 -0.196 -0.026 TRUE 0.169 0.483 0.350 0.726
#> 873 -1.876 -1.854 TRUE 0.022 0.744 0.029 0.977
#> 874 -0.394 0.301 TRUE 0.695 0.495 1.405 0.16
#> 875 0.727 1.040 TRUE 0.313 0.573 0.547 0.585
#> 876 -0.108 -0.295 TRUE -0.187 0.484 -0.386 0.699
#> 877 1.165 1.296 TRUE 0.131 0.633 0.206 0.837
#> 878 0.629 0.789 TRUE 0.160 0.545 0.293 0.769
#> 879 -0.390 -0.092 TRUE 0.298 0.487 0.612 0.54
#> 880 -0.691 -1.325 TRUE -0.633 0.569 -1.113 0.266
#> 881 -0.745 -1.503 TRUE -0.758 0.593 -1.279 0.201
#> 882 -0.548 -0.050 TRUE 0.498 0.492 1.012 0.311
#> 883 0.196 0.117 TRUE -0.078 0.490 -0.160 0.873
#> 884 -0.735 -0.782 TRUE -0.047 0.523 -0.091 0.928
#> 885 0.730 0.629 TRUE -0.101 0.541 -0.187 0.852
#> 886 -1.062 -0.461 TRUE 0.601 0.533 1.128 0.259
#> 887 -1.097 -0.144 TRUE 0.953 0.530 1.796 0.073
#> 888 -0.074 -0.490 TRUE -0.415 0.490 -0.848 0.396
#> 889 -1.638 -0.667 TRUE 0.971 0.607 1.600 0.11
#> 890 0.941 0.240 TRUE -0.701 0.539 -1.300 0.193
#> 891 -0.018 -0.610 TRUE -0.592 0.495 -1.195 0.232
#> 892 0.188 0.162 TRUE -0.026 0.491 -0.053 0.958
#> 893 1.411 1.249 TRUE -0.162 0.653 -0.248 0.804
#> 894 0.318 0.314 TRUE -0.003 0.500 -0.007 0.995
#> 895 -0.233 0.079 TRUE 0.312 0.485 0.643 0.52
#> 896 1.000 0.554 TRUE -0.445 0.559 -0.797 0.425
#> 897 1.345 1.205 TRUE -0.140 0.642 -0.218 0.827
#> 898 -0.526 -0.170 TRUE 0.356 0.491 0.725 0.468
#> 899 -0.024 -0.351 TRUE -0.326 0.486 -0.672 0.502
#> 900 -0.598 -0.895 TRUE -0.297 0.524 -0.567 0.571
#> 901 -0.600 -0.714 TRUE -0.114 0.512 -0.223 0.824
#> 902 1.254 1.972 TRUE 0.718 0.716 1.004 0.316
#> 903 1.261 1.943 TRUE 0.682 0.713 0.957 0.339
#> 904 0.351 -0.065 TRUE -0.416 0.493 -0.844 0.399
#> 905 -0.637 -0.612 TRUE 0.026 0.508 0.050 0.96
#> 906 1.880 2.251 TRUE 0.371 0.807 0.459 0.646
#> 907 0.911 0.285 TRUE -0.626 0.538 -1.164 0.245
#> 908 -0.016 -0.820 TRUE -0.803 0.508 -1.582 0.114
#> 909 -1.645 -2.133 TRUE -0.487 0.754 -0.646 0.518
#> 910 1.420 0.067 TRUE -1.353 0.585 -2.311 0.021
#> 911 -1.644 -2.133 TRUE -0.488 0.754 -0.647 0.517
#> 912 2.251 1.425 TRUE -0.825 0.764 -1.080 0.28
#> 913 -1.081 -1.503 TRUE -0.422 0.616 -0.686 0.493
#> 914 1.152 1.361 TRUE 0.208 0.639 0.326 0.744
#> 915 0.771 1.055 TRUE 0.284 0.578 0.491 0.623
#> 916 1.599 0.643 TRUE -0.956 0.627 -1.525 0.127
#> 917 1.040 1.413 TRUE 0.373 0.634 0.588 0.557
#> 918 0.986 1.519 TRUE 0.533 0.641 0.831 0.406
#> 919 0.638 0.057 TRUE -0.581 0.511 -1.137 0.255
#> 920 0.248 -0.197 TRUE -0.444 0.489 -0.908 0.364
#> 921 -0.914 -1.408 TRUE -0.494 0.592 -0.835 0.404
#> 922 -0.454 0.094 TRUE 0.547 0.491 1.116 0.264
#> 923 0.330 0.111 TRUE -0.219 0.494 -0.442 0.658
#> 924 1.650 1.589 TRUE -0.062 0.711 -0.087 0.931
#> 925 -0.898 -0.861 TRUE 0.037 0.539 0.069 0.945
#> 926 1.972 1.814 TRUE -0.158 0.770 -0.205 0.838
#> 927 -0.490 -0.761 TRUE -0.271 0.510 -0.532 0.595
#> 928 -0.261 -1.052 TRUE -0.791 0.527 -1.500 0.134
#> 929 0.965 1.972 TRUE 1.007 0.693 1.454 0.146
#> 930 0.869 -0.077 TRUE -0.946 0.528 -1.794 0.073
#> 931 0.353 0.208 TRUE -0.145 0.498 -0.291 0.771
#> 932 0.358 0.091 TRUE -0.267 0.495 -0.540 0.589
#> 933 0.426 0.718 TRUE 0.291 0.528 0.551 0.581
#> 934 -0.155 -0.759 TRUE -0.604 0.504 -1.199 0.231
#> 935 0.768 0.876 TRUE 0.108 0.562 0.192 0.848
#> 936 -0.530 -0.519 TRUE 0.011 0.500 0.021 0.983
#> 937 -0.749 -0.721 TRUE 0.028 0.520 0.054 0.957
#> 938 -0.231 -0.155 TRUE 0.076 0.484 0.158 0.875
#> 939 -1.279 -1.645 TRUE -0.367 0.651 -0.564 0.573
#> 940 0.243 0.142 TRUE -0.101 0.492 -0.205 0.838
#> 941 0.559 0.936 TRUE 0.377 0.553 0.682 0.495
#> 942 0.670 0.744 TRUE 0.075 0.544 0.137 0.891
#> 943 0.261 -0.270 TRUE -0.531 0.491 -1.083 0.279
#> 944 0.843 0.495 TRUE -0.348 0.542 -0.642 0.521
#> 945 0.042 0.335 TRUE 0.293 0.493 0.593 0.553
#> 946 0.263 0.241 TRUE -0.022 0.495 -0.045 0.964
#> 947 0.355 -0.018 TRUE -0.373 0.494 -0.755 0.45
#> 948 0.052 0.581 TRUE 0.529 0.507 1.043 0.297
#> 949 -1.795 -1.470 TRUE 0.325 0.689 0.472 0.637
#> 950 -0.394 0.473 TRUE 0.867 0.503 1.724 0.085
#> 951 -0.390 -0.468 TRUE -0.078 0.493 -0.159 0.874
#> 952 0.982 0.348 TRUE -0.633 0.547 -1.158 0.247
#> 953 -0.554 -1.070 TRUE -0.516 0.537 -0.961 0.337
#> 954 -1.586 -0.702 TRUE 0.884 0.602 1.470 0.142
#> 955 -0.619 -0.916 TRUE -0.297 0.527 -0.564 0.573
#> 956 -1.292 -1.290 TRUE 0.002 0.611 0.004 0.997
#> 957 -0.987 -0.726 TRUE 0.261 0.538 0.484 0.628
#> 958 -0.629 -0.651 TRUE -0.023 0.510 -0.044 0.965
#> 959 0.723 1.451 TRUE 0.728 0.615 1.183 0.237
#> 960 -0.701 -0.579 TRUE 0.122 0.510 0.239 0.811
#> 961 -1.264 -1.638 TRUE -0.374 0.648 -0.577 0.564
#> 962 0.443 0.162 TRUE -0.281 0.501 -0.560 0.576
#> 963 -0.730 -1.011 TRUE -0.280 0.540 -0.519 0.603
#> 964 1.458 0.276 TRUE -1.182 0.594 -1.988 0.047
#> 965 -0.922 -0.508 TRUE 0.414 0.522 0.793 0.428
#> 966 0.580 1.124 TRUE 0.544 0.572 0.951 0.341
#> 967 1.076 1.167 TRUE 0.091 0.613 0.149 0.882
#> 968 0.439 -0.218 TRUE -0.657 0.498 -1.320 0.187
#> 969 0.935 0.495 TRUE -0.440 0.549 -0.801 0.423
#> 970 0.737 1.210 TRUE 0.473 0.590 0.801 0.423
#> 971 -0.743 -0.472 TRUE 0.271 0.509 0.534 0.594
#> 972 1.208 1.205 TRUE -0.003 0.628 -0.004 0.996
#> 973 -1.259 -1.821 TRUE -0.562 0.672 -0.836 0.403
#> 974 -0.829 -0.870 TRUE -0.042 0.535 -0.078 0.938
#> 975 -0.389 -1.197 TRUE -0.809 0.544 -1.487 0.137
#> 976 0.547 0.480 TRUE -0.067 0.520 -0.129 0.897
#> 977 -0.060 0.378 TRUE 0.438 0.494 0.886 0.375
#> 978 -1.503 -0.950 TRUE 0.553 0.606 0.913 0.361
#> 979 -1.418 -0.196 TRUE 1.222 0.566 2.159 0.031
#> 980 -0.032 -0.002 TRUE 0.030 0.484 0.062 0.951
#> 981 -0.993 -1.649 TRUE -0.656 0.627 -1.046 0.295
#> 982 -0.526 -1.183 TRUE -0.657 0.547 -1.202 0.229
#> 983 1.334 0.407 TRUE -0.928 0.585 -1.585 0.113
#> 984 1.506 1.064 TRUE -0.443 0.646 -0.685 0.494
#> 985 1.254 0.239 TRUE -1.015 0.570 -1.779 0.075
#> 986 -0.725 -1.319 TRUE -0.594 0.570 -1.042 0.297
#> 987 0.685 0.698 TRUE 0.013 0.542 0.024 0.981
#> 988 0.141 -0.361 TRUE -0.502 0.489 -1.027 0.304
#> 989 -1.366 0.469 TRUE 1.835 0.573 3.201 0.001
#> 990 -0.193 0.204 TRUE 0.397 0.488 0.814 0.416
#> 991 0.140 -0.560 TRUE -0.700 0.496 -1.413 0.158
#> 992 0.246 0.044 TRUE -0.202 0.490 -0.411 0.681
#> 993 -0.439 -0.614 TRUE -0.176 0.500 -0.351 0.726
#> 994 -1.649 -1.018 TRUE 0.631 0.629 1.003 0.316
#> 995 0.107 -0.521 TRUE -0.628 0.493 -1.273 0.203
#> 996 -0.003 -0.821 TRUE -0.818 0.508 -1.611 0.107
#> 997 -0.394 -0.621 TRUE -0.227 0.499 -0.454 0.65
#> 998 0.065 0.413 TRUE 0.348 0.497 0.699 0.485
#> 999 0.198 -0.517 TRUE -0.715 0.495 -1.443 0.149
#> 1000 -1.854 -1.519 TRUE 0.335 0.702 0.477 0.633
# 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 1.714 1.97 TRUE 0.256 0.759 0.337 0.736
# 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 2.161 2.769 TRUE 0.609 1.199 0.508 0.612
# multiple respondents
RCI(mod, predat = dat_pre[1:6,], postdat = dat_post[1:6,])
#> pre.score post.score converged diff SE z p
#> 1 1.714 1.970 TRUE 0.256 0.759 0.337 0.736
#> 2 1.406 -0.120 TRUE -1.526 0.582 -2.620 0.009
#> 3 0.960 -0.150 TRUE -1.111 0.536 -2.073 0.038
#> 4 0.302 0.202 TRUE -0.100 0.496 -0.202 0.84
#> 5 -0.973 -0.906 TRUE 0.067 0.548 0.122 0.903
#> 6 -0.797 -0.298 TRUE 0.499 0.508 0.983 0.326
# 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 1.714 1.970 TRUE 0.256 0.759 0.337 0.736 unchanged
#> 2 1.406 -0.120 TRUE -1.526 0.582 -2.620 0.009 decreased
#> 3 0.960 -0.150 TRUE -1.111 0.536 -2.073 0.038 decreased
#> 4 0.302 0.202 TRUE -0.100 0.496 -0.202 0.84 unchanged
#> 5 -0.973 -0.906 TRUE 0.067 0.548 0.122 0.903 unchanged
#> 6 -0.797 -0.298 TRUE 0.499 0.508 0.983 0.326 unchanged
######
# CTT version by omitting IRT model
# Requires either sample or population SEM's as input
(istats <- itemstats(dat_pre)$overall)
#> N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
#> 1000 9.785 4.846 0.214 0.065 0.846 1.901
SEM.alpha <- istats$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 18 19 1 2.688 0.372 0.71
#> 2 18 9 -9 2.688 -3.349 0.001
#> 3 15 9 -6 2.688 -2.232 0.026
#> 4 11 10 -1 2.688 -0.372 0.71
#> 5 4 5 1 2.688 0.372 0.71
#> 6 4 8 4 2.688 1.488 0.137
#> 7 11 8 -3 2.688 -1.116 0.264
#> 8 11 15 4 2.688 1.488 0.137
#> 9 3 3 0 2.688 0.000 1
#> 10 4 8 4 2.688 1.488 0.137
#> 11 1 5 4 2.688 1.488 0.137
#> 12 16 14 -2 2.688 -0.744 0.457
#> 13 12 10 -2 2.688 -0.744 0.457
#> 14 11 10 -1 2.688 -0.372 0.71
#> 15 17 18 1 2.688 0.372 0.71
#> 16 1 4 3 2.688 1.116 0.264
#> 17 10 8 -2 2.688 -0.744 0.457
#> 18 12 11 -1 2.688 -0.372 0.71
#> 19 15 12 -3 2.688 -1.116 0.264
#> 20 16 10 -6 2.688 -2.232 0.026
#> 21 7 6 -1 2.688 -0.372 0.71
#> 22 7 12 5 2.688 1.860 0.063
#> 23 2 4 2 2.688 0.744 0.457
#> 24 5 7 2 2.688 0.744 0.457
#> 25 14 15 1 2.688 0.372 0.71
#> 26 9 6 -3 2.688 -1.116 0.264
#> 27 17 17 0 2.688 0.000 1
#> 28 4 9 5 2.688 1.860 0.063
#> 29 14 16 2 2.688 0.744 0.457
#> 30 4 7 3 2.688 1.116 0.264
#> 31 2 0 -2 2.688 -0.744 0.457
#> 32 9 6 -3 2.688 -1.116 0.264
#> 33 20 20 0 2.688 0.000 1
#> 34 9 6 -3 2.688 -1.116 0.264
#> 35 3 4 1 2.688 0.372 0.71
#> 36 14 15 1 2.688 0.372 0.71
#> 37 8 9 1 2.688 0.372 0.71
#> 38 15 13 -2 2.688 -0.744 0.457
#> 39 9 12 3 2.688 1.116 0.264
#> 40 18 18 0 2.688 0.000 1
#> 41 11 10 -1 2.688 -0.372 0.71
#> 42 12 9 -3 2.688 -1.116 0.264
#> 43 8 7 -1 2.688 -0.372 0.71
#> 44 10 11 1 2.688 0.372 0.71
#> 45 7 10 3 2.688 1.116 0.264
#> 46 8 9 1 2.688 0.372 0.71
#> 47 6 8 2 2.688 0.744 0.457
#> 48 6 7 1 2.688 0.372 0.71
#> 49 6 8 2 2.688 0.744 0.457
#> 50 8 11 3 2.688 1.116 0.264
#> 51 13 17 4 2.688 1.488 0.137
#> 52 6 6 0 2.688 0.000 1
#> 53 19 13 -6 2.688 -2.232 0.026
#> 54 6 11 5 2.688 1.860 0.063
#> 55 9 8 -1 2.688 -0.372 0.71
#> 56 7 8 1 2.688 0.372 0.71
#> 57 9 6 -3 2.688 -1.116 0.264
#> 58 3 3 0 2.688 0.000 1
#> 59 10 8 -2 2.688 -0.744 0.457
#> 60 14 14 0 2.688 0.000 1
#> 61 12 12 0 2.688 0.000 1
#> 62 15 14 -1 2.688 -0.372 0.71
#> 63 13 12 -1 2.688 -0.372 0.71
#> 64 5 5 0 2.688 0.000 1
#> 65 5 4 -1 2.688 -0.372 0.71
#> 66 5 4 -1 2.688 -0.372 0.71
#> 67 18 14 -4 2.688 -1.488 0.137
#> 68 9 8 -1 2.688 -0.372 0.71
#> 69 11 9 -2 2.688 -0.744 0.457
#> 70 19 17 -2 2.688 -0.744 0.457
#> 71 9 5 -4 2.688 -1.488 0.137
#> 72 16 15 -1 2.688 -0.372 0.71
#> 73 10 9 -1 2.688 -0.372 0.71
#> 74 11 11 0 2.688 0.000 1
#> 75 14 10 -4 2.688 -1.488 0.137
#> 76 14 15 1 2.688 0.372 0.71
#> 77 5 4 -1 2.688 -0.372 0.71
#> 78 11 9 -2 2.688 -0.744 0.457
#> 79 15 10 -5 2.688 -1.860 0.063
#> 80 11 11 0 2.688 0.000 1
#> 81 10 8 -2 2.688 -0.744 0.457
#> 82 12 12 0 2.688 0.000 1
#> 83 11 11 0 2.688 0.000 1
#> 84 5 1 -4 2.688 -1.488 0.137
#> 85 7 9 2 2.688 0.744 0.457
#> 86 7 10 3 2.688 1.116 0.264
#> 87 3 7 4 2.688 1.488 0.137
#> 88 9 11 2 2.688 0.744 0.457
#> 89 8 9 1 2.688 0.372 0.71
#> 90 12 11 -1 2.688 -0.372 0.71
#> 91 6 1 -5 2.688 -1.860 0.063
#> 92 6 8 2 2.688 0.744 0.457
#> 93 3 5 2 2.688 0.744 0.457
#> 94 12 12 0 2.688 0.000 1
#> 95 18 16 -2 2.688 -0.744 0.457
#> 96 9 7 -2 2.688 -0.744 0.457
#> 97 8 11 3 2.688 1.116 0.264
#> 98 7 7 0 2.688 0.000 1
#> 99 12 11 -1 2.688 -0.372 0.71
#> 100 10 10 0 2.688 0.000 1
#> 101 5 5 0 2.688 0.000 1
#> 102 14 15 1 2.688 0.372 0.71
#> 103 9 9 0 2.688 0.000 1
#> 104 8 15 7 2.688 2.604 0.009
#> 105 2 3 1 2.688 0.372 0.71
#> 106 7 10 3 2.688 1.116 0.264
#> 107 12 12 0 2.688 0.000 1
#> 108 2 2 0 2.688 0.000 1
#> 109 14 13 -1 2.688 -0.372 0.71
#> 110 6 4 -2 2.688 -0.744 0.457
#> 111 15 10 -5 2.688 -1.860 0.063
#> 112 5 5 0 2.688 0.000 1
#> 113 15 18 3 2.688 1.116 0.264
#> 114 2 0 -2 2.688 -0.744 0.457
#> 115 9 12 3 2.688 1.116 0.264
#> 116 14 14 0 2.688 0.000 1
#> 117 10 7 -3 2.688 -1.116 0.264
#> 118 6 5 -1 2.688 -0.372 0.71
#> 119 12 9 -3 2.688 -1.116 0.264
#> 120 7 3 -4 2.688 -1.488 0.137
#> 121 9 12 3 2.688 1.116 0.264
#> 122 2 6 4 2.688 1.488 0.137
#> 123 9 6 -3 2.688 -1.116 0.264
#> 124 2 5 3 2.688 1.116 0.264
#> 125 12 12 0 2.688 0.000 1
#> 126 16 19 3 2.688 1.116 0.264
#> 127 13 14 1 2.688 0.372 0.71
#> 128 13 14 1 2.688 0.372 0.71
#> 129 14 15 1 2.688 0.372 0.71
#> 130 7 14 7 2.688 2.604 0.009
#> 131 10 11 1 2.688 0.372 0.71
#> 132 3 3 0 2.688 0.000 1
#> 133 15 15 0 2.688 0.000 1
#> 134 18 19 1 2.688 0.372 0.71
#> 135 2 5 3 2.688 1.116 0.264
#> 136 12 10 -2 2.688 -0.744 0.457
#> 137 12 14 2 2.688 0.744 0.457
#> 138 6 3 -3 2.688 -1.116 0.264
#> 139 13 9 -4 2.688 -1.488 0.137
#> 140 8 5 -3 2.688 -1.116 0.264
#> 141 18 17 -1 2.688 -0.372 0.71
#> 142 15 15 0 2.688 0.000 1
#> 143 7 9 2 2.688 0.744 0.457
#> 144 14 10 -4 2.688 -1.488 0.137
#> 145 3 5 2 2.688 0.744 0.457
#> 146 1 2 1 2.688 0.372 0.71
#> 147 5 6 1 2.688 0.372 0.71
#> 148 8 8 0 2.688 0.000 1
#> 149 13 15 2 2.688 0.744 0.457
#> 150 9 9 0 2.688 0.000 1
#> 151 8 9 1 2.688 0.372 0.71
#> 152 2 1 -1 2.688 -0.372 0.71
#> 153 3 3 0 2.688 0.000 1
#> 154 7 5 -2 2.688 -0.744 0.457
#> 155 16 13 -3 2.688 -1.116 0.264
#> 156 9 12 3 2.688 1.116 0.264
#> 157 15 17 2 2.688 0.744 0.457
#> 158 10 5 -5 2.688 -1.860 0.063
#> 159 8 10 2 2.688 0.744 0.457
#> 160 17 11 -6 2.688 -2.232 0.026
#> 161 14 8 -6 2.688 -2.232 0.026
#> 162 8 8 0 2.688 0.000 1
#> 163 3 5 2 2.688 0.744 0.457
#> 164 16 8 -8 2.688 -2.976 0.003
#> 165 9 7 -2 2.688 -0.744 0.457
#> 166 7 8 1 2.688 0.372 0.71
#> 167 15 15 0 2.688 0.000 1
#> 168 15 18 3 2.688 1.116 0.264
#> 169 3 2 -1 2.688 -0.372 0.71
#> 170 1 2 1 2.688 0.372 0.71
#> 171 2 0 -2 2.688 -0.744 0.457
#> 172 20 15 -5 2.688 -1.860 0.063
#> 173 10 12 2 2.688 0.744 0.457
#> 174 9 3 -6 2.688 -2.232 0.026
#> 175 5 15 10 2.688 3.721 0
#> 176 9 7 -2 2.688 -0.744 0.457
#> 177 15 16 1 2.688 0.372 0.71
#> 178 2 5 3 2.688 1.116 0.264
#> 179 18 20 2 2.688 0.744 0.457
#> 180 10 8 -2 2.688 -0.744 0.457
#> 181 6 6 0 2.688 0.000 1
#> 182 3 5 2 2.688 0.744 0.457
#> 183 9 7 -2 2.688 -0.744 0.457
#> 184 7 10 3 2.688 1.116 0.264
#> 185 6 3 -3 2.688 -1.116 0.264
#> 186 7 5 -2 2.688 -0.744 0.457
#> 187 7 4 -3 2.688 -1.116 0.264
#> 188 10 9 -1 2.688 -0.372 0.71
#> 189 17 12 -5 2.688 -1.860 0.063
#> 190 2 4 2 2.688 0.744 0.457
#> 191 16 15 -1 2.688 -0.372 0.71
#> 192 6 9 3 2.688 1.116 0.264
#> 193 10 13 3 2.688 1.116 0.264
#> 194 2 7 5 2.688 1.860 0.063
#> 195 5 3 -2 2.688 -0.744 0.457
#> 196 12 8 -4 2.688 -1.488 0.137
#> 197 5 1 -4 2.688 -1.488 0.137
#> 198 5 2 -3 2.688 -1.116 0.264
#> 199 17 17 0 2.688 0.000 1
#> 200 4 2 -2 2.688 -0.744 0.457
#> 201 13 13 0 2.688 0.000 1
#> 202 14 12 -2 2.688 -0.744 0.457
#> 203 2 2 0 2.688 0.000 1
#> 204 11 9 -2 2.688 -0.744 0.457
#> 205 10 11 1 2.688 0.372 0.71
#> 206 13 11 -2 2.688 -0.744 0.457
#> 207 17 18 1 2.688 0.372 0.71
#> 208 14 15 1 2.688 0.372 0.71
#> 209 18 18 0 2.688 0.000 1
#> 210 2 0 -2 2.688 -0.744 0.457
#> 211 9 11 2 2.688 0.744 0.457
#> 212 10 12 2 2.688 0.744 0.457
#> 213 16 14 -2 2.688 -0.744 0.457
#> 214 2 2 0 2.688 0.000 1
#> 215 3 4 1 2.688 0.372 0.71
#> 216 15 17 2 2.688 0.744 0.457
#> 217 14 12 -2 2.688 -0.744 0.457
#> 218 3 5 2 2.688 0.744 0.457
#> 219 9 8 -1 2.688 -0.372 0.71
#> 220 0 1 1 2.688 0.372 0.71
#> 221 14 12 -2 2.688 -0.744 0.457
#> 222 2 1 -1 2.688 -0.372 0.71
#> 223 5 10 5 2.688 1.860 0.063
#> 224 8 15 7 2.688 2.604 0.009
#> 225 12 14 2 2.688 0.744 0.457
#> 226 14 14 0 2.688 0.000 1
#> 227 11 11 0 2.688 0.000 1
#> 228 9 9 0 2.688 0.000 1
#> 229 17 15 -2 2.688 -0.744 0.457
#> 230 2 2 0 2.688 0.000 1
#> 231 6 9 3 2.688 1.116 0.264
#> 232 9 14 5 2.688 1.860 0.063
#> 233 13 13 0 2.688 0.000 1
#> 234 13 17 4 2.688 1.488 0.137
#> 235 13 6 -7 2.688 -2.604 0.009
#> 236 8 8 0 2.688 0.000 1
#> 237 8 9 1 2.688 0.372 0.71
#> 238 6 12 6 2.688 2.232 0.026
#> 239 9 9 0 2.688 0.000 1
#> 240 7 12 5 2.688 1.860 0.063
#> 241 18 18 0 2.688 0.000 1
#> 242 4 3 -1 2.688 -0.372 0.71
#> 243 1 2 1 2.688 0.372 0.71
#> 244 3 1 -2 2.688 -0.744 0.457
#> 245 6 5 -1 2.688 -0.372 0.71
#> 246 4 4 0 2.688 0.000 1
#> 247 17 17 0 2.688 0.000 1
#> 248 20 18 -2 2.688 -0.744 0.457
#> 249 8 10 2 2.688 0.744 0.457
#> 250 15 18 3 2.688 1.116 0.264
#> 251 15 13 -2 2.688 -0.744 0.457
#> 252 8 8 0 2.688 0.000 1
#> 253 8 8 0 2.688 0.000 1
#> 254 11 13 2 2.688 0.744 0.457
#> 255 18 16 -2 2.688 -0.744 0.457
#> 256 10 11 1 2.688 0.372 0.71
#> 257 18 16 -2 2.688 -0.744 0.457
#> 258 10 11 1 2.688 0.372 0.71
#> 259 4 3 -1 2.688 -0.372 0.71
#> 260 11 14 3 2.688 1.116 0.264
#> 261 14 11 -3 2.688 -1.116 0.264
#> 262 14 13 -1 2.688 -0.372 0.71
#> 263 19 17 -2 2.688 -0.744 0.457
#> 264 4 6 2 2.688 0.744 0.457
#> 265 17 17 0 2.688 0.000 1
#> 266 9 12 3 2.688 1.116 0.264
#> 267 4 7 3 2.688 1.116 0.264
#> 268 15 12 -3 2.688 -1.116 0.264
#> 269 7 7 0 2.688 0.000 1
#> 270 8 11 3 2.688 1.116 0.264
#> 271 1 2 1 2.688 0.372 0.71
#> 272 8 6 -2 2.688 -0.744 0.457
#> 273 6 6 0 2.688 0.000 1
#> 274 17 16 -1 2.688 -0.372 0.71
#> 275 13 11 -2 2.688 -0.744 0.457
#> 276 2 1 -1 2.688 -0.372 0.71
#> 277 9 10 1 2.688 0.372 0.71
#> 278 2 0 -2 2.688 -0.744 0.457
#> 279 11 13 2 2.688 0.744 0.457
#> 280 17 17 0 2.688 0.000 1
#> 281 16 16 0 2.688 0.000 1
#> 282 14 15 1 2.688 0.372 0.71
#> 283 15 16 1 2.688 0.372 0.71
#> 284 4 1 -3 2.688 -1.116 0.264
#> 285 17 18 1 2.688 0.372 0.71
#> 286 10 7 -3 2.688 -1.116 0.264
#> 287 12 15 3 2.688 1.116 0.264
#> 288 15 17 2 2.688 0.744 0.457
#> 289 17 15 -2 2.688 -0.744 0.457
#> 290 14 11 -3 2.688 -1.116 0.264
#> 291 15 12 -3 2.688 -1.116 0.264
#> 292 10 10 0 2.688 0.000 1
#> 293 0 2 2 2.688 0.744 0.457
#> 294 12 8 -4 2.688 -1.488 0.137
#> 295 4 7 3 2.688 1.116 0.264
#> 296 15 15 0 2.688 0.000 1
#> 297 18 17 -1 2.688 -0.372 0.71
#> 298 9 7 -2 2.688 -0.744 0.457
#> 299 18 12 -6 2.688 -2.232 0.026
#> 300 0 1 1 2.688 0.372 0.71
#> 301 4 11 7 2.688 2.604 0.009
#> 302 10 8 -2 2.688 -0.744 0.457
#> 303 5 2 -3 2.688 -1.116 0.264
#> 304 19 17 -2 2.688 -0.744 0.457
#> 305 11 6 -5 2.688 -1.860 0.063
#> 306 15 15 0 2.688 0.000 1
#> 307 10 12 2 2.688 0.744 0.457
#> 308 11 8 -3 2.688 -1.116 0.264
#> 309 10 7 -3 2.688 -1.116 0.264
#> 310 8 6 -2 2.688 -0.744 0.457
#> 311 14 15 1 2.688 0.372 0.71
#> 312 16 11 -5 2.688 -1.860 0.063
#> 313 6 4 -2 2.688 -0.744 0.457
#> 314 11 11 0 2.688 0.000 1
#> 315 7 7 0 2.688 0.000 1
#> 316 9 11 2 2.688 0.744 0.457
#> 317 7 11 4 2.688 1.488 0.137
#> 318 1 5 4 2.688 1.488 0.137
#> 319 10 9 -1 2.688 -0.372 0.71
#> 320 13 10 -3 2.688 -1.116 0.264
#> 321 13 10 -3 2.688 -1.116 0.264
#> 322 13 9 -4 2.688 -1.488 0.137
#> 323 1 2 1 2.688 0.372 0.71
#> 324 13 13 0 2.688 0.000 1
#> 325 13 13 0 2.688 0.000 1
#> 326 13 13 0 2.688 0.000 1
#> 327 7 6 -1 2.688 -0.372 0.71
#> 328 9 12 3 2.688 1.116 0.264
#> 329 13 13 0 2.688 0.000 1
#> 330 6 14 8 2.688 2.976 0.003
#> 331 12 14 2 2.688 0.744 0.457
#> 332 9 5 -4 2.688 -1.488 0.137
#> 333 13 12 -1 2.688 -0.372 0.71
#> 334 13 14 1 2.688 0.372 0.71
#> 335 9 11 2 2.688 0.744 0.457
#> 336 10 9 -1 2.688 -0.372 0.71
#> 337 12 13 1 2.688 0.372 0.71
#> 338 16 14 -2 2.688 -0.744 0.457
#> 339 6 10 4 2.688 1.488 0.137
#> 340 17 15 -2 2.688 -0.744 0.457
#> 341 12 14 2 2.688 0.744 0.457
#> 342 6 5 -1 2.688 -0.372 0.71
#> 343 5 9 4 2.688 1.488 0.137
#> 344 5 4 -1 2.688 -0.372 0.71
#> 345 6 9 3 2.688 1.116 0.264
#> 346 12 8 -4 2.688 -1.488 0.137
#> 347 12 13 1 2.688 0.372 0.71
#> 348 8 11 3 2.688 1.116 0.264
#> 349 5 6 1 2.688 0.372 0.71
#> 350 11 12 1 2.688 0.372 0.71
#> 351 9 7 -2 2.688 -0.744 0.457
#> 352 18 16 -2 2.688 -0.744 0.457
#> 353 9 11 2 2.688 0.744 0.457
#> 354 4 3 -1 2.688 -0.372 0.71
#> 355 12 17 5 2.688 1.860 0.063
#> 356 16 15 -1 2.688 -0.372 0.71
#> 357 9 13 4 2.688 1.488 0.137
#> 358 10 7 -3 2.688 -1.116 0.264
#> 359 1 3 2 2.688 0.744 0.457
#> 360 10 12 2 2.688 0.744 0.457
#> 361 5 5 0 2.688 0.000 1
#> 362 13 15 2 2.688 0.744 0.457
#> 363 9 12 3 2.688 1.116 0.264
#> 364 13 14 1 2.688 0.372 0.71
#> 365 9 5 -4 2.688 -1.488 0.137
#> 366 17 17 0 2.688 0.000 1
#> 367 4 2 -2 2.688 -0.744 0.457
#> 368 12 9 -3 2.688 -1.116 0.264
#> 369 3 10 7 2.688 2.604 0.009
#> 370 12 12 0 2.688 0.000 1
#> 371 14 18 4 2.688 1.488 0.137
#> 372 10 11 1 2.688 0.372 0.71
#> 373 7 9 2 2.688 0.744 0.457
#> 374 4 6 2 2.688 0.744 0.457
#> 375 10 5 -5 2.688 -1.860 0.063
#> 376 16 14 -2 2.688 -0.744 0.457
#> 377 15 15 0 2.688 0.000 1
#> 378 13 12 -1 2.688 -0.372 0.71
#> 379 0 3 3 2.688 1.116 0.264
#> 380 7 8 1 2.688 0.372 0.71
#> 381 6 7 1 2.688 0.372 0.71
#> 382 6 6 0 2.688 0.000 1
#> 383 6 8 2 2.688 0.744 0.457
#> 384 4 4 0 2.688 0.000 1
#> 385 3 4 1 2.688 0.372 0.71
#> 386 2 7 5 2.688 1.860 0.063
#> 387 9 9 0 2.688 0.000 1
#> 388 19 14 -5 2.688 -1.860 0.063
#> 389 3 6 3 2.688 1.116 0.264
#> 390 0 2 2 2.688 0.744 0.457
#> 391 15 14 -1 2.688 -0.372 0.71
#> 392 11 4 -7 2.688 -2.604 0.009
#> 393 5 6 1 2.688 0.372 0.71
#> 394 2 1 -1 2.688 -0.372 0.71
#> 395 7 13 6 2.688 2.232 0.026
#> 396 13 11 -2 2.688 -0.744 0.457
#> 397 15 14 -1 2.688 -0.372 0.71
#> 398 2 4 2 2.688 0.744 0.457
#> 399 13 6 -7 2.688 -2.604 0.009
#> 400 15 9 -6 2.688 -2.232 0.026
#> 401 7 8 1 2.688 0.372 0.71
#> 402 3 3 0 2.688 0.000 1
#> 403 9 12 3 2.688 1.116 0.264
#> 404 17 17 0 2.688 0.000 1
#> 405 1 4 3 2.688 1.116 0.264
#> 406 4 2 -2 2.688 -0.744 0.457
#> 407 7 10 3 2.688 1.116 0.264
#> 408 7 11 4 2.688 1.488 0.137
#> 409 12 12 0 2.688 0.000 1
#> 410 8 6 -2 2.688 -0.744 0.457
#> 411 8 4 -4 2.688 -1.488 0.137
#> 412 14 11 -3 2.688 -1.116 0.264
#> 413 5 3 -2 2.688 -0.744 0.457
#> 414 16 17 1 2.688 0.372 0.71
#> 415 11 15 4 2.688 1.488 0.137
#> 416 15 12 -3 2.688 -1.116 0.264
#> 417 14 15 1 2.688 0.372 0.71
#> 418 5 6 1 2.688 0.372 0.71
#> 419 5 10 5 2.688 1.860 0.063
#> 420 10 13 3 2.688 1.116 0.264
#> 421 3 2 -1 2.688 -0.372 0.71
#> 422 17 17 0 2.688 0.000 1
#> 423 11 11 0 2.688 0.000 1
#> 424 14 13 -1 2.688 -0.372 0.71
#> 425 16 9 -7 2.688 -2.604 0.009
#> 426 15 16 1 2.688 0.372 0.71
#> 427 11 7 -4 2.688 -1.488 0.137
#> 428 8 11 3 2.688 1.116 0.264
#> 429 13 13 0 2.688 0.000 1
#> 430 10 10 0 2.688 0.000 1
#> 431 15 14 -1 2.688 -0.372 0.71
#> 432 1 4 3 2.688 1.116 0.264
#> 433 3 3 0 2.688 0.000 1
#> 434 11 15 4 2.688 1.488 0.137
#> 435 3 4 1 2.688 0.372 0.71
#> 436 6 11 5 2.688 1.860 0.063
#> 437 2 0 -2 2.688 -0.744 0.457
#> 438 13 14 1 2.688 0.372 0.71
#> 439 18 14 -4 2.688 -1.488 0.137
#> 440 6 13 7 2.688 2.604 0.009
#> 441 14 12 -2 2.688 -0.744 0.457
#> 442 4 5 1 2.688 0.372 0.71
#> 443 10 9 -1 2.688 -0.372 0.71
#> 444 18 18 0 2.688 0.000 1
#> 445 17 16 -1 2.688 -0.372 0.71
#> 446 16 17 1 2.688 0.372 0.71
#> 447 0 0 0 2.688 0.000 1
#> 448 12 10 -2 2.688 -0.744 0.457
#> 449 4 7 3 2.688 1.116 0.264
#> 450 1 4 3 2.688 1.116 0.264
#> 451 19 18 -1 2.688 -0.372 0.71
#> 452 8 5 -3 2.688 -1.116 0.264
#> 453 8 11 3 2.688 1.116 0.264
#> 454 5 9 4 2.688 1.488 0.137
#> 455 18 17 -1 2.688 -0.372 0.71
#> 456 12 11 -1 2.688 -0.372 0.71
#> 457 5 9 4 2.688 1.488 0.137
#> 458 2 5 3 2.688 1.116 0.264
#> 459 1 2 1 2.688 0.372 0.71
#> 460 19 18 -1 2.688 -0.372 0.71
#> 461 15 17 2 2.688 0.744 0.457
#> 462 17 13 -4 2.688 -1.488 0.137
#> 463 13 15 2 2.688 0.744 0.457
#> 464 14 14 0 2.688 0.000 1
#> 465 6 9 3 2.688 1.116 0.264
#> 466 9 5 -4 2.688 -1.488 0.137
#> 467 16 15 -1 2.688 -0.372 0.71
#> 468 3 2 -1 2.688 -0.372 0.71
#> 469 1 7 6 2.688 2.232 0.026
#> 470 13 10 -3 2.688 -1.116 0.264
#> 471 5 4 -1 2.688 -0.372 0.71
#> 472 6 7 1 2.688 0.372 0.71
#> 473 20 19 -1 2.688 -0.372 0.71
#> 474 7 9 2 2.688 0.744 0.457
#> 475 1 1 0 2.688 0.000 1
#> 476 15 13 -2 2.688 -0.744 0.457
#> 477 16 11 -5 2.688 -1.860 0.063
#> 478 16 12 -4 2.688 -1.488 0.137
#> 479 11 10 -1 2.688 -0.372 0.71
#> 480 15 16 1 2.688 0.372 0.71
#> 481 7 8 1 2.688 0.372 0.71
#> 482 15 12 -3 2.688 -1.116 0.264
#> 483 15 16 1 2.688 0.372 0.71
#> 484 12 11 -1 2.688 -0.372 0.71
#> 485 12 10 -2 2.688 -0.744 0.457
#> 486 5 8 3 2.688 1.116 0.264
#> 487 8 12 4 2.688 1.488 0.137
#> 488 11 13 2 2.688 0.744 0.457
#> 489 16 17 1 2.688 0.372 0.71
#> 490 7 8 1 2.688 0.372 0.71
#> 491 19 18 -1 2.688 -0.372 0.71
#> 492 4 5 1 2.688 0.372 0.71
#> 493 19 16 -3 2.688 -1.116 0.264
#> 494 8 9 1 2.688 0.372 0.71
#> 495 10 15 5 2.688 1.860 0.063
#> 496 6 7 1 2.688 0.372 0.71
#> 497 11 8 -3 2.688 -1.116 0.264
#> 498 3 9 6 2.688 2.232 0.026
#> 499 8 8 0 2.688 0.000 1
#> 500 7 11 4 2.688 1.488 0.137
#> 501 13 16 3 2.688 1.116 0.264
#> 502 11 10 -1 2.688 -0.372 0.71
#> 503 0 1 1 2.688 0.372 0.71
#> 504 4 5 1 2.688 0.372 0.71
#> 505 4 6 2 2.688 0.744 0.457
#> 506 12 10 -2 2.688 -0.744 0.457
#> 507 18 16 -2 2.688 -0.744 0.457
#> 508 13 14 1 2.688 0.372 0.71
#> 509 5 7 2 2.688 0.744 0.457
#> 510 8 10 2 2.688 0.744 0.457
#> 511 6 10 4 2.688 1.488 0.137
#> 512 7 9 2 2.688 0.744 0.457
#> 513 5 5 0 2.688 0.000 1
#> 514 5 10 5 2.688 1.860 0.063
#> 515 9 11 2 2.688 0.744 0.457
#> 516 17 17 0 2.688 0.000 1
#> 517 14 13 -1 2.688 -0.372 0.71
#> 518 8 15 7 2.688 2.604 0.009
#> 519 14 14 0 2.688 0.000 1
#> 520 13 8 -5 2.688 -1.860 0.063
#> 521 14 12 -2 2.688 -0.744 0.457
#> 522 6 2 -4 2.688 -1.488 0.137
#> 523 17 14 -3 2.688 -1.116 0.264
#> 524 13 13 0 2.688 0.000 1
#> 525 14 14 0 2.688 0.000 1
#> 526 16 12 -4 2.688 -1.488 0.137
#> 527 12 10 -2 2.688 -0.744 0.457
#> 528 15 16 1 2.688 0.372 0.71
#> 529 13 10 -3 2.688 -1.116 0.264
#> 530 9 10 1 2.688 0.372 0.71
#> 531 12 7 -5 2.688 -1.860 0.063
#> 532 20 20 0 2.688 0.000 1
#> 533 17 12 -5 2.688 -1.860 0.063
#> 534 6 8 2 2.688 0.744 0.457
#> 535 19 18 -1 2.688 -0.372 0.71
#> 536 12 12 0 2.688 0.000 1
#> 537 10 7 -3 2.688 -1.116 0.264
#> 538 6 4 -2 2.688 -0.744 0.457
#> 539 8 8 0 2.688 0.000 1
#> 540 10 12 2 2.688 0.744 0.457
#> 541 4 7 3 2.688 1.116 0.264
#> 542 2 2 0 2.688 0.000 1
#> 543 6 5 -1 2.688 -0.372 0.71
#> 544 12 10 -2 2.688 -0.744 0.457
#> 545 4 5 1 2.688 0.372 0.71
#> 546 11 10 -1 2.688 -0.372 0.71
#> 547 14 12 -2 2.688 -0.744 0.457
#> 548 13 15 2 2.688 0.744 0.457
#> 549 12 9 -3 2.688 -1.116 0.264
#> 550 11 11 0 2.688 0.000 1
#> 551 8 2 -6 2.688 -2.232 0.026
#> 552 14 15 1 2.688 0.372 0.71
#> 553 11 14 3 2.688 1.116 0.264
#> 554 13 12 -1 2.688 -0.372 0.71
#> 555 2 3 1 2.688 0.372 0.71
#> 556 9 13 4 2.688 1.488 0.137
#> 557 10 11 1 2.688 0.372 0.71
#> 558 8 12 4 2.688 1.488 0.137
#> 559 11 12 1 2.688 0.372 0.71
#> 560 19 18 -1 2.688 -0.372 0.71
#> 561 12 12 0 2.688 0.000 1
#> 562 12 8 -4 2.688 -1.488 0.137
#> 563 3 6 3 2.688 1.116 0.264
#> 564 4 0 -4 2.688 -1.488 0.137
#> 565 14 14 0 2.688 0.000 1
#> 566 3 4 1 2.688 0.372 0.71
#> 567 18 16 -2 2.688 -0.744 0.457
#> 568 3 2 -1 2.688 -0.372 0.71
#> 569 17 19 2 2.688 0.744 0.457
#> 570 10 8 -2 2.688 -0.744 0.457
#> 571 16 13 -3 2.688 -1.116 0.264
#> 572 8 8 0 2.688 0.000 1
#> 573 15 17 2 2.688 0.744 0.457
#> 574 7 12 5 2.688 1.860 0.063
#> 575 6 2 -4 2.688 -1.488 0.137
#> 576 11 14 3 2.688 1.116 0.264
#> 577 13 12 -1 2.688 -0.372 0.71
#> 578 17 14 -3 2.688 -1.116 0.264
#> 579 5 9 4 2.688 1.488 0.137
#> 580 12 17 5 2.688 1.860 0.063
#> 581 11 10 -1 2.688 -0.372 0.71
#> 582 6 12 6 2.688 2.232 0.026
#> 583 11 13 2 2.688 0.744 0.457
#> 584 16 18 2 2.688 0.744 0.457
#> 585 8 6 -2 2.688 -0.744 0.457
#> 586 7 9 2 2.688 0.744 0.457
#> 587 12 11 -1 2.688 -0.372 0.71
#> 588 9 7 -2 2.688 -0.744 0.457
#> 589 9 6 -3 2.688 -1.116 0.264
#> 590 14 13 -1 2.688 -0.372 0.71
#> 591 15 15 0 2.688 0.000 1
#> 592 19 15 -4 2.688 -1.488 0.137
#> 593 6 7 1 2.688 0.372 0.71
#> 594 4 3 -1 2.688 -0.372 0.71
#> 595 4 6 2 2.688 0.744 0.457
#> 596 4 3 -1 2.688 -0.372 0.71
#> 597 4 4 0 2.688 0.000 1
#> 598 10 6 -4 2.688 -1.488 0.137
#> 599 8 14 6 2.688 2.232 0.026
#> 600 9 12 3 2.688 1.116 0.264
#> 601 10 12 2 2.688 0.744 0.457
#> 602 12 9 -3 2.688 -1.116 0.264
#> 603 13 9 -4 2.688 -1.488 0.137
#> 604 11 11 0 2.688 0.000 1
#> 605 2 4 2 2.688 0.744 0.457
#> 606 16 14 -2 2.688 -0.744 0.457
#> 607 2 1 -1 2.688 -0.372 0.71
#> 608 3 2 -1 2.688 -0.372 0.71
#> 609 6 4 -2 2.688 -0.744 0.457
#> 610 15 11 -4 2.688 -1.488 0.137
#> 611 7 6 -1 2.688 -0.372 0.71
#> 612 14 18 4 2.688 1.488 0.137
#> 613 7 14 7 2.688 2.604 0.009
#> 614 18 14 -4 2.688 -1.488 0.137
#> 615 9 6 -3 2.688 -1.116 0.264
#> 616 11 11 0 2.688 0.000 1
#> 617 6 2 -4 2.688 -1.488 0.137
#> 618 10 7 -3 2.688 -1.116 0.264
#> 619 3 2 -1 2.688 -0.372 0.71
#> 620 8 4 -4 2.688 -1.488 0.137
#> 621 8 10 2 2.688 0.744 0.457
#> 622 16 16 0 2.688 0.000 1
#> 623 4 2 -2 2.688 -0.744 0.457
#> 624 13 15 2 2.688 0.744 0.457
#> 625 11 11 0 2.688 0.000 1
#> 626 14 13 -1 2.688 -0.372 0.71
#> 627 4 8 4 2.688 1.488 0.137
#> 628 6 8 2 2.688 0.744 0.457
#> 629 15 9 -6 2.688 -2.232 0.026
#> 630 2 3 1 2.688 0.372 0.71
#> 631 2 3 1 2.688 0.372 0.71
#> 632 8 6 -2 2.688 -0.744 0.457
#> 633 8 4 -4 2.688 -1.488 0.137
#> 634 12 18 6 2.688 2.232 0.026
#> 635 15 15 0 2.688 0.000 1
#> 636 10 10 0 2.688 0.000 1
#> 637 3 3 0 2.688 0.000 1
#> 638 14 15 1 2.688 0.372 0.71
#> 639 9 6 -3 2.688 -1.116 0.264
#> 640 2 5 3 2.688 1.116 0.264
#> 641 14 17 3 2.688 1.116 0.264
#> 642 4 2 -2 2.688 -0.744 0.457
#> 643 12 13 1 2.688 0.372 0.71
#> 644 10 7 -3 2.688 -1.116 0.264
#> 645 3 4 1 2.688 0.372 0.71
#> 646 4 2 -2 2.688 -0.744 0.457
#> 647 2 6 4 2.688 1.488 0.137
#> 648 11 8 -3 2.688 -1.116 0.264
#> 649 10 10 0 2.688 0.000 1
#> 650 17 17 0 2.688 0.000 1
#> 651 8 10 2 2.688 0.744 0.457
#> 652 8 9 1 2.688 0.372 0.71
#> 653 17 17 0 2.688 0.000 1
#> 654 15 13 -2 2.688 -0.744 0.457
#> 655 14 19 5 2.688 1.860 0.063
#> 656 10 14 4 2.688 1.488 0.137
#> 657 12 13 1 2.688 0.372 0.71
#> 658 7 12 5 2.688 1.860 0.063
#> 659 11 12 1 2.688 0.372 0.71
#> 660 13 10 -3 2.688 -1.116 0.264
#> 661 7 7 0 2.688 0.000 1
#> 662 8 6 -2 2.688 -0.744 0.457
#> 663 7 5 -2 2.688 -0.744 0.457
#> 664 14 10 -4 2.688 -1.488 0.137
#> 665 17 19 2 2.688 0.744 0.457
#> 666 9 6 -3 2.688 -1.116 0.264
#> 667 3 3 0 2.688 0.000 1
#> 668 15 11 -4 2.688 -1.488 0.137
#> 669 7 8 1 2.688 0.372 0.71
#> 670 12 12 0 2.688 0.000 1
#> 671 13 13 0 2.688 0.000 1
#> 672 16 20 4 2.688 1.488 0.137
#> 673 13 9 -4 2.688 -1.488 0.137
#> 674 14 16 2 2.688 0.744 0.457
#> 675 7 2 -5 2.688 -1.860 0.063
#> 676 10 6 -4 2.688 -1.488 0.137
#> 677 10 12 2 2.688 0.744 0.457
#> 678 8 9 1 2.688 0.372 0.71
#> 679 4 7 3 2.688 1.116 0.264
#> 680 2 4 2 2.688 0.744 0.457
#> 681 13 10 -3 2.688 -1.116 0.264
#> 682 5 12 7 2.688 2.604 0.009
#> 683 5 6 1 2.688 0.372 0.71
#> 684 10 7 -3 2.688 -1.116 0.264
#> 685 13 12 -1 2.688 -0.372 0.71
#> 686 17 19 2 2.688 0.744 0.457
#> 687 11 12 1 2.688 0.372 0.71
#> 688 4 10 6 2.688 2.232 0.026
#> 689 6 4 -2 2.688 -0.744 0.457
#> 690 3 5 2 2.688 0.744 0.457
#> 691 11 14 3 2.688 1.116 0.264
#> 692 7 2 -5 2.688 -1.860 0.063
#> 693 8 10 2 2.688 0.744 0.457
#> 694 13 11 -2 2.688 -0.744 0.457
#> 695 13 16 3 2.688 1.116 0.264
#> 696 16 15 -1 2.688 -0.372 0.71
#> 697 16 12 -4 2.688 -1.488 0.137
#> 698 3 3 0 2.688 0.000 1
#> 699 12 15 3 2.688 1.116 0.264
#> 700 12 16 4 2.688 1.488 0.137
#> 701 3 3 0 2.688 0.000 1
#> 702 20 20 0 2.688 0.000 1
#> 703 7 10 3 2.688 1.116 0.264
#> 704 9 13 4 2.688 1.488 0.137
#> 705 5 7 2 2.688 0.744 0.457
#> 706 2 2 0 2.688 0.000 1
#> 707 13 16 3 2.688 1.116 0.264
#> 708 5 7 2 2.688 0.744 0.457
#> 709 8 7 -1 2.688 -0.372 0.71
#> 710 15 18 3 2.688 1.116 0.264
#> 711 3 1 -2 2.688 -0.744 0.457
#> 712 5 5 0 2.688 0.000 1
#> 713 5 3 -2 2.688 -0.744 0.457
#> 714 15 16 1 2.688 0.372 0.71
#> 715 12 10 -2 2.688 -0.744 0.457
#> 716 9 6 -3 2.688 -1.116 0.264
#> 717 5 2 -3 2.688 -1.116 0.264
#> 718 3 4 1 2.688 0.372 0.71
#> 719 2 6 4 2.688 1.488 0.137
#> 720 4 6 2 2.688 0.744 0.457
#> 721 10 12 2 2.688 0.744 0.457
#> 722 16 14 -2 2.688 -0.744 0.457
#> 723 3 2 -1 2.688 -0.372 0.71
#> 724 13 8 -5 2.688 -1.860 0.063
#> 725 17 15 -2 2.688 -0.744 0.457
#> 726 8 8 0 2.688 0.000 1
#> 727 8 10 2 2.688 0.744 0.457
#> 728 16 12 -4 2.688 -1.488 0.137
#> 729 11 15 4 2.688 1.488 0.137
#> 730 4 8 4 2.688 1.488 0.137
#> 731 5 6 1 2.688 0.372 0.71
#> 732 4 3 -1 2.688 -0.372 0.71
#> 733 8 6 -2 2.688 -0.744 0.457
#> 734 18 19 1 2.688 0.372 0.71
#> 735 10 11 1 2.688 0.372 0.71
#> 736 10 12 2 2.688 0.744 0.457
#> 737 18 20 2 2.688 0.744 0.457
#> 738 11 5 -6 2.688 -2.232 0.026
#> 739 17 17 0 2.688 0.000 1
#> 740 3 5 2 2.688 0.744 0.457
#> 741 15 15 0 2.688 0.000 1
#> 742 8 9 1 2.688 0.372 0.71
#> 743 9 5 -4 2.688 -1.488 0.137
#> 744 16 13 -3 2.688 -1.116 0.264
#> 745 14 13 -1 2.688 -0.372 0.71
#> 746 8 6 -2 2.688 -0.744 0.457
#> 747 5 9 4 2.688 1.488 0.137
#> 748 3 1 -2 2.688 -0.744 0.457
#> 749 6 7 1 2.688 0.372 0.71
#> 750 17 13 -4 2.688 -1.488 0.137
#> 751 15 15 0 2.688 0.000 1
#> 752 5 6 1 2.688 0.372 0.71
#> 753 9 11 2 2.688 0.744 0.457
#> 754 16 14 -2 2.688 -0.744 0.457
#> 755 12 12 0 2.688 0.000 1
#> 756 12 14 2 2.688 0.744 0.457
#> 757 14 9 -5 2.688 -1.860 0.063
#> 758 12 15 3 2.688 1.116 0.264
#> 759 1 0 -1 2.688 -0.372 0.71
#> 760 13 17 4 2.688 1.488 0.137
#> 761 17 19 2 2.688 0.744 0.457
#> 762 4 4 0 2.688 0.000 1
#> 763 10 7 -3 2.688 -1.116 0.264
#> 764 15 15 0 2.688 0.000 1
#> 765 10 12 2 2.688 0.744 0.457
#> 766 2 2 0 2.688 0.000 1
#> 767 16 16 0 2.688 0.000 1
#> 768 14 13 -1 2.688 -0.372 0.71
#> 769 15 15 0 2.688 0.000 1
#> 770 7 3 -4 2.688 -1.488 0.137
#> 771 7 3 -4 2.688 -1.488 0.137
#> 772 15 14 -1 2.688 -0.372 0.71
#> 773 11 12 1 2.688 0.372 0.71
#> 774 2 1 -1 2.688 -0.372 0.71
#> 775 3 7 4 2.688 1.488 0.137
#> 776 16 16 0 2.688 0.000 1
#> 777 14 9 -5 2.688 -1.860 0.063
#> 778 14 14 0 2.688 0.000 1
#> 779 14 13 -1 2.688 -0.372 0.71
#> 780 13 9 -4 2.688 -1.488 0.137
#> 781 13 11 -2 2.688 -0.744 0.457
#> 782 5 13 8 2.688 2.976 0.003
#> 783 13 12 -1 2.688 -0.372 0.71
#> 784 8 7 -1 2.688 -0.372 0.71
#> 785 17 16 -1 2.688 -0.372 0.71
#> 786 10 11 1 2.688 0.372 0.71
#> 787 12 10 -2 2.688 -0.744 0.457
#> 788 7 9 2 2.688 0.744 0.457
#> 789 2 2 0 2.688 0.000 1
#> 790 1 3 2 2.688 0.744 0.457
#> 791 3 8 5 2.688 1.860 0.063
#> 792 14 16 2 2.688 0.744 0.457
#> 793 4 7 3 2.688 1.116 0.264
#> 794 15 17 2 2.688 0.744 0.457
#> 795 15 13 -2 2.688 -0.744 0.457
#> 796 7 8 1 2.688 0.372 0.71
#> 797 6 4 -2 2.688 -0.744 0.457
#> 798 7 6 -1 2.688 -0.372 0.71
#> 799 11 8 -3 2.688 -1.116 0.264
#> 800 8 12 4 2.688 1.488 0.137
#> 801 6 3 -3 2.688 -1.116 0.264
#> 802 7 2 -5 2.688 -1.860 0.063
#> 803 9 9 0 2.688 0.000 1
#> 804 17 14 -3 2.688 -1.116 0.264
#> 805 6 7 1 2.688 0.372 0.71
#> 806 14 13 -1 2.688 -0.372 0.71
#> 807 6 13 7 2.688 2.604 0.009
#> 808 7 9 2 2.688 0.744 0.457
#> 809 17 17 0 2.688 0.000 1
#> 810 3 6 3 2.688 1.116 0.264
#> 811 15 18 3 2.688 1.116 0.264
#> 812 10 10 0 2.688 0.000 1
#> 813 7 2 -5 2.688 -1.860 0.063
#> 814 13 14 1 2.688 0.372 0.71
#> 815 8 10 2 2.688 0.744 0.457
#> 816 7 7 0 2.688 0.000 1
#> 817 15 5 -10 2.688 -3.721 0
#> 818 11 11 0 2.688 0.000 1
#> 819 8 14 6 2.688 2.232 0.026
#> 820 7 5 -2 2.688 -0.744 0.457
#> 821 12 12 0 2.688 0.000 1
#> 822 10 13 3 2.688 1.116 0.264
#> 823 3 3 0 2.688 0.000 1
#> 824 17 18 1 2.688 0.372 0.71
#> 825 7 6 -1 2.688 -0.372 0.71
#> 826 5 7 2 2.688 0.744 0.457
#> 827 15 14 -1 2.688 -0.372 0.71
#> 828 3 7 4 2.688 1.488 0.137
#> 829 4 3 -1 2.688 -0.372 0.71
#> 830 20 17 -3 2.688 -1.116 0.264
#> 831 8 5 -3 2.688 -1.116 0.264
#> 832 13 18 5 2.688 1.860 0.063
#> 833 15 15 0 2.688 0.000 1
#> 834 16 17 1 2.688 0.372 0.71
#> 835 6 6 0 2.688 0.000 1
#> 836 16 16 0 2.688 0.000 1
#> 837 9 9 0 2.688 0.000 1
#> 838 10 16 6 2.688 2.232 0.026
#> 839 10 11 1 2.688 0.372 0.71
#> 840 16 17 1 2.688 0.372 0.71
#> 841 15 15 0 2.688 0.000 1
#> 842 13 13 0 2.688 0.000 1
#> 843 15 16 1 2.688 0.372 0.71
#> 844 10 7 -3 2.688 -1.116 0.264
#> 845 12 9 -3 2.688 -1.116 0.264
#> 846 12 12 0 2.688 0.000 1
#> 847 8 7 -1 2.688 -0.372 0.71
#> 848 7 3 -4 2.688 -1.488 0.137
#> 849 5 5 0 2.688 0.000 1
#> 850 19 16 -3 2.688 -1.116 0.264
#> 851 15 15 0 2.688 0.000 1
#> 852 13 8 -5 2.688 -1.860 0.063
#> 853 9 10 1 2.688 0.372 0.71
#> 854 8 8 0 2.688 0.000 1
#> 855 9 9 0 2.688 0.000 1
#> 856 12 13 1 2.688 0.372 0.71
#> 857 10 7 -3 2.688 -1.116 0.264
#> 858 13 10 -3 2.688 -1.116 0.264
#> 859 10 9 -1 2.688 -0.372 0.71
#> 860 5 8 3 2.688 1.116 0.264
#> 861 5 3 -2 2.688 -0.744 0.457
#> 862 13 14 1 2.688 0.372 0.71
#> 863 3 6 3 2.688 1.116 0.264
#> 864 8 4 -4 2.688 -1.488 0.137
#> 865 10 13 3 2.688 1.116 0.264
#> 866 12 12 0 2.688 0.000 1
#> 867 9 10 1 2.688 0.372 0.71
#> 868 11 13 2 2.688 0.744 0.457
#> 869 10 7 -3 2.688 -1.116 0.264
#> 870 13 13 0 2.688 0.000 1
#> 871 14 13 -1 2.688 -0.372 0.71
#> 872 8 10 2 2.688 0.744 0.457
#> 873 1 1 0 2.688 0.000 1
#> 874 7 13 6 2.688 2.232 0.026
#> 875 14 16 2 2.688 0.744 0.457
#> 876 9 8 -1 2.688 -0.372 0.71
#> 877 16 16 0 2.688 0.000 1
#> 878 14 15 1 2.688 0.372 0.71
#> 879 8 10 2 2.688 0.744 0.457
#> 880 6 2 -4 2.688 -1.488 0.137
#> 881 5 2 -3 2.688 -1.116 0.264
#> 882 6 10 4 2.688 1.488 0.137
#> 883 11 11 0 2.688 0.000 1
#> 884 6 5 -1 2.688 -0.372 0.71
#> 885 14 14 0 2.688 0.000 1
#> 886 3 7 4 2.688 1.488 0.137
#> 887 3 9 6 2.688 2.232 0.026
#> 888 10 7 -3 2.688 -1.116 0.264
#> 889 2 6 4 2.688 1.488 0.137
#> 890 15 11 -4 2.688 -1.488 0.137
#> 891 10 6 -4 2.688 -1.488 0.137
#> 892 10 10 0 2.688 0.000 1
#> 893 17 16 -1 2.688 -0.372 0.71
#> 894 11 12 1 2.688 0.372 0.71
#> 895 9 11 2 2.688 0.744 0.457
#> 896 15 13 -2 2.688 -0.744 0.457
#> 897 17 16 -1 2.688 -0.372 0.71
#> 898 7 9 2 2.688 0.744 0.457
#> 899 10 8 -2 2.688 -0.744 0.457
#> 900 6 5 -1 2.688 -0.372 0.71
#> 901 7 6 -1 2.688 -0.372 0.71
#> 902 16 19 3 2.688 1.116 0.264
#> 903 16 19 3 2.688 1.116 0.264
#> 904 12 9 -3 2.688 -1.116 0.264
#> 905 6 7 1 2.688 0.372 0.71
#> 906 19 20 1 2.688 0.372 0.71
#> 907 15 11 -4 2.688 -1.488 0.137
#> 908 10 5 -5 2.688 -1.860 0.063
#> 909 2 0 -2 2.688 -0.744 0.457
#> 910 18 10 -8 2.688 -2.976 0.003
#> 911 2 0 -2 2.688 -0.744 0.457
#> 912 20 17 -3 2.688 -1.116 0.264
#> 913 4 2 -2 2.688 -0.744 0.457
#> 914 16 17 1 2.688 0.372 0.71
#> 915 14 15 1 2.688 0.372 0.71
#> 916 18 13 -5 2.688 -1.860 0.063
#> 917 16 17 1 2.688 0.372 0.71
#> 918 15 18 3 2.688 1.116 0.264
#> 919 13 10 -3 2.688 -1.116 0.264
#> 920 11 8 -3 2.688 -1.116 0.264
#> 921 4 2 -2 2.688 -0.744 0.457
#> 922 6 10 4 2.688 1.488 0.137
#> 923 12 11 -1 2.688 -0.372 0.71
#> 924 18 18 0 2.688 0.000 1
#> 925 5 5 0 2.688 0.000 1
#> 926 19 19 0 2.688 0.000 1
#> 927 7 5 -2 2.688 -0.744 0.457
#> 928 9 3 -6 2.688 -2.232 0.026
#> 929 15 19 4 2.688 1.488 0.137
#> 930 15 9 -6 2.688 -2.232 0.026
#> 931 11 11 0 2.688 0.000 1
#> 932 12 10 -2 2.688 -0.744 0.457
#> 933 12 13 1 2.688 0.372 0.71
#> 934 9 6 -3 2.688 -1.116 0.264
#> 935 14 14 0 2.688 0.000 1
#> 936 6 7 1 2.688 0.372 0.71
#> 937 6 6 0 2.688 0.000 1
#> 938 8 10 2 2.688 0.744 0.457
#> 939 3 2 -1 2.688 -0.372 0.71
#> 940 11 10 -1 2.688 -0.372 0.71
#> 941 12 15 3 2.688 1.116 0.264
#> 942 13 14 1 2.688 0.372 0.71
#> 943 12 8 -4 2.688 -1.488 0.137
#> 944 15 13 -2 2.688 -0.744 0.457
#> 945 11 12 1 2.688 0.372 0.71
#> 946 11 11 0 2.688 0.000 1
#> 947 11 10 -1 2.688 -0.372 0.71
#> 948 10 13 3 2.688 1.116 0.264
#> 949 1 2 1 2.688 0.372 0.71
#> 950 7 12 5 2.688 1.860 0.063
#> 951 8 6 -2 2.688 -0.744 0.457
#> 952 15 12 -3 2.688 -1.116 0.264
#> 953 7 4 -3 2.688 -1.116 0.264
#> 954 2 6 4 2.688 1.488 0.137
#> 955 6 5 -1 2.688 -0.372 0.71
#> 956 3 3 0 2.688 0.000 1
#> 957 5 5 0 2.688 0.000 1
#> 958 6 6 0 2.688 0.000 1
#> 959 13 17 4 2.688 1.488 0.137
#> 960 6 7 1 2.688 0.372 0.71
#> 961 3 2 -1 2.688 -0.372 0.71
#> 962 12 11 -1 2.688 -0.372 0.71
#> 963 6 4 -2 2.688 -0.744 0.457
#> 964 17 12 -5 2.688 -1.860 0.063
#> 965 5 7 2 2.688 0.744 0.457
#> 966 13 16 3 2.688 1.116 0.264
#> 967 15 16 1 2.688 0.372 0.71
#> 968 12 9 -3 2.688 -1.116 0.264
#> 969 15 13 -2 2.688 -0.744 0.457
#> 970 14 16 2 2.688 0.744 0.457
#> 971 6 7 1 2.688 0.372 0.71
#> 972 16 16 0 2.688 0.000 1
#> 973 3 1 -2 2.688 -0.744 0.457
#> 974 5 5 0 2.688 0.000 1
#> 975 7 3 -4 2.688 -1.488 0.137
#> 976 13 13 0 2.688 0.000 1
#> 977 10 12 2 2.688 0.744 0.457
#> 978 2 4 2 2.688 0.744 0.457
#> 979 2 9 7 2.688 2.604 0.009
#> 980 10 9 -1 2.688 -0.372 0.71
#> 981 4 1 -3 2.688 -1.116 0.264
#> 982 7 4 -3 2.688 -1.116 0.264
#> 983 17 12 -5 2.688 -1.860 0.063
#> 984 18 16 -2 2.688 -0.744 0.457
#> 985 16 11 -5 2.688 -1.860 0.063
#> 986 5 3 -2 2.688 -0.744 0.457
#> 987 13 14 1 2.688 0.372 0.71
#> 988 11 8 -3 2.688 -1.116 0.264
#> 989 2 12 10 2.688 3.721 0
#> 990 9 11 2 2.688 0.744 0.457
#> 991 11 6 -5 2.688 -1.860 0.063
#> 992 11 10 -1 2.688 -0.372 0.71
#> 993 8 6 -2 2.688 -0.744 0.457
#> 994 1 4 3 2.688 1.116 0.264
#> 995 10 7 -3 2.688 -1.116 0.264
#> 996 11 5 -6 2.688 -2.232 0.026
#> 997 7 6 -1 2.688 -0.372 0.71
#> 998 10 12 2 2.688 0.744 0.457
#> 999 11 7 -4 2.688 -1.488 0.137
#> 1000 1 2 1 2.688 0.372 0.71
# 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 18 19 1 2.688 0.372 0.71 unchanged
#> 2 18 9 -9 2.688 -3.349 0.001 decreased
#> 3 15 9 -6 2.688 -2.232 0.026 decreased
#> 4 11 10 -1 2.688 -0.372 0.71 unchanged
#> 5 4 5 1 2.688 0.372 0.71 unchanged
#> 6 4 8 4 2.688 1.488 0.137 unchanged
#> 7 11 8 -3 2.688 -1.116 0.264 unchanged
#> 8 11 15 4 2.688 1.488 0.137 unchanged
#> 9 3 3 0 2.688 0.000 1 unchanged
#> 10 4 8 4 2.688 1.488 0.137 unchanged
#> 11 1 5 4 2.688 1.488 0.137 unchanged
#> 12 16 14 -2 2.688 -0.744 0.457 unchanged
#> 13 12 10 -2 2.688 -0.744 0.457 unchanged
#> 14 11 10 -1 2.688 -0.372 0.71 unchanged
#> 15 17 18 1 2.688 0.372 0.71 unchanged
#> 16 1 4 3 2.688 1.116 0.264 unchanged
#> 17 10 8 -2 2.688 -0.744 0.457 unchanged
#> 18 12 11 -1 2.688 -0.372 0.71 unchanged
#> 19 15 12 -3 2.688 -1.116 0.264 unchanged
#> 20 16 10 -6 2.688 -2.232 0.026 decreased
#> 21 7 6 -1 2.688 -0.372 0.71 unchanged
#> 22 7 12 5 2.688 1.860 0.063 unchanged
#> 23 2 4 2 2.688 0.744 0.457 unchanged
#> 24 5 7 2 2.688 0.744 0.457 unchanged
#> 25 14 15 1 2.688 0.372 0.71 unchanged
#> 26 9 6 -3 2.688 -1.116 0.264 unchanged
#> 27 17 17 0 2.688 0.000 1 unchanged
#> 28 4 9 5 2.688 1.860 0.063 unchanged
#> 29 14 16 2 2.688 0.744 0.457 unchanged
#> 30 4 7 3 2.688 1.116 0.264 unchanged
#> 31 2 0 -2 2.688 -0.744 0.457 unchanged
#> 32 9 6 -3 2.688 -1.116 0.264 unchanged
#> 33 20 20 0 2.688 0.000 1 unchanged
#> 34 9 6 -3 2.688 -1.116 0.264 unchanged
#> 35 3 4 1 2.688 0.372 0.71 unchanged
#> 36 14 15 1 2.688 0.372 0.71 unchanged
#> 37 8 9 1 2.688 0.372 0.71 unchanged
#> 38 15 13 -2 2.688 -0.744 0.457 unchanged
#> 39 9 12 3 2.688 1.116 0.264 unchanged
#> 40 18 18 0 2.688 0.000 1 unchanged
#> 41 11 10 -1 2.688 -0.372 0.71 unchanged
#> 42 12 9 -3 2.688 -1.116 0.264 unchanged
#> 43 8 7 -1 2.688 -0.372 0.71 unchanged
#> 44 10 11 1 2.688 0.372 0.71 unchanged
#> 45 7 10 3 2.688 1.116 0.264 unchanged
#> 46 8 9 1 2.688 0.372 0.71 unchanged
#> 47 6 8 2 2.688 0.744 0.457 unchanged
#> 48 6 7 1 2.688 0.372 0.71 unchanged
#> 49 6 8 2 2.688 0.744 0.457 unchanged
#> 50 8 11 3 2.688 1.116 0.264 unchanged
#> 51 13 17 4 2.688 1.488 0.137 unchanged
#> 52 6 6 0 2.688 0.000 1 unchanged
#> 53 19 13 -6 2.688 -2.232 0.026 decreased
#> 54 6 11 5 2.688 1.860 0.063 unchanged
#> 55 9 8 -1 2.688 -0.372 0.71 unchanged
#> 56 7 8 1 2.688 0.372 0.71 unchanged
#> 57 9 6 -3 2.688 -1.116 0.264 unchanged
#> 58 3 3 0 2.688 0.000 1 unchanged
#> 59 10 8 -2 2.688 -0.744 0.457 unchanged
#> 60 14 14 0 2.688 0.000 1 unchanged
#> 61 12 12 0 2.688 0.000 1 unchanged
#> 62 15 14 -1 2.688 -0.372 0.71 unchanged
#> 63 13 12 -1 2.688 -0.372 0.71 unchanged
#> 64 5 5 0 2.688 0.000 1 unchanged
#> 65 5 4 -1 2.688 -0.372 0.71 unchanged
#> 66 5 4 -1 2.688 -0.372 0.71 unchanged
#> 67 18 14 -4 2.688 -1.488 0.137 unchanged
#> 68 9 8 -1 2.688 -0.372 0.71 unchanged
#> 69 11 9 -2 2.688 -0.744 0.457 unchanged
#> 70 19 17 -2 2.688 -0.744 0.457 unchanged
#> 71 9 5 -4 2.688 -1.488 0.137 unchanged
#> 72 16 15 -1 2.688 -0.372 0.71 unchanged
#> 73 10 9 -1 2.688 -0.372 0.71 unchanged
#> 74 11 11 0 2.688 0.000 1 unchanged
#> 75 14 10 -4 2.688 -1.488 0.137 unchanged
#> 76 14 15 1 2.688 0.372 0.71 unchanged
#> 77 5 4 -1 2.688 -0.372 0.71 unchanged
#> 78 11 9 -2 2.688 -0.744 0.457 unchanged
#> 79 15 10 -5 2.688 -1.860 0.063 unchanged
#> 80 11 11 0 2.688 0.000 1 unchanged
#> 81 10 8 -2 2.688 -0.744 0.457 unchanged
#> 82 12 12 0 2.688 0.000 1 unchanged
#> 83 11 11 0 2.688 0.000 1 unchanged
#> 84 5 1 -4 2.688 -1.488 0.137 unchanged
#> 85 7 9 2 2.688 0.744 0.457 unchanged
#> 86 7 10 3 2.688 1.116 0.264 unchanged
#> 87 3 7 4 2.688 1.488 0.137 unchanged
#> 88 9 11 2 2.688 0.744 0.457 unchanged
#> 89 8 9 1 2.688 0.372 0.71 unchanged
#> 90 12 11 -1 2.688 -0.372 0.71 unchanged
#> 91 6 1 -5 2.688 -1.860 0.063 unchanged
#> 92 6 8 2 2.688 0.744 0.457 unchanged
#> 93 3 5 2 2.688 0.744 0.457 unchanged
#> 94 12 12 0 2.688 0.000 1 unchanged
#> 95 18 16 -2 2.688 -0.744 0.457 unchanged
#> 96 9 7 -2 2.688 -0.744 0.457 unchanged
#> 97 8 11 3 2.688 1.116 0.264 unchanged
#> 98 7 7 0 2.688 0.000 1 unchanged
#> 99 12 11 -1 2.688 -0.372 0.71 unchanged
#> 100 10 10 0 2.688 0.000 1 unchanged
#> 101 5 5 0 2.688 0.000 1 unchanged
#> 102 14 15 1 2.688 0.372 0.71 unchanged
#> 103 9 9 0 2.688 0.000 1 unchanged
#> 104 8 15 7 2.688 2.604 0.009 increased
#> 105 2 3 1 2.688 0.372 0.71 unchanged
#> 106 7 10 3 2.688 1.116 0.264 unchanged
#> 107 12 12 0 2.688 0.000 1 unchanged
#> 108 2 2 0 2.688 0.000 1 unchanged
#> 109 14 13 -1 2.688 -0.372 0.71 unchanged
#> 110 6 4 -2 2.688 -0.744 0.457 unchanged
#> 111 15 10 -5 2.688 -1.860 0.063 unchanged
#> 112 5 5 0 2.688 0.000 1 unchanged
#> 113 15 18 3 2.688 1.116 0.264 unchanged
#> 114 2 0 -2 2.688 -0.744 0.457 unchanged
#> 115 9 12 3 2.688 1.116 0.264 unchanged
#> 116 14 14 0 2.688 0.000 1 unchanged
#> 117 10 7 -3 2.688 -1.116 0.264 unchanged
#> 118 6 5 -1 2.688 -0.372 0.71 unchanged
#> 119 12 9 -3 2.688 -1.116 0.264 unchanged
#> 120 7 3 -4 2.688 -1.488 0.137 unchanged
#> 121 9 12 3 2.688 1.116 0.264 unchanged
#> 122 2 6 4 2.688 1.488 0.137 unchanged
#> 123 9 6 -3 2.688 -1.116 0.264 unchanged
#> 124 2 5 3 2.688 1.116 0.264 unchanged
#> 125 12 12 0 2.688 0.000 1 unchanged
#> 126 16 19 3 2.688 1.116 0.264 unchanged
#> 127 13 14 1 2.688 0.372 0.71 unchanged
#> 128 13 14 1 2.688 0.372 0.71 unchanged
#> 129 14 15 1 2.688 0.372 0.71 unchanged
#> 130 7 14 7 2.688 2.604 0.009 increased
#> 131 10 11 1 2.688 0.372 0.71 unchanged
#> 132 3 3 0 2.688 0.000 1 unchanged
#> 133 15 15 0 2.688 0.000 1 unchanged
#> 134 18 19 1 2.688 0.372 0.71 unchanged
#> 135 2 5 3 2.688 1.116 0.264 unchanged
#> 136 12 10 -2 2.688 -0.744 0.457 unchanged
#> 137 12 14 2 2.688 0.744 0.457 unchanged
#> 138 6 3 -3 2.688 -1.116 0.264 unchanged
#> 139 13 9 -4 2.688 -1.488 0.137 unchanged
#> 140 8 5 -3 2.688 -1.116 0.264 unchanged
#> 141 18 17 -1 2.688 -0.372 0.71 unchanged
#> 142 15 15 0 2.688 0.000 1 unchanged
#> 143 7 9 2 2.688 0.744 0.457 unchanged
#> 144 14 10 -4 2.688 -1.488 0.137 unchanged
#> 145 3 5 2 2.688 0.744 0.457 unchanged
#> 146 1 2 1 2.688 0.372 0.71 unchanged
#> 147 5 6 1 2.688 0.372 0.71 unchanged
#> 148 8 8 0 2.688 0.000 1 unchanged
#> 149 13 15 2 2.688 0.744 0.457 unchanged
#> 150 9 9 0 2.688 0.000 1 unchanged
#> 151 8 9 1 2.688 0.372 0.71 unchanged
#> 152 2 1 -1 2.688 -0.372 0.71 unchanged
#> 153 3 3 0 2.688 0.000 1 unchanged
#> 154 7 5 -2 2.688 -0.744 0.457 unchanged
#> 155 16 13 -3 2.688 -1.116 0.264 unchanged
#> 156 9 12 3 2.688 1.116 0.264 unchanged
#> 157 15 17 2 2.688 0.744 0.457 unchanged
#> 158 10 5 -5 2.688 -1.860 0.063 unchanged
#> 159 8 10 2 2.688 0.744 0.457 unchanged
#> 160 17 11 -6 2.688 -2.232 0.026 decreased
#> 161 14 8 -6 2.688 -2.232 0.026 decreased
#> 162 8 8 0 2.688 0.000 1 unchanged
#> 163 3 5 2 2.688 0.744 0.457 unchanged
#> 164 16 8 -8 2.688 -2.976 0.003 decreased
#> 165 9 7 -2 2.688 -0.744 0.457 unchanged
#> 166 7 8 1 2.688 0.372 0.71 unchanged
#> 167 15 15 0 2.688 0.000 1 unchanged
#> 168 15 18 3 2.688 1.116 0.264 unchanged
#> 169 3 2 -1 2.688 -0.372 0.71 unchanged
#> 170 1 2 1 2.688 0.372 0.71 unchanged
#> 171 2 0 -2 2.688 -0.744 0.457 unchanged
#> 172 20 15 -5 2.688 -1.860 0.063 unchanged
#> 173 10 12 2 2.688 0.744 0.457 unchanged
#> 174 9 3 -6 2.688 -2.232 0.026 decreased
#> 175 5 15 10 2.688 3.721 0 increased
#> 176 9 7 -2 2.688 -0.744 0.457 unchanged
#> 177 15 16 1 2.688 0.372 0.71 unchanged
#> 178 2 5 3 2.688 1.116 0.264 unchanged
#> 179 18 20 2 2.688 0.744 0.457 unchanged
#> 180 10 8 -2 2.688 -0.744 0.457 unchanged
#> 181 6 6 0 2.688 0.000 1 unchanged
#> 182 3 5 2 2.688 0.744 0.457 unchanged
#> 183 9 7 -2 2.688 -0.744 0.457 unchanged
#> 184 7 10 3 2.688 1.116 0.264 unchanged
#> 185 6 3 -3 2.688 -1.116 0.264 unchanged
#> 186 7 5 -2 2.688 -0.744 0.457 unchanged
#> 187 7 4 -3 2.688 -1.116 0.264 unchanged
#> 188 10 9 -1 2.688 -0.372 0.71 unchanged
#> 189 17 12 -5 2.688 -1.860 0.063 unchanged
#> 190 2 4 2 2.688 0.744 0.457 unchanged
#> 191 16 15 -1 2.688 -0.372 0.71 unchanged
#> 192 6 9 3 2.688 1.116 0.264 unchanged
#> 193 10 13 3 2.688 1.116 0.264 unchanged
#> 194 2 7 5 2.688 1.860 0.063 unchanged
#> 195 5 3 -2 2.688 -0.744 0.457 unchanged
#> 196 12 8 -4 2.688 -1.488 0.137 unchanged
#> 197 5 1 -4 2.688 -1.488 0.137 unchanged
#> 198 5 2 -3 2.688 -1.116 0.264 unchanged
#> 199 17 17 0 2.688 0.000 1 unchanged
#> 200 4 2 -2 2.688 -0.744 0.457 unchanged
#> 201 13 13 0 2.688 0.000 1 unchanged
#> 202 14 12 -2 2.688 -0.744 0.457 unchanged
#> 203 2 2 0 2.688 0.000 1 unchanged
#> 204 11 9 -2 2.688 -0.744 0.457 unchanged
#> 205 10 11 1 2.688 0.372 0.71 unchanged
#> 206 13 11 -2 2.688 -0.744 0.457 unchanged
#> 207 17 18 1 2.688 0.372 0.71 unchanged
#> 208 14 15 1 2.688 0.372 0.71 unchanged
#> 209 18 18 0 2.688 0.000 1 unchanged
#> 210 2 0 -2 2.688 -0.744 0.457 unchanged
#> 211 9 11 2 2.688 0.744 0.457 unchanged
#> 212 10 12 2 2.688 0.744 0.457 unchanged
#> 213 16 14 -2 2.688 -0.744 0.457 unchanged
#> 214 2 2 0 2.688 0.000 1 unchanged
#> 215 3 4 1 2.688 0.372 0.71 unchanged
#> 216 15 17 2 2.688 0.744 0.457 unchanged
#> 217 14 12 -2 2.688 -0.744 0.457 unchanged
#> 218 3 5 2 2.688 0.744 0.457 unchanged
#> 219 9 8 -1 2.688 -0.372 0.71 unchanged
#> 220 0 1 1 2.688 0.372 0.71 unchanged
#> 221 14 12 -2 2.688 -0.744 0.457 unchanged
#> 222 2 1 -1 2.688 -0.372 0.71 unchanged
#> 223 5 10 5 2.688 1.860 0.063 unchanged
#> 224 8 15 7 2.688 2.604 0.009 increased
#> 225 12 14 2 2.688 0.744 0.457 unchanged
#> 226 14 14 0 2.688 0.000 1 unchanged
#> 227 11 11 0 2.688 0.000 1 unchanged
#> 228 9 9 0 2.688 0.000 1 unchanged
#> 229 17 15 -2 2.688 -0.744 0.457 unchanged
#> 230 2 2 0 2.688 0.000 1 unchanged
#> 231 6 9 3 2.688 1.116 0.264 unchanged
#> 232 9 14 5 2.688 1.860 0.063 unchanged
#> 233 13 13 0 2.688 0.000 1 unchanged
#> 234 13 17 4 2.688 1.488 0.137 unchanged
#> 235 13 6 -7 2.688 -2.604 0.009 decreased
#> 236 8 8 0 2.688 0.000 1 unchanged
#> 237 8 9 1 2.688 0.372 0.71 unchanged
#> 238 6 12 6 2.688 2.232 0.026 increased
#> 239 9 9 0 2.688 0.000 1 unchanged
#> 240 7 12 5 2.688 1.860 0.063 unchanged
#> 241 18 18 0 2.688 0.000 1 unchanged
#> 242 4 3 -1 2.688 -0.372 0.71 unchanged
#> 243 1 2 1 2.688 0.372 0.71 unchanged
#> 244 3 1 -2 2.688 -0.744 0.457 unchanged
#> 245 6 5 -1 2.688 -0.372 0.71 unchanged
#> 246 4 4 0 2.688 0.000 1 unchanged
#> 247 17 17 0 2.688 0.000 1 unchanged
#> 248 20 18 -2 2.688 -0.744 0.457 unchanged
#> 249 8 10 2 2.688 0.744 0.457 unchanged
#> 250 15 18 3 2.688 1.116 0.264 unchanged
#> 251 15 13 -2 2.688 -0.744 0.457 unchanged
#> 252 8 8 0 2.688 0.000 1 unchanged
#> 253 8 8 0 2.688 0.000 1 unchanged
#> 254 11 13 2 2.688 0.744 0.457 unchanged
#> 255 18 16 -2 2.688 -0.744 0.457 unchanged
#> 256 10 11 1 2.688 0.372 0.71 unchanged
#> 257 18 16 -2 2.688 -0.744 0.457 unchanged
#> 258 10 11 1 2.688 0.372 0.71 unchanged
#> 259 4 3 -1 2.688 -0.372 0.71 unchanged
#> 260 11 14 3 2.688 1.116 0.264 unchanged
#> 261 14 11 -3 2.688 -1.116 0.264 unchanged
#> 262 14 13 -1 2.688 -0.372 0.71 unchanged
#> 263 19 17 -2 2.688 -0.744 0.457 unchanged
#> 264 4 6 2 2.688 0.744 0.457 unchanged
#> 265 17 17 0 2.688 0.000 1 unchanged
#> 266 9 12 3 2.688 1.116 0.264 unchanged
#> 267 4 7 3 2.688 1.116 0.264 unchanged
#> 268 15 12 -3 2.688 -1.116 0.264 unchanged
#> 269 7 7 0 2.688 0.000 1 unchanged
#> 270 8 11 3 2.688 1.116 0.264 unchanged
#> 271 1 2 1 2.688 0.372 0.71 unchanged
#> 272 8 6 -2 2.688 -0.744 0.457 unchanged
#> 273 6 6 0 2.688 0.000 1 unchanged
#> 274 17 16 -1 2.688 -0.372 0.71 unchanged
#> 275 13 11 -2 2.688 -0.744 0.457 unchanged
#> 276 2 1 -1 2.688 -0.372 0.71 unchanged
#> 277 9 10 1 2.688 0.372 0.71 unchanged
#> 278 2 0 -2 2.688 -0.744 0.457 unchanged
#> 279 11 13 2 2.688 0.744 0.457 unchanged
#> 280 17 17 0 2.688 0.000 1 unchanged
#> 281 16 16 0 2.688 0.000 1 unchanged
#> 282 14 15 1 2.688 0.372 0.71 unchanged
#> 283 15 16 1 2.688 0.372 0.71 unchanged
#> 284 4 1 -3 2.688 -1.116 0.264 unchanged
#> 285 17 18 1 2.688 0.372 0.71 unchanged
#> 286 10 7 -3 2.688 -1.116 0.264 unchanged
#> 287 12 15 3 2.688 1.116 0.264 unchanged
#> 288 15 17 2 2.688 0.744 0.457 unchanged
#> 289 17 15 -2 2.688 -0.744 0.457 unchanged
#> 290 14 11 -3 2.688 -1.116 0.264 unchanged
#> 291 15 12 -3 2.688 -1.116 0.264 unchanged
#> 292 10 10 0 2.688 0.000 1 unchanged
#> 293 0 2 2 2.688 0.744 0.457 unchanged
#> 294 12 8 -4 2.688 -1.488 0.137 unchanged
#> 295 4 7 3 2.688 1.116 0.264 unchanged
#> 296 15 15 0 2.688 0.000 1 unchanged
#> 297 18 17 -1 2.688 -0.372 0.71 unchanged
#> 298 9 7 -2 2.688 -0.744 0.457 unchanged
#> 299 18 12 -6 2.688 -2.232 0.026 decreased
#> 300 0 1 1 2.688 0.372 0.71 unchanged
#> 301 4 11 7 2.688 2.604 0.009 increased
#> 302 10 8 -2 2.688 -0.744 0.457 unchanged
#> 303 5 2 -3 2.688 -1.116 0.264 unchanged
#> 304 19 17 -2 2.688 -0.744 0.457 unchanged
#> 305 11 6 -5 2.688 -1.860 0.063 unchanged
#> 306 15 15 0 2.688 0.000 1 unchanged
#> 307 10 12 2 2.688 0.744 0.457 unchanged
#> 308 11 8 -3 2.688 -1.116 0.264 unchanged
#> 309 10 7 -3 2.688 -1.116 0.264 unchanged
#> 310 8 6 -2 2.688 -0.744 0.457 unchanged
#> 311 14 15 1 2.688 0.372 0.71 unchanged
#> 312 16 11 -5 2.688 -1.860 0.063 unchanged
#> 313 6 4 -2 2.688 -0.744 0.457 unchanged
#> 314 11 11 0 2.688 0.000 1 unchanged
#> 315 7 7 0 2.688 0.000 1 unchanged
#> 316 9 11 2 2.688 0.744 0.457 unchanged
#> 317 7 11 4 2.688 1.488 0.137 unchanged
#> 318 1 5 4 2.688 1.488 0.137 unchanged
#> 319 10 9 -1 2.688 -0.372 0.71 unchanged
#> 320 13 10 -3 2.688 -1.116 0.264 unchanged
#> 321 13 10 -3 2.688 -1.116 0.264 unchanged
#> 322 13 9 -4 2.688 -1.488 0.137 unchanged
#> 323 1 2 1 2.688 0.372 0.71 unchanged
#> 324 13 13 0 2.688 0.000 1 unchanged
#> 325 13 13 0 2.688 0.000 1 unchanged
#> 326 13 13 0 2.688 0.000 1 unchanged
#> 327 7 6 -1 2.688 -0.372 0.71 unchanged
#> 328 9 12 3 2.688 1.116 0.264 unchanged
#> 329 13 13 0 2.688 0.000 1 unchanged
#> 330 6 14 8 2.688 2.976 0.003 increased
#> 331 12 14 2 2.688 0.744 0.457 unchanged
#> 332 9 5 -4 2.688 -1.488 0.137 unchanged
#> 333 13 12 -1 2.688 -0.372 0.71 unchanged
#> 334 13 14 1 2.688 0.372 0.71 unchanged
#> 335 9 11 2 2.688 0.744 0.457 unchanged
#> 336 10 9 -1 2.688 -0.372 0.71 unchanged
#> 337 12 13 1 2.688 0.372 0.71 unchanged
#> 338 16 14 -2 2.688 -0.744 0.457 unchanged
#> 339 6 10 4 2.688 1.488 0.137 unchanged
#> 340 17 15 -2 2.688 -0.744 0.457 unchanged
#> 341 12 14 2 2.688 0.744 0.457 unchanged
#> 342 6 5 -1 2.688 -0.372 0.71 unchanged
#> 343 5 9 4 2.688 1.488 0.137 unchanged
#> 344 5 4 -1 2.688 -0.372 0.71 unchanged
#> 345 6 9 3 2.688 1.116 0.264 unchanged
#> 346 12 8 -4 2.688 -1.488 0.137 unchanged
#> 347 12 13 1 2.688 0.372 0.71 unchanged
#> 348 8 11 3 2.688 1.116 0.264 unchanged
#> 349 5 6 1 2.688 0.372 0.71 unchanged
#> 350 11 12 1 2.688 0.372 0.71 unchanged
#> 351 9 7 -2 2.688 -0.744 0.457 unchanged
#> 352 18 16 -2 2.688 -0.744 0.457 unchanged
#> 353 9 11 2 2.688 0.744 0.457 unchanged
#> 354 4 3 -1 2.688 -0.372 0.71 unchanged
#> 355 12 17 5 2.688 1.860 0.063 unchanged
#> 356 16 15 -1 2.688 -0.372 0.71 unchanged
#> 357 9 13 4 2.688 1.488 0.137 unchanged
#> 358 10 7 -3 2.688 -1.116 0.264 unchanged
#> 359 1 3 2 2.688 0.744 0.457 unchanged
#> 360 10 12 2 2.688 0.744 0.457 unchanged
#> 361 5 5 0 2.688 0.000 1 unchanged
#> 362 13 15 2 2.688 0.744 0.457 unchanged
#> 363 9 12 3 2.688 1.116 0.264 unchanged
#> 364 13 14 1 2.688 0.372 0.71 unchanged
#> 365 9 5 -4 2.688 -1.488 0.137 unchanged
#> 366 17 17 0 2.688 0.000 1 unchanged
#> 367 4 2 -2 2.688 -0.744 0.457 unchanged
#> 368 12 9 -3 2.688 -1.116 0.264 unchanged
#> 369 3 10 7 2.688 2.604 0.009 increased
#> 370 12 12 0 2.688 0.000 1 unchanged
#> 371 14 18 4 2.688 1.488 0.137 unchanged
#> 372 10 11 1 2.688 0.372 0.71 unchanged
#> 373 7 9 2 2.688 0.744 0.457 unchanged
#> 374 4 6 2 2.688 0.744 0.457 unchanged
#> 375 10 5 -5 2.688 -1.860 0.063 unchanged
#> 376 16 14 -2 2.688 -0.744 0.457 unchanged
#> 377 15 15 0 2.688 0.000 1 unchanged
#> 378 13 12 -1 2.688 -0.372 0.71 unchanged
#> 379 0 3 3 2.688 1.116 0.264 unchanged
#> 380 7 8 1 2.688 0.372 0.71 unchanged
#> 381 6 7 1 2.688 0.372 0.71 unchanged
#> 382 6 6 0 2.688 0.000 1 unchanged
#> 383 6 8 2 2.688 0.744 0.457 unchanged
#> 384 4 4 0 2.688 0.000 1 unchanged
#> 385 3 4 1 2.688 0.372 0.71 unchanged
#> 386 2 7 5 2.688 1.860 0.063 unchanged
#> 387 9 9 0 2.688 0.000 1 unchanged
#> 388 19 14 -5 2.688 -1.860 0.063 unchanged
#> 389 3 6 3 2.688 1.116 0.264 unchanged
#> 390 0 2 2 2.688 0.744 0.457 unchanged
#> 391 15 14 -1 2.688 -0.372 0.71 unchanged
#> 392 11 4 -7 2.688 -2.604 0.009 decreased
#> 393 5 6 1 2.688 0.372 0.71 unchanged
#> 394 2 1 -1 2.688 -0.372 0.71 unchanged
#> 395 7 13 6 2.688 2.232 0.026 increased
#> 396 13 11 -2 2.688 -0.744 0.457 unchanged
#> 397 15 14 -1 2.688 -0.372 0.71 unchanged
#> 398 2 4 2 2.688 0.744 0.457 unchanged
#> 399 13 6 -7 2.688 -2.604 0.009 decreased
#> 400 15 9 -6 2.688 -2.232 0.026 decreased
#> 401 7 8 1 2.688 0.372 0.71 unchanged
#> 402 3 3 0 2.688 0.000 1 unchanged
#> 403 9 12 3 2.688 1.116 0.264 unchanged
#> 404 17 17 0 2.688 0.000 1 unchanged
#> 405 1 4 3 2.688 1.116 0.264 unchanged
#> 406 4 2 -2 2.688 -0.744 0.457 unchanged
#> 407 7 10 3 2.688 1.116 0.264 unchanged
#> 408 7 11 4 2.688 1.488 0.137 unchanged
#> 409 12 12 0 2.688 0.000 1 unchanged
#> 410 8 6 -2 2.688 -0.744 0.457 unchanged
#> 411 8 4 -4 2.688 -1.488 0.137 unchanged
#> 412 14 11 -3 2.688 -1.116 0.264 unchanged
#> 413 5 3 -2 2.688 -0.744 0.457 unchanged
#> 414 16 17 1 2.688 0.372 0.71 unchanged
#> 415 11 15 4 2.688 1.488 0.137 unchanged
#> 416 15 12 -3 2.688 -1.116 0.264 unchanged
#> 417 14 15 1 2.688 0.372 0.71 unchanged
#> 418 5 6 1 2.688 0.372 0.71 unchanged
#> 419 5 10 5 2.688 1.860 0.063 unchanged
#> 420 10 13 3 2.688 1.116 0.264 unchanged
#> 421 3 2 -1 2.688 -0.372 0.71 unchanged
#> 422 17 17 0 2.688 0.000 1 unchanged
#> 423 11 11 0 2.688 0.000 1 unchanged
#> 424 14 13 -1 2.688 -0.372 0.71 unchanged
#> 425 16 9 -7 2.688 -2.604 0.009 decreased
#> 426 15 16 1 2.688 0.372 0.71 unchanged
#> 427 11 7 -4 2.688 -1.488 0.137 unchanged
#> 428 8 11 3 2.688 1.116 0.264 unchanged
#> 429 13 13 0 2.688 0.000 1 unchanged
#> 430 10 10 0 2.688 0.000 1 unchanged
#> 431 15 14 -1 2.688 -0.372 0.71 unchanged
#> 432 1 4 3 2.688 1.116 0.264 unchanged
#> 433 3 3 0 2.688 0.000 1 unchanged
#> 434 11 15 4 2.688 1.488 0.137 unchanged
#> 435 3 4 1 2.688 0.372 0.71 unchanged
#> 436 6 11 5 2.688 1.860 0.063 unchanged
#> 437 2 0 -2 2.688 -0.744 0.457 unchanged
#> 438 13 14 1 2.688 0.372 0.71 unchanged
#> 439 18 14 -4 2.688 -1.488 0.137 unchanged
#> 440 6 13 7 2.688 2.604 0.009 increased
#> 441 14 12 -2 2.688 -0.744 0.457 unchanged
#> 442 4 5 1 2.688 0.372 0.71 unchanged
#> 443 10 9 -1 2.688 -0.372 0.71 unchanged
#> 444 18 18 0 2.688 0.000 1 unchanged
#> 445 17 16 -1 2.688 -0.372 0.71 unchanged
#> 446 16 17 1 2.688 0.372 0.71 unchanged
#> 447 0 0 0 2.688 0.000 1 unchanged
#> 448 12 10 -2 2.688 -0.744 0.457 unchanged
#> 449 4 7 3 2.688 1.116 0.264 unchanged
#> 450 1 4 3 2.688 1.116 0.264 unchanged
#> 451 19 18 -1 2.688 -0.372 0.71 unchanged
#> 452 8 5 -3 2.688 -1.116 0.264 unchanged
#> 453 8 11 3 2.688 1.116 0.264 unchanged
#> 454 5 9 4 2.688 1.488 0.137 unchanged
#> 455 18 17 -1 2.688 -0.372 0.71 unchanged
#> 456 12 11 -1 2.688 -0.372 0.71 unchanged
#> 457 5 9 4 2.688 1.488 0.137 unchanged
#> 458 2 5 3 2.688 1.116 0.264 unchanged
#> 459 1 2 1 2.688 0.372 0.71 unchanged
#> 460 19 18 -1 2.688 -0.372 0.71 unchanged
#> 461 15 17 2 2.688 0.744 0.457 unchanged
#> 462 17 13 -4 2.688 -1.488 0.137 unchanged
#> 463 13 15 2 2.688 0.744 0.457 unchanged
#> 464 14 14 0 2.688 0.000 1 unchanged
#> 465 6 9 3 2.688 1.116 0.264 unchanged
#> 466 9 5 -4 2.688 -1.488 0.137 unchanged
#> 467 16 15 -1 2.688 -0.372 0.71 unchanged
#> 468 3 2 -1 2.688 -0.372 0.71 unchanged
#> 469 1 7 6 2.688 2.232 0.026 increased
#> 470 13 10 -3 2.688 -1.116 0.264 unchanged
#> 471 5 4 -1 2.688 -0.372 0.71 unchanged
#> 472 6 7 1 2.688 0.372 0.71 unchanged
#> 473 20 19 -1 2.688 -0.372 0.71 unchanged
#> 474 7 9 2 2.688 0.744 0.457 unchanged
#> 475 1 1 0 2.688 0.000 1 unchanged
#> 476 15 13 -2 2.688 -0.744 0.457 unchanged
#> 477 16 11 -5 2.688 -1.860 0.063 unchanged
#> 478 16 12 -4 2.688 -1.488 0.137 unchanged
#> 479 11 10 -1 2.688 -0.372 0.71 unchanged
#> 480 15 16 1 2.688 0.372 0.71 unchanged
#> 481 7 8 1 2.688 0.372 0.71 unchanged
#> 482 15 12 -3 2.688 -1.116 0.264 unchanged
#> 483 15 16 1 2.688 0.372 0.71 unchanged
#> 484 12 11 -1 2.688 -0.372 0.71 unchanged
#> 485 12 10 -2 2.688 -0.744 0.457 unchanged
#> 486 5 8 3 2.688 1.116 0.264 unchanged
#> 487 8 12 4 2.688 1.488 0.137 unchanged
#> 488 11 13 2 2.688 0.744 0.457 unchanged
#> 489 16 17 1 2.688 0.372 0.71 unchanged
#> 490 7 8 1 2.688 0.372 0.71 unchanged
#> 491 19 18 -1 2.688 -0.372 0.71 unchanged
#> 492 4 5 1 2.688 0.372 0.71 unchanged
#> 493 19 16 -3 2.688 -1.116 0.264 unchanged
#> 494 8 9 1 2.688 0.372 0.71 unchanged
#> 495 10 15 5 2.688 1.860 0.063 unchanged
#> 496 6 7 1 2.688 0.372 0.71 unchanged
#> 497 11 8 -3 2.688 -1.116 0.264 unchanged
#> 498 3 9 6 2.688 2.232 0.026 increased
#> 499 8 8 0 2.688 0.000 1 unchanged
#> 500 7 11 4 2.688 1.488 0.137 unchanged
#> 501 13 16 3 2.688 1.116 0.264 unchanged
#> 502 11 10 -1 2.688 -0.372 0.71 unchanged
#> 503 0 1 1 2.688 0.372 0.71 unchanged
#> 504 4 5 1 2.688 0.372 0.71 unchanged
#> 505 4 6 2 2.688 0.744 0.457 unchanged
#> 506 12 10 -2 2.688 -0.744 0.457 unchanged
#> 507 18 16 -2 2.688 -0.744 0.457 unchanged
#> 508 13 14 1 2.688 0.372 0.71 unchanged
#> 509 5 7 2 2.688 0.744 0.457 unchanged
#> 510 8 10 2 2.688 0.744 0.457 unchanged
#> 511 6 10 4 2.688 1.488 0.137 unchanged
#> 512 7 9 2 2.688 0.744 0.457 unchanged
#> 513 5 5 0 2.688 0.000 1 unchanged
#> 514 5 10 5 2.688 1.860 0.063 unchanged
#> 515 9 11 2 2.688 0.744 0.457 unchanged
#> 516 17 17 0 2.688 0.000 1 unchanged
#> 517 14 13 -1 2.688 -0.372 0.71 unchanged
#> 518 8 15 7 2.688 2.604 0.009 increased
#> 519 14 14 0 2.688 0.000 1 unchanged
#> 520 13 8 -5 2.688 -1.860 0.063 unchanged
#> 521 14 12 -2 2.688 -0.744 0.457 unchanged
#> 522 6 2 -4 2.688 -1.488 0.137 unchanged
#> 523 17 14 -3 2.688 -1.116 0.264 unchanged
#> 524 13 13 0 2.688 0.000 1 unchanged
#> 525 14 14 0 2.688 0.000 1 unchanged
#> 526 16 12 -4 2.688 -1.488 0.137 unchanged
#> 527 12 10 -2 2.688 -0.744 0.457 unchanged
#> 528 15 16 1 2.688 0.372 0.71 unchanged
#> 529 13 10 -3 2.688 -1.116 0.264 unchanged
#> 530 9 10 1 2.688 0.372 0.71 unchanged
#> 531 12 7 -5 2.688 -1.860 0.063 unchanged
#> 532 20 20 0 2.688 0.000 1 unchanged
#> 533 17 12 -5 2.688 -1.860 0.063 unchanged
#> 534 6 8 2 2.688 0.744 0.457 unchanged
#> 535 19 18 -1 2.688 -0.372 0.71 unchanged
#> 536 12 12 0 2.688 0.000 1 unchanged
#> 537 10 7 -3 2.688 -1.116 0.264 unchanged
#> 538 6 4 -2 2.688 -0.744 0.457 unchanged
#> 539 8 8 0 2.688 0.000 1 unchanged
#> 540 10 12 2 2.688 0.744 0.457 unchanged
#> 541 4 7 3 2.688 1.116 0.264 unchanged
#> 542 2 2 0 2.688 0.000 1 unchanged
#> 543 6 5 -1 2.688 -0.372 0.71 unchanged
#> 544 12 10 -2 2.688 -0.744 0.457 unchanged
#> 545 4 5 1 2.688 0.372 0.71 unchanged
#> 546 11 10 -1 2.688 -0.372 0.71 unchanged
#> 547 14 12 -2 2.688 -0.744 0.457 unchanged
#> 548 13 15 2 2.688 0.744 0.457 unchanged
#> 549 12 9 -3 2.688 -1.116 0.264 unchanged
#> 550 11 11 0 2.688 0.000 1 unchanged
#> 551 8 2 -6 2.688 -2.232 0.026 decreased
#> 552 14 15 1 2.688 0.372 0.71 unchanged
#> 553 11 14 3 2.688 1.116 0.264 unchanged
#> 554 13 12 -1 2.688 -0.372 0.71 unchanged
#> 555 2 3 1 2.688 0.372 0.71 unchanged
#> 556 9 13 4 2.688 1.488 0.137 unchanged
#> 557 10 11 1 2.688 0.372 0.71 unchanged
#> 558 8 12 4 2.688 1.488 0.137 unchanged
#> 559 11 12 1 2.688 0.372 0.71 unchanged
#> 560 19 18 -1 2.688 -0.372 0.71 unchanged
#> 561 12 12 0 2.688 0.000 1 unchanged
#> 562 12 8 -4 2.688 -1.488 0.137 unchanged
#> 563 3 6 3 2.688 1.116 0.264 unchanged
#> 564 4 0 -4 2.688 -1.488 0.137 unchanged
#> 565 14 14 0 2.688 0.000 1 unchanged
#> 566 3 4 1 2.688 0.372 0.71 unchanged
#> 567 18 16 -2 2.688 -0.744 0.457 unchanged
#> 568 3 2 -1 2.688 -0.372 0.71 unchanged
#> 569 17 19 2 2.688 0.744 0.457 unchanged
#> 570 10 8 -2 2.688 -0.744 0.457 unchanged
#> 571 16 13 -3 2.688 -1.116 0.264 unchanged
#> 572 8 8 0 2.688 0.000 1 unchanged
#> 573 15 17 2 2.688 0.744 0.457 unchanged
#> 574 7 12 5 2.688 1.860 0.063 unchanged
#> 575 6 2 -4 2.688 -1.488 0.137 unchanged
#> 576 11 14 3 2.688 1.116 0.264 unchanged
#> 577 13 12 -1 2.688 -0.372 0.71 unchanged
#> 578 17 14 -3 2.688 -1.116 0.264 unchanged
#> 579 5 9 4 2.688 1.488 0.137 unchanged
#> 580 12 17 5 2.688 1.860 0.063 unchanged
#> 581 11 10 -1 2.688 -0.372 0.71 unchanged
#> 582 6 12 6 2.688 2.232 0.026 increased
#> 583 11 13 2 2.688 0.744 0.457 unchanged
#> 584 16 18 2 2.688 0.744 0.457 unchanged
#> 585 8 6 -2 2.688 -0.744 0.457 unchanged
#> 586 7 9 2 2.688 0.744 0.457 unchanged
#> 587 12 11 -1 2.688 -0.372 0.71 unchanged
#> 588 9 7 -2 2.688 -0.744 0.457 unchanged
#> 589 9 6 -3 2.688 -1.116 0.264 unchanged
#> 590 14 13 -1 2.688 -0.372 0.71 unchanged
#> 591 15 15 0 2.688 0.000 1 unchanged
#> 592 19 15 -4 2.688 -1.488 0.137 unchanged
#> 593 6 7 1 2.688 0.372 0.71 unchanged
#> 594 4 3 -1 2.688 -0.372 0.71 unchanged
#> 595 4 6 2 2.688 0.744 0.457 unchanged
#> 596 4 3 -1 2.688 -0.372 0.71 unchanged
#> 597 4 4 0 2.688 0.000 1 unchanged
#> 598 10 6 -4 2.688 -1.488 0.137 unchanged
#> 599 8 14 6 2.688 2.232 0.026 increased
#> 600 9 12 3 2.688 1.116 0.264 unchanged
#> 601 10 12 2 2.688 0.744 0.457 unchanged
#> 602 12 9 -3 2.688 -1.116 0.264 unchanged
#> 603 13 9 -4 2.688 -1.488 0.137 unchanged
#> 604 11 11 0 2.688 0.000 1 unchanged
#> 605 2 4 2 2.688 0.744 0.457 unchanged
#> 606 16 14 -2 2.688 -0.744 0.457 unchanged
#> 607 2 1 -1 2.688 -0.372 0.71 unchanged
#> 608 3 2 -1 2.688 -0.372 0.71 unchanged
#> 609 6 4 -2 2.688 -0.744 0.457 unchanged
#> 610 15 11 -4 2.688 -1.488 0.137 unchanged
#> 611 7 6 -1 2.688 -0.372 0.71 unchanged
#> 612 14 18 4 2.688 1.488 0.137 unchanged
#> 613 7 14 7 2.688 2.604 0.009 increased
#> 614 18 14 -4 2.688 -1.488 0.137 unchanged
#> 615 9 6 -3 2.688 -1.116 0.264 unchanged
#> 616 11 11 0 2.688 0.000 1 unchanged
#> 617 6 2 -4 2.688 -1.488 0.137 unchanged
#> 618 10 7 -3 2.688 -1.116 0.264 unchanged
#> 619 3 2 -1 2.688 -0.372 0.71 unchanged
#> 620 8 4 -4 2.688 -1.488 0.137 unchanged
#> 621 8 10 2 2.688 0.744 0.457 unchanged
#> 622 16 16 0 2.688 0.000 1 unchanged
#> 623 4 2 -2 2.688 -0.744 0.457 unchanged
#> 624 13 15 2 2.688 0.744 0.457 unchanged
#> 625 11 11 0 2.688 0.000 1 unchanged
#> 626 14 13 -1 2.688 -0.372 0.71 unchanged
#> 627 4 8 4 2.688 1.488 0.137 unchanged
#> 628 6 8 2 2.688 0.744 0.457 unchanged
#> 629 15 9 -6 2.688 -2.232 0.026 decreased
#> 630 2 3 1 2.688 0.372 0.71 unchanged
#> 631 2 3 1 2.688 0.372 0.71 unchanged
#> 632 8 6 -2 2.688 -0.744 0.457 unchanged
#> 633 8 4 -4 2.688 -1.488 0.137 unchanged
#> 634 12 18 6 2.688 2.232 0.026 increased
#> 635 15 15 0 2.688 0.000 1 unchanged
#> 636 10 10 0 2.688 0.000 1 unchanged
#> 637 3 3 0 2.688 0.000 1 unchanged
#> 638 14 15 1 2.688 0.372 0.71 unchanged
#> 639 9 6 -3 2.688 -1.116 0.264 unchanged
#> 640 2 5 3 2.688 1.116 0.264 unchanged
#> 641 14 17 3 2.688 1.116 0.264 unchanged
#> 642 4 2 -2 2.688 -0.744 0.457 unchanged
#> 643 12 13 1 2.688 0.372 0.71 unchanged
#> 644 10 7 -3 2.688 -1.116 0.264 unchanged
#> 645 3 4 1 2.688 0.372 0.71 unchanged
#> 646 4 2 -2 2.688 -0.744 0.457 unchanged
#> 647 2 6 4 2.688 1.488 0.137 unchanged
#> 648 11 8 -3 2.688 -1.116 0.264 unchanged
#> 649 10 10 0 2.688 0.000 1 unchanged
#> 650 17 17 0 2.688 0.000 1 unchanged
#> 651 8 10 2 2.688 0.744 0.457 unchanged
#> 652 8 9 1 2.688 0.372 0.71 unchanged
#> 653 17 17 0 2.688 0.000 1 unchanged
#> 654 15 13 -2 2.688 -0.744 0.457 unchanged
#> 655 14 19 5 2.688 1.860 0.063 unchanged
#> 656 10 14 4 2.688 1.488 0.137 unchanged
#> 657 12 13 1 2.688 0.372 0.71 unchanged
#> 658 7 12 5 2.688 1.860 0.063 unchanged
#> 659 11 12 1 2.688 0.372 0.71 unchanged
#> 660 13 10 -3 2.688 -1.116 0.264 unchanged
#> 661 7 7 0 2.688 0.000 1 unchanged
#> 662 8 6 -2 2.688 -0.744 0.457 unchanged
#> 663 7 5 -2 2.688 -0.744 0.457 unchanged
#> 664 14 10 -4 2.688 -1.488 0.137 unchanged
#> 665 17 19 2 2.688 0.744 0.457 unchanged
#> 666 9 6 -3 2.688 -1.116 0.264 unchanged
#> 667 3 3 0 2.688 0.000 1 unchanged
#> 668 15 11 -4 2.688 -1.488 0.137 unchanged
#> 669 7 8 1 2.688 0.372 0.71 unchanged
#> 670 12 12 0 2.688 0.000 1 unchanged
#> 671 13 13 0 2.688 0.000 1 unchanged
#> 672 16 20 4 2.688 1.488 0.137 unchanged
#> 673 13 9 -4 2.688 -1.488 0.137 unchanged
#> 674 14 16 2 2.688 0.744 0.457 unchanged
#> 675 7 2 -5 2.688 -1.860 0.063 unchanged
#> 676 10 6 -4 2.688 -1.488 0.137 unchanged
#> 677 10 12 2 2.688 0.744 0.457 unchanged
#> 678 8 9 1 2.688 0.372 0.71 unchanged
#> 679 4 7 3 2.688 1.116 0.264 unchanged
#> 680 2 4 2 2.688 0.744 0.457 unchanged
#> 681 13 10 -3 2.688 -1.116 0.264 unchanged
#> 682 5 12 7 2.688 2.604 0.009 increased
#> 683 5 6 1 2.688 0.372 0.71 unchanged
#> 684 10 7 -3 2.688 -1.116 0.264 unchanged
#> 685 13 12 -1 2.688 -0.372 0.71 unchanged
#> 686 17 19 2 2.688 0.744 0.457 unchanged
#> 687 11 12 1 2.688 0.372 0.71 unchanged
#> 688 4 10 6 2.688 2.232 0.026 increased
#> 689 6 4 -2 2.688 -0.744 0.457 unchanged
#> 690 3 5 2 2.688 0.744 0.457 unchanged
#> 691 11 14 3 2.688 1.116 0.264 unchanged
#> 692 7 2 -5 2.688 -1.860 0.063 unchanged
#> 693 8 10 2 2.688 0.744 0.457 unchanged
#> 694 13 11 -2 2.688 -0.744 0.457 unchanged
#> 695 13 16 3 2.688 1.116 0.264 unchanged
#> 696 16 15 -1 2.688 -0.372 0.71 unchanged
#> 697 16 12 -4 2.688 -1.488 0.137 unchanged
#> 698 3 3 0 2.688 0.000 1 unchanged
#> 699 12 15 3 2.688 1.116 0.264 unchanged
#> 700 12 16 4 2.688 1.488 0.137 unchanged
#> 701 3 3 0 2.688 0.000 1 unchanged
#> 702 20 20 0 2.688 0.000 1 unchanged
#> 703 7 10 3 2.688 1.116 0.264 unchanged
#> 704 9 13 4 2.688 1.488 0.137 unchanged
#> 705 5 7 2 2.688 0.744 0.457 unchanged
#> 706 2 2 0 2.688 0.000 1 unchanged
#> 707 13 16 3 2.688 1.116 0.264 unchanged
#> 708 5 7 2 2.688 0.744 0.457 unchanged
#> 709 8 7 -1 2.688 -0.372 0.71 unchanged
#> 710 15 18 3 2.688 1.116 0.264 unchanged
#> 711 3 1 -2 2.688 -0.744 0.457 unchanged
#> 712 5 5 0 2.688 0.000 1 unchanged
#> 713 5 3 -2 2.688 -0.744 0.457 unchanged
#> 714 15 16 1 2.688 0.372 0.71 unchanged
#> 715 12 10 -2 2.688 -0.744 0.457 unchanged
#> 716 9 6 -3 2.688 -1.116 0.264 unchanged
#> 717 5 2 -3 2.688 -1.116 0.264 unchanged
#> 718 3 4 1 2.688 0.372 0.71 unchanged
#> 719 2 6 4 2.688 1.488 0.137 unchanged
#> 720 4 6 2 2.688 0.744 0.457 unchanged
#> 721 10 12 2 2.688 0.744 0.457 unchanged
#> 722 16 14 -2 2.688 -0.744 0.457 unchanged
#> 723 3 2 -1 2.688 -0.372 0.71 unchanged
#> 724 13 8 -5 2.688 -1.860 0.063 unchanged
#> 725 17 15 -2 2.688 -0.744 0.457 unchanged
#> 726 8 8 0 2.688 0.000 1 unchanged
#> 727 8 10 2 2.688 0.744 0.457 unchanged
#> 728 16 12 -4 2.688 -1.488 0.137 unchanged
#> 729 11 15 4 2.688 1.488 0.137 unchanged
#> 730 4 8 4 2.688 1.488 0.137 unchanged
#> 731 5 6 1 2.688 0.372 0.71 unchanged
#> 732 4 3 -1 2.688 -0.372 0.71 unchanged
#> 733 8 6 -2 2.688 -0.744 0.457 unchanged
#> 734 18 19 1 2.688 0.372 0.71 unchanged
#> 735 10 11 1 2.688 0.372 0.71 unchanged
#> 736 10 12 2 2.688 0.744 0.457 unchanged
#> 737 18 20 2 2.688 0.744 0.457 unchanged
#> 738 11 5 -6 2.688 -2.232 0.026 decreased
#> 739 17 17 0 2.688 0.000 1 unchanged
#> 740 3 5 2 2.688 0.744 0.457 unchanged
#> 741 15 15 0 2.688 0.000 1 unchanged
#> 742 8 9 1 2.688 0.372 0.71 unchanged
#> 743 9 5 -4 2.688 -1.488 0.137 unchanged
#> 744 16 13 -3 2.688 -1.116 0.264 unchanged
#> 745 14 13 -1 2.688 -0.372 0.71 unchanged
#> 746 8 6 -2 2.688 -0.744 0.457 unchanged
#> 747 5 9 4 2.688 1.488 0.137 unchanged
#> 748 3 1 -2 2.688 -0.744 0.457 unchanged
#> 749 6 7 1 2.688 0.372 0.71 unchanged
#> 750 17 13 -4 2.688 -1.488 0.137 unchanged
#> 751 15 15 0 2.688 0.000 1 unchanged
#> 752 5 6 1 2.688 0.372 0.71 unchanged
#> 753 9 11 2 2.688 0.744 0.457 unchanged
#> 754 16 14 -2 2.688 -0.744 0.457 unchanged
#> 755 12 12 0 2.688 0.000 1 unchanged
#> 756 12 14 2 2.688 0.744 0.457 unchanged
#> 757 14 9 -5 2.688 -1.860 0.063 unchanged
#> 758 12 15 3 2.688 1.116 0.264 unchanged
#> 759 1 0 -1 2.688 -0.372 0.71 unchanged
#> 760 13 17 4 2.688 1.488 0.137 unchanged
#> 761 17 19 2 2.688 0.744 0.457 unchanged
#> 762 4 4 0 2.688 0.000 1 unchanged
#> 763 10 7 -3 2.688 -1.116 0.264 unchanged
#> 764 15 15 0 2.688 0.000 1 unchanged
#> 765 10 12 2 2.688 0.744 0.457 unchanged
#> 766 2 2 0 2.688 0.000 1 unchanged
#> 767 16 16 0 2.688 0.000 1 unchanged
#> 768 14 13 -1 2.688 -0.372 0.71 unchanged
#> 769 15 15 0 2.688 0.000 1 unchanged
#> 770 7 3 -4 2.688 -1.488 0.137 unchanged
#> 771 7 3 -4 2.688 -1.488 0.137 unchanged
#> 772 15 14 -1 2.688 -0.372 0.71 unchanged
#> 773 11 12 1 2.688 0.372 0.71 unchanged
#> 774 2 1 -1 2.688 -0.372 0.71 unchanged
#> 775 3 7 4 2.688 1.488 0.137 unchanged
#> 776 16 16 0 2.688 0.000 1 unchanged
#> 777 14 9 -5 2.688 -1.860 0.063 unchanged
#> 778 14 14 0 2.688 0.000 1 unchanged
#> 779 14 13 -1 2.688 -0.372 0.71 unchanged
#> 780 13 9 -4 2.688 -1.488 0.137 unchanged
#> 781 13 11 -2 2.688 -0.744 0.457 unchanged
#> 782 5 13 8 2.688 2.976 0.003 increased
#> 783 13 12 -1 2.688 -0.372 0.71 unchanged
#> 784 8 7 -1 2.688 -0.372 0.71 unchanged
#> 785 17 16 -1 2.688 -0.372 0.71 unchanged
#> 786 10 11 1 2.688 0.372 0.71 unchanged
#> 787 12 10 -2 2.688 -0.744 0.457 unchanged
#> 788 7 9 2 2.688 0.744 0.457 unchanged
#> 789 2 2 0 2.688 0.000 1 unchanged
#> 790 1 3 2 2.688 0.744 0.457 unchanged
#> 791 3 8 5 2.688 1.860 0.063 unchanged
#> 792 14 16 2 2.688 0.744 0.457 unchanged
#> 793 4 7 3 2.688 1.116 0.264 unchanged
#> 794 15 17 2 2.688 0.744 0.457 unchanged
#> 795 15 13 -2 2.688 -0.744 0.457 unchanged
#> 796 7 8 1 2.688 0.372 0.71 unchanged
#> 797 6 4 -2 2.688 -0.744 0.457 unchanged
#> 798 7 6 -1 2.688 -0.372 0.71 unchanged
#> 799 11 8 -3 2.688 -1.116 0.264 unchanged
#> 800 8 12 4 2.688 1.488 0.137 unchanged
#> 801 6 3 -3 2.688 -1.116 0.264 unchanged
#> 802 7 2 -5 2.688 -1.860 0.063 unchanged
#> 803 9 9 0 2.688 0.000 1 unchanged
#> 804 17 14 -3 2.688 -1.116 0.264 unchanged
#> 805 6 7 1 2.688 0.372 0.71 unchanged
#> 806 14 13 -1 2.688 -0.372 0.71 unchanged
#> 807 6 13 7 2.688 2.604 0.009 increased
#> 808 7 9 2 2.688 0.744 0.457 unchanged
#> 809 17 17 0 2.688 0.000 1 unchanged
#> 810 3 6 3 2.688 1.116 0.264 unchanged
#> 811 15 18 3 2.688 1.116 0.264 unchanged
#> 812 10 10 0 2.688 0.000 1 unchanged
#> 813 7 2 -5 2.688 -1.860 0.063 unchanged
#> 814 13 14 1 2.688 0.372 0.71 unchanged
#> 815 8 10 2 2.688 0.744 0.457 unchanged
#> 816 7 7 0 2.688 0.000 1 unchanged
#> 817 15 5 -10 2.688 -3.721 0 decreased
#> 818 11 11 0 2.688 0.000 1 unchanged
#> 819 8 14 6 2.688 2.232 0.026 increased
#> 820 7 5 -2 2.688 -0.744 0.457 unchanged
#> 821 12 12 0 2.688 0.000 1 unchanged
#> 822 10 13 3 2.688 1.116 0.264 unchanged
#> 823 3 3 0 2.688 0.000 1 unchanged
#> 824 17 18 1 2.688 0.372 0.71 unchanged
#> 825 7 6 -1 2.688 -0.372 0.71 unchanged
#> 826 5 7 2 2.688 0.744 0.457 unchanged
#> 827 15 14 -1 2.688 -0.372 0.71 unchanged
#> 828 3 7 4 2.688 1.488 0.137 unchanged
#> 829 4 3 -1 2.688 -0.372 0.71 unchanged
#> 830 20 17 -3 2.688 -1.116 0.264 unchanged
#> 831 8 5 -3 2.688 -1.116 0.264 unchanged
#> 832 13 18 5 2.688 1.860 0.063 unchanged
#> 833 15 15 0 2.688 0.000 1 unchanged
#> 834 16 17 1 2.688 0.372 0.71 unchanged
#> 835 6 6 0 2.688 0.000 1 unchanged
#> 836 16 16 0 2.688 0.000 1 unchanged
#> 837 9 9 0 2.688 0.000 1 unchanged
#> 838 10 16 6 2.688 2.232 0.026 increased
#> 839 10 11 1 2.688 0.372 0.71 unchanged
#> 840 16 17 1 2.688 0.372 0.71 unchanged
#> 841 15 15 0 2.688 0.000 1 unchanged
#> 842 13 13 0 2.688 0.000 1 unchanged
#> 843 15 16 1 2.688 0.372 0.71 unchanged
#> 844 10 7 -3 2.688 -1.116 0.264 unchanged
#> 845 12 9 -3 2.688 -1.116 0.264 unchanged
#> 846 12 12 0 2.688 0.000 1 unchanged
#> 847 8 7 -1 2.688 -0.372 0.71 unchanged
#> 848 7 3 -4 2.688 -1.488 0.137 unchanged
#> 849 5 5 0 2.688 0.000 1 unchanged
#> 850 19 16 -3 2.688 -1.116 0.264 unchanged
#> 851 15 15 0 2.688 0.000 1 unchanged
#> 852 13 8 -5 2.688 -1.860 0.063 unchanged
#> 853 9 10 1 2.688 0.372 0.71 unchanged
#> 854 8 8 0 2.688 0.000 1 unchanged
#> 855 9 9 0 2.688 0.000 1 unchanged
#> 856 12 13 1 2.688 0.372 0.71 unchanged
#> 857 10 7 -3 2.688 -1.116 0.264 unchanged
#> 858 13 10 -3 2.688 -1.116 0.264 unchanged
#> 859 10 9 -1 2.688 -0.372 0.71 unchanged
#> 860 5 8 3 2.688 1.116 0.264 unchanged
#> 861 5 3 -2 2.688 -0.744 0.457 unchanged
#> 862 13 14 1 2.688 0.372 0.71 unchanged
#> 863 3 6 3 2.688 1.116 0.264 unchanged
#> 864 8 4 -4 2.688 -1.488 0.137 unchanged
#> 865 10 13 3 2.688 1.116 0.264 unchanged
#> 866 12 12 0 2.688 0.000 1 unchanged
#> 867 9 10 1 2.688 0.372 0.71 unchanged
#> 868 11 13 2 2.688 0.744 0.457 unchanged
#> 869 10 7 -3 2.688 -1.116 0.264 unchanged
#> 870 13 13 0 2.688 0.000 1 unchanged
#> 871 14 13 -1 2.688 -0.372 0.71 unchanged
#> 872 8 10 2 2.688 0.744 0.457 unchanged
#> 873 1 1 0 2.688 0.000 1 unchanged
#> 874 7 13 6 2.688 2.232 0.026 increased
#> 875 14 16 2 2.688 0.744 0.457 unchanged
#> 876 9 8 -1 2.688 -0.372 0.71 unchanged
#> 877 16 16 0 2.688 0.000 1 unchanged
#> 878 14 15 1 2.688 0.372 0.71 unchanged
#> 879 8 10 2 2.688 0.744 0.457 unchanged
#> 880 6 2 -4 2.688 -1.488 0.137 unchanged
#> 881 5 2 -3 2.688 -1.116 0.264 unchanged
#> 882 6 10 4 2.688 1.488 0.137 unchanged
#> 883 11 11 0 2.688 0.000 1 unchanged
#> 884 6 5 -1 2.688 -0.372 0.71 unchanged
#> 885 14 14 0 2.688 0.000 1 unchanged
#> 886 3 7 4 2.688 1.488 0.137 unchanged
#> 887 3 9 6 2.688 2.232 0.026 increased
#> 888 10 7 -3 2.688 -1.116 0.264 unchanged
#> 889 2 6 4 2.688 1.488 0.137 unchanged
#> 890 15 11 -4 2.688 -1.488 0.137 unchanged
#> 891 10 6 -4 2.688 -1.488 0.137 unchanged
#> 892 10 10 0 2.688 0.000 1 unchanged
#> 893 17 16 -1 2.688 -0.372 0.71 unchanged
#> 894 11 12 1 2.688 0.372 0.71 unchanged
#> 895 9 11 2 2.688 0.744 0.457 unchanged
#> 896 15 13 -2 2.688 -0.744 0.457 unchanged
#> 897 17 16 -1 2.688 -0.372 0.71 unchanged
#> 898 7 9 2 2.688 0.744 0.457 unchanged
#> 899 10 8 -2 2.688 -0.744 0.457 unchanged
#> 900 6 5 -1 2.688 -0.372 0.71 unchanged
#> 901 7 6 -1 2.688 -0.372 0.71 unchanged
#> 902 16 19 3 2.688 1.116 0.264 unchanged
#> 903 16 19 3 2.688 1.116 0.264 unchanged
#> 904 12 9 -3 2.688 -1.116 0.264 unchanged
#> 905 6 7 1 2.688 0.372 0.71 unchanged
#> 906 19 20 1 2.688 0.372 0.71 unchanged
#> 907 15 11 -4 2.688 -1.488 0.137 unchanged
#> 908 10 5 -5 2.688 -1.860 0.063 unchanged
#> 909 2 0 -2 2.688 -0.744 0.457 unchanged
#> 910 18 10 -8 2.688 -2.976 0.003 decreased
#> 911 2 0 -2 2.688 -0.744 0.457 unchanged
#> 912 20 17 -3 2.688 -1.116 0.264 unchanged
#> 913 4 2 -2 2.688 -0.744 0.457 unchanged
#> 914 16 17 1 2.688 0.372 0.71 unchanged
#> 915 14 15 1 2.688 0.372 0.71 unchanged
#> 916 18 13 -5 2.688 -1.860 0.063 unchanged
#> 917 16 17 1 2.688 0.372 0.71 unchanged
#> 918 15 18 3 2.688 1.116 0.264 unchanged
#> 919 13 10 -3 2.688 -1.116 0.264 unchanged
#> 920 11 8 -3 2.688 -1.116 0.264 unchanged
#> 921 4 2 -2 2.688 -0.744 0.457 unchanged
#> 922 6 10 4 2.688 1.488 0.137 unchanged
#> 923 12 11 -1 2.688 -0.372 0.71 unchanged
#> 924 18 18 0 2.688 0.000 1 unchanged
#> 925 5 5 0 2.688 0.000 1 unchanged
#> 926 19 19 0 2.688 0.000 1 unchanged
#> 927 7 5 -2 2.688 -0.744 0.457 unchanged
#> 928 9 3 -6 2.688 -2.232 0.026 decreased
#> 929 15 19 4 2.688 1.488 0.137 unchanged
#> 930 15 9 -6 2.688 -2.232 0.026 decreased
#> 931 11 11 0 2.688 0.000 1 unchanged
#> 932 12 10 -2 2.688 -0.744 0.457 unchanged
#> 933 12 13 1 2.688 0.372 0.71 unchanged
#> 934 9 6 -3 2.688 -1.116 0.264 unchanged
#> 935 14 14 0 2.688 0.000 1 unchanged
#> 936 6 7 1 2.688 0.372 0.71 unchanged
#> 937 6 6 0 2.688 0.000 1 unchanged
#> 938 8 10 2 2.688 0.744 0.457 unchanged
#> 939 3 2 -1 2.688 -0.372 0.71 unchanged
#> 940 11 10 -1 2.688 -0.372 0.71 unchanged
#> 941 12 15 3 2.688 1.116 0.264 unchanged
#> 942 13 14 1 2.688 0.372 0.71 unchanged
#> 943 12 8 -4 2.688 -1.488 0.137 unchanged
#> 944 15 13 -2 2.688 -0.744 0.457 unchanged
#> 945 11 12 1 2.688 0.372 0.71 unchanged
#> 946 11 11 0 2.688 0.000 1 unchanged
#> 947 11 10 -1 2.688 -0.372 0.71 unchanged
#> 948 10 13 3 2.688 1.116 0.264 unchanged
#> 949 1 2 1 2.688 0.372 0.71 unchanged
#> 950 7 12 5 2.688 1.860 0.063 unchanged
#> 951 8 6 -2 2.688 -0.744 0.457 unchanged
#> 952 15 12 -3 2.688 -1.116 0.264 unchanged
#> 953 7 4 -3 2.688 -1.116 0.264 unchanged
#> 954 2 6 4 2.688 1.488 0.137 unchanged
#> 955 6 5 -1 2.688 -0.372 0.71 unchanged
#> 956 3 3 0 2.688 0.000 1 unchanged
#> 957 5 5 0 2.688 0.000 1 unchanged
#> 958 6 6 0 2.688 0.000 1 unchanged
#> 959 13 17 4 2.688 1.488 0.137 unchanged
#> 960 6 7 1 2.688 0.372 0.71 unchanged
#> 961 3 2 -1 2.688 -0.372 0.71 unchanged
#> 962 12 11 -1 2.688 -0.372 0.71 unchanged
#> 963 6 4 -2 2.688 -0.744 0.457 unchanged
#> 964 17 12 -5 2.688 -1.860 0.063 unchanged
#> 965 5 7 2 2.688 0.744 0.457 unchanged
#> 966 13 16 3 2.688 1.116 0.264 unchanged
#> 967 15 16 1 2.688 0.372 0.71 unchanged
#> 968 12 9 -3 2.688 -1.116 0.264 unchanged
#> 969 15 13 -2 2.688 -0.744 0.457 unchanged
#> 970 14 16 2 2.688 0.744 0.457 unchanged
#> 971 6 7 1 2.688 0.372 0.71 unchanged
#> 972 16 16 0 2.688 0.000 1 unchanged
#> 973 3 1 -2 2.688 -0.744 0.457 unchanged
#> 974 5 5 0 2.688 0.000 1 unchanged
#> 975 7 3 -4 2.688 -1.488 0.137 unchanged
#> 976 13 13 0 2.688 0.000 1 unchanged
#> 977 10 12 2 2.688 0.744 0.457 unchanged
#> 978 2 4 2 2.688 0.744 0.457 unchanged
#> 979 2 9 7 2.688 2.604 0.009 increased
#> 980 10 9 -1 2.688 -0.372 0.71 unchanged
#> 981 4 1 -3 2.688 -1.116 0.264 unchanged
#> 982 7 4 -3 2.688 -1.116 0.264 unchanged
#> 983 17 12 -5 2.688 -1.860 0.063 unchanged
#> 984 18 16 -2 2.688 -0.744 0.457 unchanged
#> 985 16 11 -5 2.688 -1.860 0.063 unchanged
#> 986 5 3 -2 2.688 -0.744 0.457 unchanged
#> 987 13 14 1 2.688 0.372 0.71 unchanged
#> 988 11 8 -3 2.688 -1.116 0.264 unchanged
#> 989 2 12 10 2.688 3.721 0 increased
#> 990 9 11 2 2.688 0.744 0.457 unchanged
#> 991 11 6 -5 2.688 -1.860 0.063 unchanged
#> 992 11 10 -1 2.688 -0.372 0.71 unchanged
#> 993 8 6 -2 2.688 -0.744 0.457 unchanged
#> 994 1 4 3 2.688 1.116 0.264 unchanged
#> 995 10 7 -3 2.688 -1.116 0.264 unchanged
#> 996 11 5 -6 2.688 -2.232 0.026 decreased
#> 997 7 6 -1 2.688 -0.372 0.71 unchanged
#> 998 10 12 2 2.688 0.744 0.457 unchanged
#> 999 11 7 -4 2.688 -1.488 0.137 unchanged
#> 1000 1 2 1 2.688 0.372 0.71 unchanged
# allows SEM.post != SEM.pre
(istats.post <- itemstats(dat_post)$overall)
#> N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
#> 1000 9.745 4.774 0.206 0.063 0.84 1.91
SEM.alpha.post <- istats.post$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 18 19 1 2.694 0.371 0.711
#> 2 18 9 -9 2.694 -3.340 0.001
#> 3 15 9 -6 2.694 -2.227 0.026
#> 4 11 10 -1 2.694 -0.371 0.711
#> 5 4 5 1 2.694 0.371 0.711
#> 6 4 8 4 2.694 1.485 0.138
#> 7 11 8 -3 2.694 -1.113 0.266
#> 8 11 15 4 2.694 1.485 0.138
#> 9 3 3 0 2.694 0.000 1
#> 10 4 8 4 2.694 1.485 0.138
#> 11 1 5 4 2.694 1.485 0.138
#> 12 16 14 -2 2.694 -0.742 0.458
#> 13 12 10 -2 2.694 -0.742 0.458
#> 14 11 10 -1 2.694 -0.371 0.711
#> 15 17 18 1 2.694 0.371 0.711
#> 16 1 4 3 2.694 1.113 0.266
#> 17 10 8 -2 2.694 -0.742 0.458
#> 18 12 11 -1 2.694 -0.371 0.711
#> 19 15 12 -3 2.694 -1.113 0.266
#> 20 16 10 -6 2.694 -2.227 0.026
#> 21 7 6 -1 2.694 -0.371 0.711
#> 22 7 12 5 2.694 1.856 0.063
#> 23 2 4 2 2.694 0.742 0.458
#> 24 5 7 2 2.694 0.742 0.458
#> 25 14 15 1 2.694 0.371 0.711
#> 26 9 6 -3 2.694 -1.113 0.266
#> 27 17 17 0 2.694 0.000 1
#> 28 4 9 5 2.694 1.856 0.063
#> 29 14 16 2 2.694 0.742 0.458
#> 30 4 7 3 2.694 1.113 0.266
#> 31 2 0 -2 2.694 -0.742 0.458
#> 32 9 6 -3 2.694 -1.113 0.266
#> 33 20 20 0 2.694 0.000 1
#> 34 9 6 -3 2.694 -1.113 0.266
#> 35 3 4 1 2.694 0.371 0.711
#> 36 14 15 1 2.694 0.371 0.711
#> 37 8 9 1 2.694 0.371 0.711
#> 38 15 13 -2 2.694 -0.742 0.458
#> 39 9 12 3 2.694 1.113 0.266
#> 40 18 18 0 2.694 0.000 1
#> 41 11 10 -1 2.694 -0.371 0.711
#> 42 12 9 -3 2.694 -1.113 0.266
#> 43 8 7 -1 2.694 -0.371 0.711
#> 44 10 11 1 2.694 0.371 0.711
#> 45 7 10 3 2.694 1.113 0.266
#> 46 8 9 1 2.694 0.371 0.711
#> 47 6 8 2 2.694 0.742 0.458
#> 48 6 7 1 2.694 0.371 0.711
#> 49 6 8 2 2.694 0.742 0.458
#> 50 8 11 3 2.694 1.113 0.266
#> 51 13 17 4 2.694 1.485 0.138
#> 52 6 6 0 2.694 0.000 1
#> 53 19 13 -6 2.694 -2.227 0.026
#> 54 6 11 5 2.694 1.856 0.063
#> 55 9 8 -1 2.694 -0.371 0.711
#> 56 7 8 1 2.694 0.371 0.711
#> 57 9 6 -3 2.694 -1.113 0.266
#> 58 3 3 0 2.694 0.000 1
#> 59 10 8 -2 2.694 -0.742 0.458
#> 60 14 14 0 2.694 0.000 1
#> 61 12 12 0 2.694 0.000 1
#> 62 15 14 -1 2.694 -0.371 0.711
#> 63 13 12 -1 2.694 -0.371 0.711
#> 64 5 5 0 2.694 0.000 1
#> 65 5 4 -1 2.694 -0.371 0.711
#> 66 5 4 -1 2.694 -0.371 0.711
#> 67 18 14 -4 2.694 -1.485 0.138
#> 68 9 8 -1 2.694 -0.371 0.711
#> 69 11 9 -2 2.694 -0.742 0.458
#> 70 19 17 -2 2.694 -0.742 0.458
#> 71 9 5 -4 2.694 -1.485 0.138
#> 72 16 15 -1 2.694 -0.371 0.711
#> 73 10 9 -1 2.694 -0.371 0.711
#> 74 11 11 0 2.694 0.000 1
#> 75 14 10 -4 2.694 -1.485 0.138
#> 76 14 15 1 2.694 0.371 0.711
#> 77 5 4 -1 2.694 -0.371 0.711
#> 78 11 9 -2 2.694 -0.742 0.458
#> 79 15 10 -5 2.694 -1.856 0.063
#> 80 11 11 0 2.694 0.000 1
#> 81 10 8 -2 2.694 -0.742 0.458
#> 82 12 12 0 2.694 0.000 1
#> 83 11 11 0 2.694 0.000 1
#> 84 5 1 -4 2.694 -1.485 0.138
#> 85 7 9 2 2.694 0.742 0.458
#> 86 7 10 3 2.694 1.113 0.266
#> 87 3 7 4 2.694 1.485 0.138
#> 88 9 11 2 2.694 0.742 0.458
#> 89 8 9 1 2.694 0.371 0.711
#> 90 12 11 -1 2.694 -0.371 0.711
#> 91 6 1 -5 2.694 -1.856 0.063
#> 92 6 8 2 2.694 0.742 0.458
#> 93 3 5 2 2.694 0.742 0.458
#> 94 12 12 0 2.694 0.000 1
#> 95 18 16 -2 2.694 -0.742 0.458
#> 96 9 7 -2 2.694 -0.742 0.458
#> 97 8 11 3 2.694 1.113 0.266
#> 98 7 7 0 2.694 0.000 1
#> 99 12 11 -1 2.694 -0.371 0.711
#> 100 10 10 0 2.694 0.000 1
#> 101 5 5 0 2.694 0.000 1
#> 102 14 15 1 2.694 0.371 0.711
#> 103 9 9 0 2.694 0.000 1
#> 104 8 15 7 2.694 2.598 0.009
#> 105 2 3 1 2.694 0.371 0.711
#> 106 7 10 3 2.694 1.113 0.266
#> 107 12 12 0 2.694 0.000 1
#> 108 2 2 0 2.694 0.000 1
#> 109 14 13 -1 2.694 -0.371 0.711
#> 110 6 4 -2 2.694 -0.742 0.458
#> 111 15 10 -5 2.694 -1.856 0.063
#> 112 5 5 0 2.694 0.000 1
#> 113 15 18 3 2.694 1.113 0.266
#> 114 2 0 -2 2.694 -0.742 0.458
#> 115 9 12 3 2.694 1.113 0.266
#> 116 14 14 0 2.694 0.000 1
#> 117 10 7 -3 2.694 -1.113 0.266
#> 118 6 5 -1 2.694 -0.371 0.711
#> 119 12 9 -3 2.694 -1.113 0.266
#> 120 7 3 -4 2.694 -1.485 0.138
#> 121 9 12 3 2.694 1.113 0.266
#> 122 2 6 4 2.694 1.485 0.138
#> 123 9 6 -3 2.694 -1.113 0.266
#> 124 2 5 3 2.694 1.113 0.266
#> 125 12 12 0 2.694 0.000 1
#> 126 16 19 3 2.694 1.113 0.266
#> 127 13 14 1 2.694 0.371 0.711
#> 128 13 14 1 2.694 0.371 0.711
#> 129 14 15 1 2.694 0.371 0.711
#> 130 7 14 7 2.694 2.598 0.009
#> 131 10 11 1 2.694 0.371 0.711
#> 132 3 3 0 2.694 0.000 1
#> 133 15 15 0 2.694 0.000 1
#> 134 18 19 1 2.694 0.371 0.711
#> 135 2 5 3 2.694 1.113 0.266
#> 136 12 10 -2 2.694 -0.742 0.458
#> 137 12 14 2 2.694 0.742 0.458
#> 138 6 3 -3 2.694 -1.113 0.266
#> 139 13 9 -4 2.694 -1.485 0.138
#> 140 8 5 -3 2.694 -1.113 0.266
#> 141 18 17 -1 2.694 -0.371 0.711
#> 142 15 15 0 2.694 0.000 1
#> 143 7 9 2 2.694 0.742 0.458
#> 144 14 10 -4 2.694 -1.485 0.138
#> 145 3 5 2 2.694 0.742 0.458
#> 146 1 2 1 2.694 0.371 0.711
#> 147 5 6 1 2.694 0.371 0.711
#> 148 8 8 0 2.694 0.000 1
#> 149 13 15 2 2.694 0.742 0.458
#> 150 9 9 0 2.694 0.000 1
#> 151 8 9 1 2.694 0.371 0.711
#> 152 2 1 -1 2.694 -0.371 0.711
#> 153 3 3 0 2.694 0.000 1
#> 154 7 5 -2 2.694 -0.742 0.458
#> 155 16 13 -3 2.694 -1.113 0.266
#> 156 9 12 3 2.694 1.113 0.266
#> 157 15 17 2 2.694 0.742 0.458
#> 158 10 5 -5 2.694 -1.856 0.063
#> 159 8 10 2 2.694 0.742 0.458
#> 160 17 11 -6 2.694 -2.227 0.026
#> 161 14 8 -6 2.694 -2.227 0.026
#> 162 8 8 0 2.694 0.000 1
#> 163 3 5 2 2.694 0.742 0.458
#> 164 16 8 -8 2.694 -2.969 0.003
#> 165 9 7 -2 2.694 -0.742 0.458
#> 166 7 8 1 2.694 0.371 0.711
#> 167 15 15 0 2.694 0.000 1
#> 168 15 18 3 2.694 1.113 0.266
#> 169 3 2 -1 2.694 -0.371 0.711
#> 170 1 2 1 2.694 0.371 0.711
#> 171 2 0 -2 2.694 -0.742 0.458
#> 172 20 15 -5 2.694 -1.856 0.063
#> 173 10 12 2 2.694 0.742 0.458
#> 174 9 3 -6 2.694 -2.227 0.026
#> 175 5 15 10 2.694 3.712 0
#> 176 9 7 -2 2.694 -0.742 0.458
#> 177 15 16 1 2.694 0.371 0.711
#> 178 2 5 3 2.694 1.113 0.266
#> 179 18 20 2 2.694 0.742 0.458
#> 180 10 8 -2 2.694 -0.742 0.458
#> 181 6 6 0 2.694 0.000 1
#> 182 3 5 2 2.694 0.742 0.458
#> 183 9 7 -2 2.694 -0.742 0.458
#> 184 7 10 3 2.694 1.113 0.266
#> 185 6 3 -3 2.694 -1.113 0.266
#> 186 7 5 -2 2.694 -0.742 0.458
#> 187 7 4 -3 2.694 -1.113 0.266
#> 188 10 9 -1 2.694 -0.371 0.711
#> 189 17 12 -5 2.694 -1.856 0.063
#> 190 2 4 2 2.694 0.742 0.458
#> 191 16 15 -1 2.694 -0.371 0.711
#> 192 6 9 3 2.694 1.113 0.266
#> 193 10 13 3 2.694 1.113 0.266
#> 194 2 7 5 2.694 1.856 0.063
#> 195 5 3 -2 2.694 -0.742 0.458
#> 196 12 8 -4 2.694 -1.485 0.138
#> 197 5 1 -4 2.694 -1.485 0.138
#> 198 5 2 -3 2.694 -1.113 0.266
#> 199 17 17 0 2.694 0.000 1
#> 200 4 2 -2 2.694 -0.742 0.458
#> 201 13 13 0 2.694 0.000 1
#> 202 14 12 -2 2.694 -0.742 0.458
#> 203 2 2 0 2.694 0.000 1
#> 204 11 9 -2 2.694 -0.742 0.458
#> 205 10 11 1 2.694 0.371 0.711
#> 206 13 11 -2 2.694 -0.742 0.458
#> 207 17 18 1 2.694 0.371 0.711
#> 208 14 15 1 2.694 0.371 0.711
#> 209 18 18 0 2.694 0.000 1
#> 210 2 0 -2 2.694 -0.742 0.458
#> 211 9 11 2 2.694 0.742 0.458
#> 212 10 12 2 2.694 0.742 0.458
#> 213 16 14 -2 2.694 -0.742 0.458
#> 214 2 2 0 2.694 0.000 1
#> 215 3 4 1 2.694 0.371 0.711
#> 216 15 17 2 2.694 0.742 0.458
#> 217 14 12 -2 2.694 -0.742 0.458
#> 218 3 5 2 2.694 0.742 0.458
#> 219 9 8 -1 2.694 -0.371 0.711
#> 220 0 1 1 2.694 0.371 0.711
#> 221 14 12 -2 2.694 -0.742 0.458
#> 222 2 1 -1 2.694 -0.371 0.711
#> 223 5 10 5 2.694 1.856 0.063
#> 224 8 15 7 2.694 2.598 0.009
#> 225 12 14 2 2.694 0.742 0.458
#> 226 14 14 0 2.694 0.000 1
#> 227 11 11 0 2.694 0.000 1
#> 228 9 9 0 2.694 0.000 1
#> 229 17 15 -2 2.694 -0.742 0.458
#> 230 2 2 0 2.694 0.000 1
#> 231 6 9 3 2.694 1.113 0.266
#> 232 9 14 5 2.694 1.856 0.063
#> 233 13 13 0 2.694 0.000 1
#> 234 13 17 4 2.694 1.485 0.138
#> 235 13 6 -7 2.694 -2.598 0.009
#> 236 8 8 0 2.694 0.000 1
#> 237 8 9 1 2.694 0.371 0.711
#> 238 6 12 6 2.694 2.227 0.026
#> 239 9 9 0 2.694 0.000 1
#> 240 7 12 5 2.694 1.856 0.063
#> 241 18 18 0 2.694 0.000 1
#> 242 4 3 -1 2.694 -0.371 0.711
#> 243 1 2 1 2.694 0.371 0.711
#> 244 3 1 -2 2.694 -0.742 0.458
#> 245 6 5 -1 2.694 -0.371 0.711
#> 246 4 4 0 2.694 0.000 1
#> 247 17 17 0 2.694 0.000 1
#> 248 20 18 -2 2.694 -0.742 0.458
#> 249 8 10 2 2.694 0.742 0.458
#> 250 15 18 3 2.694 1.113 0.266
#> 251 15 13 -2 2.694 -0.742 0.458
#> 252 8 8 0 2.694 0.000 1
#> 253 8 8 0 2.694 0.000 1
#> 254 11 13 2 2.694 0.742 0.458
#> 255 18 16 -2 2.694 -0.742 0.458
#> 256 10 11 1 2.694 0.371 0.711
#> 257 18 16 -2 2.694 -0.742 0.458
#> 258 10 11 1 2.694 0.371 0.711
#> 259 4 3 -1 2.694 -0.371 0.711
#> 260 11 14 3 2.694 1.113 0.266
#> 261 14 11 -3 2.694 -1.113 0.266
#> 262 14 13 -1 2.694 -0.371 0.711
#> 263 19 17 -2 2.694 -0.742 0.458
#> 264 4 6 2 2.694 0.742 0.458
#> 265 17 17 0 2.694 0.000 1
#> 266 9 12 3 2.694 1.113 0.266
#> 267 4 7 3 2.694 1.113 0.266
#> 268 15 12 -3 2.694 -1.113 0.266
#> 269 7 7 0 2.694 0.000 1
#> 270 8 11 3 2.694 1.113 0.266
#> 271 1 2 1 2.694 0.371 0.711
#> 272 8 6 -2 2.694 -0.742 0.458
#> 273 6 6 0 2.694 0.000 1
#> 274 17 16 -1 2.694 -0.371 0.711
#> 275 13 11 -2 2.694 -0.742 0.458
#> 276 2 1 -1 2.694 -0.371 0.711
#> 277 9 10 1 2.694 0.371 0.711
#> 278 2 0 -2 2.694 -0.742 0.458
#> 279 11 13 2 2.694 0.742 0.458
#> 280 17 17 0 2.694 0.000 1
#> 281 16 16 0 2.694 0.000 1
#> 282 14 15 1 2.694 0.371 0.711
#> 283 15 16 1 2.694 0.371 0.711
#> 284 4 1 -3 2.694 -1.113 0.266
#> 285 17 18 1 2.694 0.371 0.711
#> 286 10 7 -3 2.694 -1.113 0.266
#> 287 12 15 3 2.694 1.113 0.266
#> 288 15 17 2 2.694 0.742 0.458
#> 289 17 15 -2 2.694 -0.742 0.458
#> 290 14 11 -3 2.694 -1.113 0.266
#> 291 15 12 -3 2.694 -1.113 0.266
#> 292 10 10 0 2.694 0.000 1
#> 293 0 2 2 2.694 0.742 0.458
#> 294 12 8 -4 2.694 -1.485 0.138
#> 295 4 7 3 2.694 1.113 0.266
#> 296 15 15 0 2.694 0.000 1
#> 297 18 17 -1 2.694 -0.371 0.711
#> 298 9 7 -2 2.694 -0.742 0.458
#> 299 18 12 -6 2.694 -2.227 0.026
#> 300 0 1 1 2.694 0.371 0.711
#> 301 4 11 7 2.694 2.598 0.009
#> 302 10 8 -2 2.694 -0.742 0.458
#> 303 5 2 -3 2.694 -1.113 0.266
#> 304 19 17 -2 2.694 -0.742 0.458
#> 305 11 6 -5 2.694 -1.856 0.063
#> 306 15 15 0 2.694 0.000 1
#> 307 10 12 2 2.694 0.742 0.458
#> 308 11 8 -3 2.694 -1.113 0.266
#> 309 10 7 -3 2.694 -1.113 0.266
#> 310 8 6 -2 2.694 -0.742 0.458
#> 311 14 15 1 2.694 0.371 0.711
#> 312 16 11 -5 2.694 -1.856 0.063
#> 313 6 4 -2 2.694 -0.742 0.458
#> 314 11 11 0 2.694 0.000 1
#> 315 7 7 0 2.694 0.000 1
#> 316 9 11 2 2.694 0.742 0.458
#> 317 7 11 4 2.694 1.485 0.138
#> 318 1 5 4 2.694 1.485 0.138
#> 319 10 9 -1 2.694 -0.371 0.711
#> 320 13 10 -3 2.694 -1.113 0.266
#> 321 13 10 -3 2.694 -1.113 0.266
#> 322 13 9 -4 2.694 -1.485 0.138
#> 323 1 2 1 2.694 0.371 0.711
#> 324 13 13 0 2.694 0.000 1
#> 325 13 13 0 2.694 0.000 1
#> 326 13 13 0 2.694 0.000 1
#> 327 7 6 -1 2.694 -0.371 0.711
#> 328 9 12 3 2.694 1.113 0.266
#> 329 13 13 0 2.694 0.000 1
#> 330 6 14 8 2.694 2.969 0.003
#> 331 12 14 2 2.694 0.742 0.458
#> 332 9 5 -4 2.694 -1.485 0.138
#> 333 13 12 -1 2.694 -0.371 0.711
#> 334 13 14 1 2.694 0.371 0.711
#> 335 9 11 2 2.694 0.742 0.458
#> 336 10 9 -1 2.694 -0.371 0.711
#> 337 12 13 1 2.694 0.371 0.711
#> 338 16 14 -2 2.694 -0.742 0.458
#> 339 6 10 4 2.694 1.485 0.138
#> 340 17 15 -2 2.694 -0.742 0.458
#> 341 12 14 2 2.694 0.742 0.458
#> 342 6 5 -1 2.694 -0.371 0.711
#> 343 5 9 4 2.694 1.485 0.138
#> 344 5 4 -1 2.694 -0.371 0.711
#> 345 6 9 3 2.694 1.113 0.266
#> 346 12 8 -4 2.694 -1.485 0.138
#> 347 12 13 1 2.694 0.371 0.711
#> 348 8 11 3 2.694 1.113 0.266
#> 349 5 6 1 2.694 0.371 0.711
#> 350 11 12 1 2.694 0.371 0.711
#> 351 9 7 -2 2.694 -0.742 0.458
#> 352 18 16 -2 2.694 -0.742 0.458
#> 353 9 11 2 2.694 0.742 0.458
#> 354 4 3 -1 2.694 -0.371 0.711
#> 355 12 17 5 2.694 1.856 0.063
#> 356 16 15 -1 2.694 -0.371 0.711
#> 357 9 13 4 2.694 1.485 0.138
#> 358 10 7 -3 2.694 -1.113 0.266
#> 359 1 3 2 2.694 0.742 0.458
#> 360 10 12 2 2.694 0.742 0.458
#> 361 5 5 0 2.694 0.000 1
#> 362 13 15 2 2.694 0.742 0.458
#> 363 9 12 3 2.694 1.113 0.266
#> 364 13 14 1 2.694 0.371 0.711
#> 365 9 5 -4 2.694 -1.485 0.138
#> 366 17 17 0 2.694 0.000 1
#> 367 4 2 -2 2.694 -0.742 0.458
#> 368 12 9 -3 2.694 -1.113 0.266
#> 369 3 10 7 2.694 2.598 0.009
#> 370 12 12 0 2.694 0.000 1
#> 371 14 18 4 2.694 1.485 0.138
#> 372 10 11 1 2.694 0.371 0.711
#> 373 7 9 2 2.694 0.742 0.458
#> 374 4 6 2 2.694 0.742 0.458
#> 375 10 5 -5 2.694 -1.856 0.063
#> 376 16 14 -2 2.694 -0.742 0.458
#> 377 15 15 0 2.694 0.000 1
#> 378 13 12 -1 2.694 -0.371 0.711
#> 379 0 3 3 2.694 1.113 0.266
#> 380 7 8 1 2.694 0.371 0.711
#> 381 6 7 1 2.694 0.371 0.711
#> 382 6 6 0 2.694 0.000 1
#> 383 6 8 2 2.694 0.742 0.458
#> 384 4 4 0 2.694 0.000 1
#> 385 3 4 1 2.694 0.371 0.711
#> 386 2 7 5 2.694 1.856 0.063
#> 387 9 9 0 2.694 0.000 1
#> 388 19 14 -5 2.694 -1.856 0.063
#> 389 3 6 3 2.694 1.113 0.266
#> 390 0 2 2 2.694 0.742 0.458
#> 391 15 14 -1 2.694 -0.371 0.711
#> 392 11 4 -7 2.694 -2.598 0.009
#> 393 5 6 1 2.694 0.371 0.711
#> 394 2 1 -1 2.694 -0.371 0.711
#> 395 7 13 6 2.694 2.227 0.026
#> 396 13 11 -2 2.694 -0.742 0.458
#> 397 15 14 -1 2.694 -0.371 0.711
#> 398 2 4 2 2.694 0.742 0.458
#> 399 13 6 -7 2.694 -2.598 0.009
#> 400 15 9 -6 2.694 -2.227 0.026
#> 401 7 8 1 2.694 0.371 0.711
#> 402 3 3 0 2.694 0.000 1
#> 403 9 12 3 2.694 1.113 0.266
#> 404 17 17 0 2.694 0.000 1
#> 405 1 4 3 2.694 1.113 0.266
#> 406 4 2 -2 2.694 -0.742 0.458
#> 407 7 10 3 2.694 1.113 0.266
#> 408 7 11 4 2.694 1.485 0.138
#> 409 12 12 0 2.694 0.000 1
#> 410 8 6 -2 2.694 -0.742 0.458
#> 411 8 4 -4 2.694 -1.485 0.138
#> 412 14 11 -3 2.694 -1.113 0.266
#> 413 5 3 -2 2.694 -0.742 0.458
#> 414 16 17 1 2.694 0.371 0.711
#> 415 11 15 4 2.694 1.485 0.138
#> 416 15 12 -3 2.694 -1.113 0.266
#> 417 14 15 1 2.694 0.371 0.711
#> 418 5 6 1 2.694 0.371 0.711
#> 419 5 10 5 2.694 1.856 0.063
#> 420 10 13 3 2.694 1.113 0.266
#> 421 3 2 -1 2.694 -0.371 0.711
#> 422 17 17 0 2.694 0.000 1
#> 423 11 11 0 2.694 0.000 1
#> 424 14 13 -1 2.694 -0.371 0.711
#> 425 16 9 -7 2.694 -2.598 0.009
#> 426 15 16 1 2.694 0.371 0.711
#> 427 11 7 -4 2.694 -1.485 0.138
#> 428 8 11 3 2.694 1.113 0.266
#> 429 13 13 0 2.694 0.000 1
#> 430 10 10 0 2.694 0.000 1
#> 431 15 14 -1 2.694 -0.371 0.711
#> 432 1 4 3 2.694 1.113 0.266
#> 433 3 3 0 2.694 0.000 1
#> 434 11 15 4 2.694 1.485 0.138
#> 435 3 4 1 2.694 0.371 0.711
#> 436 6 11 5 2.694 1.856 0.063
#> 437 2 0 -2 2.694 -0.742 0.458
#> 438 13 14 1 2.694 0.371 0.711
#> 439 18 14 -4 2.694 -1.485 0.138
#> 440 6 13 7 2.694 2.598 0.009
#> 441 14 12 -2 2.694 -0.742 0.458
#> 442 4 5 1 2.694 0.371 0.711
#> 443 10 9 -1 2.694 -0.371 0.711
#> 444 18 18 0 2.694 0.000 1
#> 445 17 16 -1 2.694 -0.371 0.711
#> 446 16 17 1 2.694 0.371 0.711
#> 447 0 0 0 2.694 0.000 1
#> 448 12 10 -2 2.694 -0.742 0.458
#> 449 4 7 3 2.694 1.113 0.266
#> 450 1 4 3 2.694 1.113 0.266
#> 451 19 18 -1 2.694 -0.371 0.711
#> 452 8 5 -3 2.694 -1.113 0.266
#> 453 8 11 3 2.694 1.113 0.266
#> 454 5 9 4 2.694 1.485 0.138
#> 455 18 17 -1 2.694 -0.371 0.711
#> 456 12 11 -1 2.694 -0.371 0.711
#> 457 5 9 4 2.694 1.485 0.138
#> 458 2 5 3 2.694 1.113 0.266
#> 459 1 2 1 2.694 0.371 0.711
#> 460 19 18 -1 2.694 -0.371 0.711
#> 461 15 17 2 2.694 0.742 0.458
#> 462 17 13 -4 2.694 -1.485 0.138
#> 463 13 15 2 2.694 0.742 0.458
#> 464 14 14 0 2.694 0.000 1
#> 465 6 9 3 2.694 1.113 0.266
#> 466 9 5 -4 2.694 -1.485 0.138
#> 467 16 15 -1 2.694 -0.371 0.711
#> 468 3 2 -1 2.694 -0.371 0.711
#> 469 1 7 6 2.694 2.227 0.026
#> 470 13 10 -3 2.694 -1.113 0.266
#> 471 5 4 -1 2.694 -0.371 0.711
#> 472 6 7 1 2.694 0.371 0.711
#> 473 20 19 -1 2.694 -0.371 0.711
#> 474 7 9 2 2.694 0.742 0.458
#> 475 1 1 0 2.694 0.000 1
#> 476 15 13 -2 2.694 -0.742 0.458
#> 477 16 11 -5 2.694 -1.856 0.063
#> 478 16 12 -4 2.694 -1.485 0.138
#> 479 11 10 -1 2.694 -0.371 0.711
#> 480 15 16 1 2.694 0.371 0.711
#> 481 7 8 1 2.694 0.371 0.711
#> 482 15 12 -3 2.694 -1.113 0.266
#> 483 15 16 1 2.694 0.371 0.711
#> 484 12 11 -1 2.694 -0.371 0.711
#> 485 12 10 -2 2.694 -0.742 0.458
#> 486 5 8 3 2.694 1.113 0.266
#> 487 8 12 4 2.694 1.485 0.138
#> 488 11 13 2 2.694 0.742 0.458
#> 489 16 17 1 2.694 0.371 0.711
#> 490 7 8 1 2.694 0.371 0.711
#> 491 19 18 -1 2.694 -0.371 0.711
#> 492 4 5 1 2.694 0.371 0.711
#> 493 19 16 -3 2.694 -1.113 0.266
#> 494 8 9 1 2.694 0.371 0.711
#> 495 10 15 5 2.694 1.856 0.063
#> 496 6 7 1 2.694 0.371 0.711
#> 497 11 8 -3 2.694 -1.113 0.266
#> 498 3 9 6 2.694 2.227 0.026
#> 499 8 8 0 2.694 0.000 1
#> 500 7 11 4 2.694 1.485 0.138
#> 501 13 16 3 2.694 1.113 0.266
#> 502 11 10 -1 2.694 -0.371 0.711
#> 503 0 1 1 2.694 0.371 0.711
#> 504 4 5 1 2.694 0.371 0.711
#> 505 4 6 2 2.694 0.742 0.458
#> 506 12 10 -2 2.694 -0.742 0.458
#> 507 18 16 -2 2.694 -0.742 0.458
#> 508 13 14 1 2.694 0.371 0.711
#> 509 5 7 2 2.694 0.742 0.458
#> 510 8 10 2 2.694 0.742 0.458
#> 511 6 10 4 2.694 1.485 0.138
#> 512 7 9 2 2.694 0.742 0.458
#> 513 5 5 0 2.694 0.000 1
#> 514 5 10 5 2.694 1.856 0.063
#> 515 9 11 2 2.694 0.742 0.458
#> 516 17 17 0 2.694 0.000 1
#> 517 14 13 -1 2.694 -0.371 0.711
#> 518 8 15 7 2.694 2.598 0.009
#> 519 14 14 0 2.694 0.000 1
#> 520 13 8 -5 2.694 -1.856 0.063
#> 521 14 12 -2 2.694 -0.742 0.458
#> 522 6 2 -4 2.694 -1.485 0.138
#> 523 17 14 -3 2.694 -1.113 0.266
#> 524 13 13 0 2.694 0.000 1
#> 525 14 14 0 2.694 0.000 1
#> 526 16 12 -4 2.694 -1.485 0.138
#> 527 12 10 -2 2.694 -0.742 0.458
#> 528 15 16 1 2.694 0.371 0.711
#> 529 13 10 -3 2.694 -1.113 0.266
#> 530 9 10 1 2.694 0.371 0.711
#> 531 12 7 -5 2.694 -1.856 0.063
#> 532 20 20 0 2.694 0.000 1
#> 533 17 12 -5 2.694 -1.856 0.063
#> 534 6 8 2 2.694 0.742 0.458
#> 535 19 18 -1 2.694 -0.371 0.711
#> 536 12 12 0 2.694 0.000 1
#> 537 10 7 -3 2.694 -1.113 0.266
#> 538 6 4 -2 2.694 -0.742 0.458
#> 539 8 8 0 2.694 0.000 1
#> 540 10 12 2 2.694 0.742 0.458
#> 541 4 7 3 2.694 1.113 0.266
#> 542 2 2 0 2.694 0.000 1
#> 543 6 5 -1 2.694 -0.371 0.711
#> 544 12 10 -2 2.694 -0.742 0.458
#> 545 4 5 1 2.694 0.371 0.711
#> 546 11 10 -1 2.694 -0.371 0.711
#> 547 14 12 -2 2.694 -0.742 0.458
#> 548 13 15 2 2.694 0.742 0.458
#> 549 12 9 -3 2.694 -1.113 0.266
#> 550 11 11 0 2.694 0.000 1
#> 551 8 2 -6 2.694 -2.227 0.026
#> 552 14 15 1 2.694 0.371 0.711
#> 553 11 14 3 2.694 1.113 0.266
#> 554 13 12 -1 2.694 -0.371 0.711
#> 555 2 3 1 2.694 0.371 0.711
#> 556 9 13 4 2.694 1.485 0.138
#> 557 10 11 1 2.694 0.371 0.711
#> 558 8 12 4 2.694 1.485 0.138
#> 559 11 12 1 2.694 0.371 0.711
#> 560 19 18 -1 2.694 -0.371 0.711
#> 561 12 12 0 2.694 0.000 1
#> 562 12 8 -4 2.694 -1.485 0.138
#> 563 3 6 3 2.694 1.113 0.266
#> 564 4 0 -4 2.694 -1.485 0.138
#> 565 14 14 0 2.694 0.000 1
#> 566 3 4 1 2.694 0.371 0.711
#> 567 18 16 -2 2.694 -0.742 0.458
#> 568 3 2 -1 2.694 -0.371 0.711
#> 569 17 19 2 2.694 0.742 0.458
#> 570 10 8 -2 2.694 -0.742 0.458
#> 571 16 13 -3 2.694 -1.113 0.266
#> 572 8 8 0 2.694 0.000 1
#> 573 15 17 2 2.694 0.742 0.458
#> 574 7 12 5 2.694 1.856 0.063
#> 575 6 2 -4 2.694 -1.485 0.138
#> 576 11 14 3 2.694 1.113 0.266
#> 577 13 12 -1 2.694 -0.371 0.711
#> 578 17 14 -3 2.694 -1.113 0.266
#> 579 5 9 4 2.694 1.485 0.138
#> 580 12 17 5 2.694 1.856 0.063
#> 581 11 10 -1 2.694 -0.371 0.711
#> 582 6 12 6 2.694 2.227 0.026
#> 583 11 13 2 2.694 0.742 0.458
#> 584 16 18 2 2.694 0.742 0.458
#> 585 8 6 -2 2.694 -0.742 0.458
#> 586 7 9 2 2.694 0.742 0.458
#> 587 12 11 -1 2.694 -0.371 0.711
#> 588 9 7 -2 2.694 -0.742 0.458
#> 589 9 6 -3 2.694 -1.113 0.266
#> 590 14 13 -1 2.694 -0.371 0.711
#> 591 15 15 0 2.694 0.000 1
#> 592 19 15 -4 2.694 -1.485 0.138
#> 593 6 7 1 2.694 0.371 0.711
#> 594 4 3 -1 2.694 -0.371 0.711
#> 595 4 6 2 2.694 0.742 0.458
#> 596 4 3 -1 2.694 -0.371 0.711
#> 597 4 4 0 2.694 0.000 1
#> 598 10 6 -4 2.694 -1.485 0.138
#> 599 8 14 6 2.694 2.227 0.026
#> 600 9 12 3 2.694 1.113 0.266
#> 601 10 12 2 2.694 0.742 0.458
#> 602 12 9 -3 2.694 -1.113 0.266
#> 603 13 9 -4 2.694 -1.485 0.138
#> 604 11 11 0 2.694 0.000 1
#> 605 2 4 2 2.694 0.742 0.458
#> 606 16 14 -2 2.694 -0.742 0.458
#> 607 2 1 -1 2.694 -0.371 0.711
#> 608 3 2 -1 2.694 -0.371 0.711
#> 609 6 4 -2 2.694 -0.742 0.458
#> 610 15 11 -4 2.694 -1.485 0.138
#> 611 7 6 -1 2.694 -0.371 0.711
#> 612 14 18 4 2.694 1.485 0.138
#> 613 7 14 7 2.694 2.598 0.009
#> 614 18 14 -4 2.694 -1.485 0.138
#> 615 9 6 -3 2.694 -1.113 0.266
#> 616 11 11 0 2.694 0.000 1
#> 617 6 2 -4 2.694 -1.485 0.138
#> 618 10 7 -3 2.694 -1.113 0.266
#> 619 3 2 -1 2.694 -0.371 0.711
#> 620 8 4 -4 2.694 -1.485 0.138
#> 621 8 10 2 2.694 0.742 0.458
#> 622 16 16 0 2.694 0.000 1
#> 623 4 2 -2 2.694 -0.742 0.458
#> 624 13 15 2 2.694 0.742 0.458
#> 625 11 11 0 2.694 0.000 1
#> 626 14 13 -1 2.694 -0.371 0.711
#> 627 4 8 4 2.694 1.485 0.138
#> 628 6 8 2 2.694 0.742 0.458
#> 629 15 9 -6 2.694 -2.227 0.026
#> 630 2 3 1 2.694 0.371 0.711
#> 631 2 3 1 2.694 0.371 0.711
#> 632 8 6 -2 2.694 -0.742 0.458
#> 633 8 4 -4 2.694 -1.485 0.138
#> 634 12 18 6 2.694 2.227 0.026
#> 635 15 15 0 2.694 0.000 1
#> 636 10 10 0 2.694 0.000 1
#> 637 3 3 0 2.694 0.000 1
#> 638 14 15 1 2.694 0.371 0.711
#> 639 9 6 -3 2.694 -1.113 0.266
#> 640 2 5 3 2.694 1.113 0.266
#> 641 14 17 3 2.694 1.113 0.266
#> 642 4 2 -2 2.694 -0.742 0.458
#> 643 12 13 1 2.694 0.371 0.711
#> 644 10 7 -3 2.694 -1.113 0.266
#> 645 3 4 1 2.694 0.371 0.711
#> 646 4 2 -2 2.694 -0.742 0.458
#> 647 2 6 4 2.694 1.485 0.138
#> 648 11 8 -3 2.694 -1.113 0.266
#> 649 10 10 0 2.694 0.000 1
#> 650 17 17 0 2.694 0.000 1
#> 651 8 10 2 2.694 0.742 0.458
#> 652 8 9 1 2.694 0.371 0.711
#> 653 17 17 0 2.694 0.000 1
#> 654 15 13 -2 2.694 -0.742 0.458
#> 655 14 19 5 2.694 1.856 0.063
#> 656 10 14 4 2.694 1.485 0.138
#> 657 12 13 1 2.694 0.371 0.711
#> 658 7 12 5 2.694 1.856 0.063
#> 659 11 12 1 2.694 0.371 0.711
#> 660 13 10 -3 2.694 -1.113 0.266
#> 661 7 7 0 2.694 0.000 1
#> 662 8 6 -2 2.694 -0.742 0.458
#> 663 7 5 -2 2.694 -0.742 0.458
#> 664 14 10 -4 2.694 -1.485 0.138
#> 665 17 19 2 2.694 0.742 0.458
#> 666 9 6 -3 2.694 -1.113 0.266
#> 667 3 3 0 2.694 0.000 1
#> 668 15 11 -4 2.694 -1.485 0.138
#> 669 7 8 1 2.694 0.371 0.711
#> 670 12 12 0 2.694 0.000 1
#> 671 13 13 0 2.694 0.000 1
#> 672 16 20 4 2.694 1.485 0.138
#> 673 13 9 -4 2.694 -1.485 0.138
#> 674 14 16 2 2.694 0.742 0.458
#> 675 7 2 -5 2.694 -1.856 0.063
#> 676 10 6 -4 2.694 -1.485 0.138
#> 677 10 12 2 2.694 0.742 0.458
#> 678 8 9 1 2.694 0.371 0.711
#> 679 4 7 3 2.694 1.113 0.266
#> 680 2 4 2 2.694 0.742 0.458
#> 681 13 10 -3 2.694 -1.113 0.266
#> 682 5 12 7 2.694 2.598 0.009
#> 683 5 6 1 2.694 0.371 0.711
#> 684 10 7 -3 2.694 -1.113 0.266
#> 685 13 12 -1 2.694 -0.371 0.711
#> 686 17 19 2 2.694 0.742 0.458
#> 687 11 12 1 2.694 0.371 0.711
#> 688 4 10 6 2.694 2.227 0.026
#> 689 6 4 -2 2.694 -0.742 0.458
#> 690 3 5 2 2.694 0.742 0.458
#> 691 11 14 3 2.694 1.113 0.266
#> 692 7 2 -5 2.694 -1.856 0.063
#> 693 8 10 2 2.694 0.742 0.458
#> 694 13 11 -2 2.694 -0.742 0.458
#> 695 13 16 3 2.694 1.113 0.266
#> 696 16 15 -1 2.694 -0.371 0.711
#> 697 16 12 -4 2.694 -1.485 0.138
#> 698 3 3 0 2.694 0.000 1
#> 699 12 15 3 2.694 1.113 0.266
#> 700 12 16 4 2.694 1.485 0.138
#> 701 3 3 0 2.694 0.000 1
#> 702 20 20 0 2.694 0.000 1
#> 703 7 10 3 2.694 1.113 0.266
#> 704 9 13 4 2.694 1.485 0.138
#> 705 5 7 2 2.694 0.742 0.458
#> 706 2 2 0 2.694 0.000 1
#> 707 13 16 3 2.694 1.113 0.266
#> 708 5 7 2 2.694 0.742 0.458
#> 709 8 7 -1 2.694 -0.371 0.711
#> 710 15 18 3 2.694 1.113 0.266
#> 711 3 1 -2 2.694 -0.742 0.458
#> 712 5 5 0 2.694 0.000 1
#> 713 5 3 -2 2.694 -0.742 0.458
#> 714 15 16 1 2.694 0.371 0.711
#> 715 12 10 -2 2.694 -0.742 0.458
#> 716 9 6 -3 2.694 -1.113 0.266
#> 717 5 2 -3 2.694 -1.113 0.266
#> 718 3 4 1 2.694 0.371 0.711
#> 719 2 6 4 2.694 1.485 0.138
#> 720 4 6 2 2.694 0.742 0.458
#> 721 10 12 2 2.694 0.742 0.458
#> 722 16 14 -2 2.694 -0.742 0.458
#> 723 3 2 -1 2.694 -0.371 0.711
#> 724 13 8 -5 2.694 -1.856 0.063
#> 725 17 15 -2 2.694 -0.742 0.458
#> 726 8 8 0 2.694 0.000 1
#> 727 8 10 2 2.694 0.742 0.458
#> 728 16 12 -4 2.694 -1.485 0.138
#> 729 11 15 4 2.694 1.485 0.138
#> 730 4 8 4 2.694 1.485 0.138
#> 731 5 6 1 2.694 0.371 0.711
#> 732 4 3 -1 2.694 -0.371 0.711
#> 733 8 6 -2 2.694 -0.742 0.458
#> 734 18 19 1 2.694 0.371 0.711
#> 735 10 11 1 2.694 0.371 0.711
#> 736 10 12 2 2.694 0.742 0.458
#> 737 18 20 2 2.694 0.742 0.458
#> 738 11 5 -6 2.694 -2.227 0.026
#> 739 17 17 0 2.694 0.000 1
#> 740 3 5 2 2.694 0.742 0.458
#> 741 15 15 0 2.694 0.000 1
#> 742 8 9 1 2.694 0.371 0.711
#> 743 9 5 -4 2.694 -1.485 0.138
#> 744 16 13 -3 2.694 -1.113 0.266
#> 745 14 13 -1 2.694 -0.371 0.711
#> 746 8 6 -2 2.694 -0.742 0.458
#> 747 5 9 4 2.694 1.485 0.138
#> 748 3 1 -2 2.694 -0.742 0.458
#> 749 6 7 1 2.694 0.371 0.711
#> 750 17 13 -4 2.694 -1.485 0.138
#> 751 15 15 0 2.694 0.000 1
#> 752 5 6 1 2.694 0.371 0.711
#> 753 9 11 2 2.694 0.742 0.458
#> 754 16 14 -2 2.694 -0.742 0.458
#> 755 12 12 0 2.694 0.000 1
#> 756 12 14 2 2.694 0.742 0.458
#> 757 14 9 -5 2.694 -1.856 0.063
#> 758 12 15 3 2.694 1.113 0.266
#> 759 1 0 -1 2.694 -0.371 0.711
#> 760 13 17 4 2.694 1.485 0.138
#> 761 17 19 2 2.694 0.742 0.458
#> 762 4 4 0 2.694 0.000 1
#> 763 10 7 -3 2.694 -1.113 0.266
#> 764 15 15 0 2.694 0.000 1
#> 765 10 12 2 2.694 0.742 0.458
#> 766 2 2 0 2.694 0.000 1
#> 767 16 16 0 2.694 0.000 1
#> 768 14 13 -1 2.694 -0.371 0.711
#> 769 15 15 0 2.694 0.000 1
#> 770 7 3 -4 2.694 -1.485 0.138
#> 771 7 3 -4 2.694 -1.485 0.138
#> 772 15 14 -1 2.694 -0.371 0.711
#> 773 11 12 1 2.694 0.371 0.711
#> 774 2 1 -1 2.694 -0.371 0.711
#> 775 3 7 4 2.694 1.485 0.138
#> 776 16 16 0 2.694 0.000 1
#> 777 14 9 -5 2.694 -1.856 0.063
#> 778 14 14 0 2.694 0.000 1
#> 779 14 13 -1 2.694 -0.371 0.711
#> 780 13 9 -4 2.694 -1.485 0.138
#> 781 13 11 -2 2.694 -0.742 0.458
#> 782 5 13 8 2.694 2.969 0.003
#> 783 13 12 -1 2.694 -0.371 0.711
#> 784 8 7 -1 2.694 -0.371 0.711
#> 785 17 16 -1 2.694 -0.371 0.711
#> 786 10 11 1 2.694 0.371 0.711
#> 787 12 10 -2 2.694 -0.742 0.458
#> 788 7 9 2 2.694 0.742 0.458
#> 789 2 2 0 2.694 0.000 1
#> 790 1 3 2 2.694 0.742 0.458
#> 791 3 8 5 2.694 1.856 0.063
#> 792 14 16 2 2.694 0.742 0.458
#> 793 4 7 3 2.694 1.113 0.266
#> 794 15 17 2 2.694 0.742 0.458
#> 795 15 13 -2 2.694 -0.742 0.458
#> 796 7 8 1 2.694 0.371 0.711
#> 797 6 4 -2 2.694 -0.742 0.458
#> 798 7 6 -1 2.694 -0.371 0.711
#> 799 11 8 -3 2.694 -1.113 0.266
#> 800 8 12 4 2.694 1.485 0.138
#> 801 6 3 -3 2.694 -1.113 0.266
#> 802 7 2 -5 2.694 -1.856 0.063
#> 803 9 9 0 2.694 0.000 1
#> 804 17 14 -3 2.694 -1.113 0.266
#> 805 6 7 1 2.694 0.371 0.711
#> 806 14 13 -1 2.694 -0.371 0.711
#> 807 6 13 7 2.694 2.598 0.009
#> 808 7 9 2 2.694 0.742 0.458
#> 809 17 17 0 2.694 0.000 1
#> 810 3 6 3 2.694 1.113 0.266
#> 811 15 18 3 2.694 1.113 0.266
#> 812 10 10 0 2.694 0.000 1
#> 813 7 2 -5 2.694 -1.856 0.063
#> 814 13 14 1 2.694 0.371 0.711
#> 815 8 10 2 2.694 0.742 0.458
#> 816 7 7 0 2.694 0.000 1
#> 817 15 5 -10 2.694 -3.712 0
#> 818 11 11 0 2.694 0.000 1
#> 819 8 14 6 2.694 2.227 0.026
#> 820 7 5 -2 2.694 -0.742 0.458
#> 821 12 12 0 2.694 0.000 1
#> 822 10 13 3 2.694 1.113 0.266
#> 823 3 3 0 2.694 0.000 1
#> 824 17 18 1 2.694 0.371 0.711
#> 825 7 6 -1 2.694 -0.371 0.711
#> 826 5 7 2 2.694 0.742 0.458
#> 827 15 14 -1 2.694 -0.371 0.711
#> 828 3 7 4 2.694 1.485 0.138
#> 829 4 3 -1 2.694 -0.371 0.711
#> 830 20 17 -3 2.694 -1.113 0.266
#> 831 8 5 -3 2.694 -1.113 0.266
#> 832 13 18 5 2.694 1.856 0.063
#> 833 15 15 0 2.694 0.000 1
#> 834 16 17 1 2.694 0.371 0.711
#> 835 6 6 0 2.694 0.000 1
#> 836 16 16 0 2.694 0.000 1
#> 837 9 9 0 2.694 0.000 1
#> 838 10 16 6 2.694 2.227 0.026
#> 839 10 11 1 2.694 0.371 0.711
#> 840 16 17 1 2.694 0.371 0.711
#> 841 15 15 0 2.694 0.000 1
#> 842 13 13 0 2.694 0.000 1
#> 843 15 16 1 2.694 0.371 0.711
#> 844 10 7 -3 2.694 -1.113 0.266
#> 845 12 9 -3 2.694 -1.113 0.266
#> 846 12 12 0 2.694 0.000 1
#> 847 8 7 -1 2.694 -0.371 0.711
#> 848 7 3 -4 2.694 -1.485 0.138
#> 849 5 5 0 2.694 0.000 1
#> 850 19 16 -3 2.694 -1.113 0.266
#> 851 15 15 0 2.694 0.000 1
#> 852 13 8 -5 2.694 -1.856 0.063
#> 853 9 10 1 2.694 0.371 0.711
#> 854 8 8 0 2.694 0.000 1
#> 855 9 9 0 2.694 0.000 1
#> 856 12 13 1 2.694 0.371 0.711
#> 857 10 7 -3 2.694 -1.113 0.266
#> 858 13 10 -3 2.694 -1.113 0.266
#> 859 10 9 -1 2.694 -0.371 0.711
#> 860 5 8 3 2.694 1.113 0.266
#> 861 5 3 -2 2.694 -0.742 0.458
#> 862 13 14 1 2.694 0.371 0.711
#> 863 3 6 3 2.694 1.113 0.266
#> 864 8 4 -4 2.694 -1.485 0.138
#> 865 10 13 3 2.694 1.113 0.266
#> 866 12 12 0 2.694 0.000 1
#> 867 9 10 1 2.694 0.371 0.711
#> 868 11 13 2 2.694 0.742 0.458
#> 869 10 7 -3 2.694 -1.113 0.266
#> 870 13 13 0 2.694 0.000 1
#> 871 14 13 -1 2.694 -0.371 0.711
#> 872 8 10 2 2.694 0.742 0.458
#> 873 1 1 0 2.694 0.000 1
#> 874 7 13 6 2.694 2.227 0.026
#> 875 14 16 2 2.694 0.742 0.458
#> 876 9 8 -1 2.694 -0.371 0.711
#> 877 16 16 0 2.694 0.000 1
#> 878 14 15 1 2.694 0.371 0.711
#> 879 8 10 2 2.694 0.742 0.458
#> 880 6 2 -4 2.694 -1.485 0.138
#> 881 5 2 -3 2.694 -1.113 0.266
#> 882 6 10 4 2.694 1.485 0.138
#> 883 11 11 0 2.694 0.000 1
#> 884 6 5 -1 2.694 -0.371 0.711
#> 885 14 14 0 2.694 0.000 1
#> 886 3 7 4 2.694 1.485 0.138
#> 887 3 9 6 2.694 2.227 0.026
#> 888 10 7 -3 2.694 -1.113 0.266
#> 889 2 6 4 2.694 1.485 0.138
#> 890 15 11 -4 2.694 -1.485 0.138
#> 891 10 6 -4 2.694 -1.485 0.138
#> 892 10 10 0 2.694 0.000 1
#> 893 17 16 -1 2.694 -0.371 0.711
#> 894 11 12 1 2.694 0.371 0.711
#> 895 9 11 2 2.694 0.742 0.458
#> 896 15 13 -2 2.694 -0.742 0.458
#> 897 17 16 -1 2.694 -0.371 0.711
#> 898 7 9 2 2.694 0.742 0.458
#> 899 10 8 -2 2.694 -0.742 0.458
#> 900 6 5 -1 2.694 -0.371 0.711
#> 901 7 6 -1 2.694 -0.371 0.711
#> 902 16 19 3 2.694 1.113 0.266
#> 903 16 19 3 2.694 1.113 0.266
#> 904 12 9 -3 2.694 -1.113 0.266
#> 905 6 7 1 2.694 0.371 0.711
#> 906 19 20 1 2.694 0.371 0.711
#> 907 15 11 -4 2.694 -1.485 0.138
#> 908 10 5 -5 2.694 -1.856 0.063
#> 909 2 0 -2 2.694 -0.742 0.458
#> 910 18 10 -8 2.694 -2.969 0.003
#> 911 2 0 -2 2.694 -0.742 0.458
#> 912 20 17 -3 2.694 -1.113 0.266
#> 913 4 2 -2 2.694 -0.742 0.458
#> 914 16 17 1 2.694 0.371 0.711
#> 915 14 15 1 2.694 0.371 0.711
#> 916 18 13 -5 2.694 -1.856 0.063
#> 917 16 17 1 2.694 0.371 0.711
#> 918 15 18 3 2.694 1.113 0.266
#> 919 13 10 -3 2.694 -1.113 0.266
#> 920 11 8 -3 2.694 -1.113 0.266
#> 921 4 2 -2 2.694 -0.742 0.458
#> 922 6 10 4 2.694 1.485 0.138
#> 923 12 11 -1 2.694 -0.371 0.711
#> 924 18 18 0 2.694 0.000 1
#> 925 5 5 0 2.694 0.000 1
#> 926 19 19 0 2.694 0.000 1
#> 927 7 5 -2 2.694 -0.742 0.458
#> 928 9 3 -6 2.694 -2.227 0.026
#> 929 15 19 4 2.694 1.485 0.138
#> 930 15 9 -6 2.694 -2.227 0.026
#> 931 11 11 0 2.694 0.000 1
#> 932 12 10 -2 2.694 -0.742 0.458
#> 933 12 13 1 2.694 0.371 0.711
#> 934 9 6 -3 2.694 -1.113 0.266
#> 935 14 14 0 2.694 0.000 1
#> 936 6 7 1 2.694 0.371 0.711
#> 937 6 6 0 2.694 0.000 1
#> 938 8 10 2 2.694 0.742 0.458
#> 939 3 2 -1 2.694 -0.371 0.711
#> 940 11 10 -1 2.694 -0.371 0.711
#> 941 12 15 3 2.694 1.113 0.266
#> 942 13 14 1 2.694 0.371 0.711
#> 943 12 8 -4 2.694 -1.485 0.138
#> 944 15 13 -2 2.694 -0.742 0.458
#> 945 11 12 1 2.694 0.371 0.711
#> 946 11 11 0 2.694 0.000 1
#> 947 11 10 -1 2.694 -0.371 0.711
#> 948 10 13 3 2.694 1.113 0.266
#> 949 1 2 1 2.694 0.371 0.711
#> 950 7 12 5 2.694 1.856 0.063
#> 951 8 6 -2 2.694 -0.742 0.458
#> 952 15 12 -3 2.694 -1.113 0.266
#> 953 7 4 -3 2.694 -1.113 0.266
#> 954 2 6 4 2.694 1.485 0.138
#> 955 6 5 -1 2.694 -0.371 0.711
#> 956 3 3 0 2.694 0.000 1
#> 957 5 5 0 2.694 0.000 1
#> 958 6 6 0 2.694 0.000 1
#> 959 13 17 4 2.694 1.485 0.138
#> 960 6 7 1 2.694 0.371 0.711
#> 961 3 2 -1 2.694 -0.371 0.711
#> 962 12 11 -1 2.694 -0.371 0.711
#> 963 6 4 -2 2.694 -0.742 0.458
#> 964 17 12 -5 2.694 -1.856 0.063
#> 965 5 7 2 2.694 0.742 0.458
#> 966 13 16 3 2.694 1.113 0.266
#> 967 15 16 1 2.694 0.371 0.711
#> 968 12 9 -3 2.694 -1.113 0.266
#> 969 15 13 -2 2.694 -0.742 0.458
#> 970 14 16 2 2.694 0.742 0.458
#> 971 6 7 1 2.694 0.371 0.711
#> 972 16 16 0 2.694 0.000 1
#> 973 3 1 -2 2.694 -0.742 0.458
#> 974 5 5 0 2.694 0.000 1
#> 975 7 3 -4 2.694 -1.485 0.138
#> 976 13 13 0 2.694 0.000 1
#> 977 10 12 2 2.694 0.742 0.458
#> 978 2 4 2 2.694 0.742 0.458
#> 979 2 9 7 2.694 2.598 0.009
#> 980 10 9 -1 2.694 -0.371 0.711
#> 981 4 1 -3 2.694 -1.113 0.266
#> 982 7 4 -3 2.694 -1.113 0.266
#> 983 17 12 -5 2.694 -1.856 0.063
#> 984 18 16 -2 2.694 -0.742 0.458
#> 985 16 11 -5 2.694 -1.856 0.063
#> 986 5 3 -2 2.694 -0.742 0.458
#> 987 13 14 1 2.694 0.371 0.711
#> 988 11 8 -3 2.694 -1.113 0.266
#> 989 2 12 10 2.694 3.712 0
#> 990 9 11 2 2.694 0.742 0.458
#> 991 11 6 -5 2.694 -1.856 0.063
#> 992 11 10 -1 2.694 -0.371 0.711
#> 993 8 6 -2 2.694 -0.742 0.458
#> 994 1 4 3 2.694 1.113 0.266
#> 995 10 7 -3 2.694 -1.113 0.266
#> 996 11 5 -6 2.694 -2.227 0.026
#> 997 7 6 -1 2.694 -0.371 0.711
#> 998 10 12 2 2.694 0.742 0.458
#> 999 11 7 -4 2.694 -1.485 0.138
#> 1000 1 2 1 2.694 0.371 0.711
######
# 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 1.1552393 0.0000000 -0.63265649
#> 2 0.7725387 0.0000000 -0.23498495
#> 3 1.1911807 0.0000000 -0.23365145
#> 4 1.5201541 0.0000000 -0.09858223
#> 5 1.1752077 0.0000000 0.83519448
#> 6 1.0858223 0.0000000 -0.43051228
#> 7 1.6628731 0.0000000 0.41443651
#> 8 1.1012075 0.0000000 1.41245283
#> 9 1.0354140 0.0000000 0.84976955
#> 10 1.3580607 0.0000000 0.17070288
#> 11 0.9164153 0.0000000 -0.24230045
#> 12 1.1904205 0.0000000 -1.66708924
#> 13 1.5486689 0.0000000 -1.74009514
#> 14 1.1839185 0.0000000 0.84319987
#> 15 1.2910372 0.0000000 -1.96094872
#> 16 1.3247273 0.0000000 -0.33889244
#> 17 1.3673442 0.0000000 1.84475886
#> 18 1.2868859 0.0000000 0.51631728
#> 19 0.9999844 0.0000000 -0.73065644
#> 20 1.1269914 0.0000000 1.68359583
#> 21 0.0000000 1.1552393 -0.63265649
#> 22 0.0000000 0.7725387 -0.23498495
#> 23 0.0000000 1.1911807 -0.23365145
#> 24 0.0000000 1.5201541 -0.09858223
#> 25 0.0000000 1.1752077 0.83519448
#> 26 0.0000000 1.0858223 -0.43051228
#> 27 0.0000000 1.6628731 0.41443651
#> 28 0.0000000 1.1012075 1.41245283
#> 29 0.0000000 1.0354140 0.84976955
#> 30 0.0000000 1.3580607 0.17070288
#> 31 0.0000000 0.9164153 -0.24230045
#> 32 0.0000000 1.1904205 -1.66708924
#> 33 0.0000000 1.5486689 -1.74009514
#> 34 0.0000000 1.1839185 0.84319987
#> 35 0.0000000 1.2910372 -1.96094872
#> 36 0.0000000 1.3247273 -0.33889244
#> 37 0.0000000 1.3673442 1.84475886
#> 38 0.0000000 1.2868859 0.51631728
#> 39 0.0000000 0.9999844 -0.73065644
#> 40 0.0000000 1.1269914 1.68359583
# 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: -11031.103, Max-Change: 0.45245
Iteration: 2, Log-Lik: -10854.751, Max-Change: 0.17901
Iteration: 3, Log-Lik: -10831.439, Max-Change: 0.08252
Iteration: 4, Log-Lik: -10822.842, Max-Change: 0.04738
Iteration: 5, Log-Lik: -10817.535, Max-Change: 0.04139
Iteration: 6, Log-Lik: -10813.741, Max-Change: 0.03736
Iteration: 7, Log-Lik: -10805.844, Max-Change: 0.09350
Iteration: 8, Log-Lik: -10803.362, Max-Change: 0.03709
Iteration: 9, Log-Lik: -10802.625, Max-Change: 0.01935
Iteration: 10, Log-Lik: -10802.053, Max-Change: 0.01479
Iteration: 11, Log-Lik: -10801.802, Max-Change: 0.00968
Iteration: 12, Log-Lik: -10801.622, Max-Change: 0.00773
Iteration: 13, Log-Lik: -10801.210, Max-Change: 0.01606
Iteration: 14, Log-Lik: -10801.095, Max-Change: 0.00730
Iteration: 15, Log-Lik: -10801.053, Max-Change: 0.00406
Iteration: 16, Log-Lik: -10801.011, Max-Change: 0.00345
Iteration: 17, Log-Lik: -10800.996, Max-Change: 0.00217
Iteration: 18, Log-Lik: -10800.985, Max-Change: 0.00200
Iteration: 19, Log-Lik: -10800.959, Max-Change: 0.00339
Iteration: 20, Log-Lik: -10800.953, Max-Change: 0.00158
Iteration: 21, Log-Lik: -10800.950, Max-Change: 0.00088
Iteration: 22, Log-Lik: -10800.947, Max-Change: 0.00081
Iteration: 23, Log-Lik: -10800.946, Max-Change: 0.00055
Iteration: 24, Log-Lik: -10800.946, Max-Change: 0.00050
Iteration: 25, Log-Lik: -10800.944, Max-Change: 0.00066
Iteration: 26, Log-Lik: -10800.944, Max-Change: 0.00032
Iteration: 27, Log-Lik: -10800.943, Max-Change: 0.00023
Iteration: 28, Log-Lik: -10800.943, Max-Change: 0.00019
Iteration: 29, Log-Lik: -10800.943, Max-Change: 0.00013
Iteration: 30, Log-Lik: -10800.943, Max-Change: 0.00012
Iteration: 31, Log-Lik: -10800.943, Max-Change: 0.00011
Iteration: 32, Log-Lik: -10800.943, Max-Change: 0.00005
#>
#> Calculating information matrix...
coef(mod, printSE=TRUE)
#> $Item_1
#> a1 a2 d logit(g) logit(u)
#> par 1.252 0 -0.639 -999 999
#> SE 0.117 NA 0.097 NA NA
#>
#> $Item_2
#> a1 a2 d logit(g) logit(u)
#> par 0.702 0 -0.268 -999 999
#> SE 0.084 NA 0.077 NA NA
#>
#> $Item_3
#> a1 a2 d logit(g) logit(u)
#> par 1.210 0 -0.210 -999 999
#> SE 0.112 NA 0.094 NA NA
#>
#> $Item_4
#> a1 a2 d logit(g) logit(u)
#> par 1.608 0 -0.178 -999 999
#> SE 0.140 NA 0.110 NA NA
#>
#> $Item_5
#> a1 a2 d logit(g) logit(u)
#> par 1.237 0 0.770 -999 999
#> SE 0.116 NA 0.103 NA NA
#>
#> $Item_6
#> a1 a2 d logit(g) logit(u)
#> par 1.296 0 -0.445 -999 999
#> SE 0.118 NA 0.097 NA NA
#>
#> $Item_7
#> a1 a2 d logit(g) logit(u)
#> par 1.856 0 0.377 -999 999
#> SE 0.161 NA 0.124 NA NA
#>
#> $Item_8
#> a1 a2 d logit(g) logit(u)
#> par 1.125 0 1.368 -999 999
#> SE 0.115 NA 0.113 NA NA
#>
#> $Item_9
#> a1 a2 d logit(g) logit(u)
#> par 0.961 0 0.717 -999 999
#> SE 0.099 NA 0.092 NA NA
#>
#> $Item_10
#> a1 a2 d logit(g) logit(u)
#> par 1.517 0 0.150 -999 999
#> SE 0.133 NA 0.107 NA NA
#>
#> $Item_11
#> a1 a2 d logit(g) logit(u)
#> par 0.855 0 -0.271 -999 999
#> SE 0.092 NA 0.081 NA NA
#>
#> $Item_12
#> a1 a2 d logit(g) logit(u)
#> par 1.056 0 -1.475 -999 999
#> SE 0.115 NA 0.104 NA NA
#>
#> $Item_13
#> a1 a2 d logit(g) logit(u)
#> par 1.745 0 -2.061 -999 999
#> SE 0.173 NA 0.157 NA NA
#>
#> $Item_14
#> a1 a2 d logit(g) logit(u)
#> par 1.333 0 0.860 -999 999
#> SE 0.123 NA 0.109 NA NA
#>
#> $Item_15
#> a1 a2 d logit(g) logit(u)
#> par 1.488 0 -2.028 -999 999
#> SE 0.153 NA 0.142 NA NA
#>
#> $Item_16
#> a1 a2 d logit(g) logit(u)
#> par 1.409 0 -0.359 -999 999
#> SE 0.125 NA 0.102 NA NA
#>
#> $Item_17
#> a1 a2 d logit(g) logit(u)
#> par 1.378 0 1.715 -999 999
#> SE 0.136 NA 0.135 NA NA
#>
#> $Item_18
#> a1 a2 d logit(g) logit(u)
#> par 1.202 0 0.321 -999 999
#> SE 0.111 NA 0.096 NA NA
#>
#> $Item_19
#> a1 a2 d logit(g) logit(u)
#> par 1.061 0 -0.807 -999 999
#> SE 0.106 NA 0.092 NA NA
#>
#> $Item_20
#> a1 a2 d logit(g) logit(u)
#> par 1.146 0 1.724 -999 999
#> SE 0.121 NA 0.126 NA NA
#>
#> $Item_21
#> a1 a2 d logit(g) logit(u)
#> par 0 1.252 -0.639 -999 999
#> SE NA 0.117 0.097 NA NA
#>
#> $Item_22
#> a1 a2 d logit(g) logit(u)
#> par 0 0.702 -0.268 -999 999
#> SE NA 0.084 0.077 NA NA
#>
#> $Item_23
#> a1 a2 d logit(g) logit(u)
#> par 0 1.210 -0.210 -999 999
#> SE NA 0.112 0.094 NA NA
#>
#> $Item_24
#> a1 a2 d logit(g) logit(u)
#> par 0 1.608 -0.178 -999 999
#> SE NA 0.140 0.110 NA NA
#>
#> $Item_25
#> a1 a2 d logit(g) logit(u)
#> par 0 1.237 0.770 -999 999
#> SE NA 0.116 0.103 NA NA
#>
#> $Item_26
#> a1 a2 d logit(g) logit(u)
#> par 0 1.296 -0.445 -999 999
#> SE NA 0.118 0.097 NA NA
#>
#> $Item_27
#> a1 a2 d logit(g) logit(u)
#> par 0 1.856 0.377 -999 999
#> SE NA 0.161 0.124 NA NA
#>
#> $Item_28
#> a1 a2 d logit(g) logit(u)
#> par 0 1.125 1.368 -999 999
#> SE NA 0.115 0.113 NA NA
#>
#> $Item_29
#> a1 a2 d logit(g) logit(u)
#> par 0 0.961 0.717 -999 999
#> SE NA 0.099 0.092 NA NA
#>
#> $Item_30
#> a1 a2 d logit(g) logit(u)
#> par 0 1.517 0.150 -999 999
#> SE NA 0.133 0.107 NA NA
#>
#> $Item_31
#> a1 a2 d logit(g) logit(u)
#> par 0 0.855 -0.271 -999 999
#> SE NA 0.092 0.081 NA NA
#>
#> $Item_32
#> a1 a2 d logit(g) logit(u)
#> par 0 1.056 -1.475 -999 999
#> SE NA 0.115 0.104 NA NA
#>
#> $Item_33
#> a1 a2 d logit(g) logit(u)
#> par 0 1.745 -2.061 -999 999
#> SE NA 0.173 0.157 NA NA
#>
#> $Item_34
#> a1 a2 d logit(g) logit(u)
#> par 0 1.333 0.860 -999 999
#> SE NA 0.123 0.109 NA NA
#>
#> $Item_35
#> a1 a2 d logit(g) logit(u)
#> par 0 1.488 -2.028 -999 999
#> SE NA 0.153 0.142 NA NA
#>
#> $Item_36
#> a1 a2 d logit(g) logit(u)
#> par 0 1.409 -0.359 -999 999
#> SE NA 0.125 0.102 NA NA
#>
#> $Item_37
#> a1 a2 d logit(g) logit(u)
#> par 0 1.378 1.715 -999 999
#> SE NA 0.136 0.135 NA NA
#>
#> $Item_38
#> a1 a2 d logit(g) logit(u)
#> par 0 1.202 0.321 -999 999
#> SE NA 0.111 0.096 NA NA
#>
#> $Item_39
#> a1 a2 d logit(g) logit(u)
#> par 0 1.061 -0.807 -999 999
#> SE NA 0.106 0.092 NA NA
#>
#> $Item_40
#> a1 a2 d logit(g) logit(u)
#> par 0 1.146 1.724 -999 999
#> SE NA 0.121 0.126 NA NA
#>
#> $GroupPars
#> MEAN_1 MEAN_2 COV_11 COV_21 COV_22
#> par 0 -0.519 1 0.691 0.971
#> SE NA 0.049 NA 0.047 0.096
#>
coef(mod, simplify=TRUE)
#> $items
#> a1 a2 d g u
#> Item_1 1.252 0.000 -0.639 0 1
#> Item_2 0.702 0.000 -0.268 0 1
#> Item_3 1.210 0.000 -0.210 0 1
#> Item_4 1.608 0.000 -0.178 0 1
#> Item_5 1.237 0.000 0.770 0 1
#> Item_6 1.296 0.000 -0.445 0 1
#> Item_7 1.856 0.000 0.377 0 1
#> Item_8 1.125 0.000 1.368 0 1
#> Item_9 0.961 0.000 0.717 0 1
#> Item_10 1.517 0.000 0.150 0 1
#> Item_11 0.855 0.000 -0.271 0 1
#> Item_12 1.056 0.000 -1.475 0 1
#> Item_13 1.745 0.000 -2.061 0 1
#> Item_14 1.333 0.000 0.860 0 1
#> Item_15 1.488 0.000 -2.028 0 1
#> Item_16 1.409 0.000 -0.359 0 1
#> Item_17 1.378 0.000 1.715 0 1
#> Item_18 1.202 0.000 0.321 0 1
#> Item_19 1.061 0.000 -0.807 0 1
#> Item_20 1.146 0.000 1.724 0 1
#> Item_21 0.000 1.252 -0.639 0 1
#> Item_22 0.000 0.702 -0.268 0 1
#> Item_23 0.000 1.210 -0.210 0 1
#> Item_24 0.000 1.608 -0.178 0 1
#> Item_25 0.000 1.237 0.770 0 1
#> Item_26 0.000 1.296 -0.445 0 1
#> Item_27 0.000 1.856 0.377 0 1
#> Item_28 0.000 1.125 1.368 0 1
#> Item_29 0.000 0.961 0.717 0 1
#> Item_30 0.000 1.517 0.150 0 1
#> Item_31 0.000 0.855 -0.271 0 1
#> Item_32 0.000 1.056 -1.475 0 1
#> Item_33 0.000 1.745 -2.061 0 1
#> Item_34 0.000 1.333 0.860 0 1
#> Item_35 0.000 1.488 -2.028 0 1
#> Item_36 0.000 1.409 -0.359 0 1
#> Item_37 0.000 1.378 1.715 0 1
#> Item_38 0.000 1.202 0.321 0 1
#> Item_39 0.000 1.061 -0.807 0 1
#> Item_40 0.000 1.146 1.724 0 1
#>
#> $means
#> thetapre thetapost
#> 0.000 -0.519
#>
#> $cov
#> thetapre thetapost
#> thetapre 1.000 0.691
#> thetapost 0.691 0.971
#>
summary(mod)
#> thetapre thetapost h2
#> Item_1 0.592 0.351
#> Item_2 0.381 0.145
#> Item_3 0.579 0.336
#> Item_4 0.687 0.472
#> Item_5 0.588 0.346
#> Item_6 0.606 0.367
#> Item_7 0.737 0.543
#> Item_8 0.551 0.304
#> Item_9 0.492 0.242
#> Item_10 0.665 0.443
#> Item_11 0.449 0.202
#> Item_12 0.527 0.278
#> Item_13 0.716 0.512
#> Item_14 0.617 0.380
#> Item_15 0.658 0.433
#> Item_16 0.638 0.407
#> Item_17 0.629 0.396
#> Item_18 0.577 0.333
#> Item_19 0.529 0.280
#> Item_20 0.558 0.312
#> Item_21 0.587 0.344
#> Item_22 0.377 0.142
#> Item_23 0.574 0.329
#> Item_24 0.682 0.465
#> Item_25 0.582 0.339
#> Item_26 0.600 0.360
#> Item_27 0.732 0.536
#> Item_28 0.546 0.298
#> Item_29 0.486 0.236
#> Item_30 0.660 0.435
#> Item_31 0.444 0.197
#> Item_32 0.522 0.272
#> Item_33 0.711 0.505
#> Item_34 0.611 0.374
#> Item_35 0.653 0.426
#> Item_36 0.632 0.400
#> Item_37 0.624 0.389
#> Item_38 0.571 0.326
#> Item_39 0.524 0.274
#> Item_40 0.553 0.306
#>
#> SE.thetapre SE.thetapost
#> Item_1 0.036
#> Item_2 0.039
#> Item_3 0.036
#> Item_4 0.032
#> Item_5 0.036
#> Item_6 0.035
#> Item_7 0.029
#> Item_8 0.039
#> Item_9 0.038
#> Item_10 0.033
#> Item_11 0.039
#> Item_12 0.041
#> Item_13 0.035
#> Item_14 0.035
#> Item_15 0.038
#> Item_16 0.034
#> Item_17 0.037
#> Item_18 0.036
#> Item_19 0.038
#> Item_20 0.041
#> Item_21 0.036
#> Item_22 0.039
#> Item_23 0.036
#> Item_24 0.032
#> Item_25 0.036
#> Item_26 0.035
#> Item_27 0.029
#> Item_28 0.039
#> Item_29 0.038
#> Item_30 0.033
#> Item_31 0.038
#> Item_32 0.041
#> Item_33 0.035
#> Item_34 0.035
#> Item_35 0.038
#> Item_36 0.034
#> Item_37 0.038
#> Item_38 0.036
#> Item_39 0.038
#> Item_40 0.041
#>
#> SS loadings: 7.081 6.954
#> Proportion Var: 0.177 0.174
#>
#> Factor correlations:
#>
#> thetapre thetapost
#> thetapre 1.000
#> thetapost 0.701 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 10 8
#> 2 12 15
#> 3 18 18
data.frame(pre=rowSums(change[,1:J]),
post=rowSums(change[,1:J + J]))
#> pre post
#> 1 12 5
#> 2 14 10
#> 3 19 17
RCI(mod, predat = nochange)
#> pre.score post.score converged diff SE z p
#> 1 -0.052 -0.483 TRUE -0.431 0.524 -0.822 0.411
#> 2 0.412 0.943 TRUE 0.531 0.542 0.978 0.328
#> 3 1.673 1.367 TRUE -0.306 0.641 -0.478 0.633
RCI(mod, predat = change)
#> pre.score post.score converged diff SE z p
#> 1 0.215 -1.063 TRUE -1.278 0.554 -2.305 0.021
#> 2 0.871 -0.080 TRUE -0.951 0.536 -1.776 0.076
#> 3 1.867 1.210 TRUE -0.657 0.651 -1.009 0.313
# }