Rasch_1
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hls2 <- read.csv("data_pre.csv", header = T)
str(hls2)
## 'data.frame': 748 obs. of 45 variables:
## $ X : int 1 2 3 4 5 6 7 8 9 10 ...
## $ 癤풹chieve_1: int 0 0 0 2 1 1 3 3 1 3 ...
## $ achieve_2 : int 2 3 2 2 2 1 2 1 0 2 ...
## $ achieve_3 : int 1 2 4 2 0 3 4 0 2 1 ...
## $ achieve_4 : int 0 2 1 0 0 1 2 0 2 1 ...
## $ achieve_5 : int 0 0 1 1 0 1 3 0 1 2 ...
## $ achieve_6 : int 3 2 1 2 2 1 2 0 2 1 ...
## $ self_1 : int 0 0 2 2 1 0 0 0 2 2 ...
## $ self_2 : int 2 4 0 0 2 1 0 0 4 1 ...
## $ self_3 : int 3 0 0 0 0 1 0 0 2 1 ...
## $ self_4 : int 2 4 3 0 2 2 4 0 2 1 ...
## $ self_5 : int 3 4 1 0 2 3 2 4 3 1 ...
## $ self_6 : int 2 3 0 2 0 0 0 0 1 0 ...
## $ self_7 : int 1 0 1 0 1 0 1 1 1 1 ...
## $ self_8 : int 0 0 3 0 2 3 1 1 3 2 ...
## $ curio_1 : int 0 0 1 0 0 0 0 0 4 0 ...
## $ curio_2 : int 0 0 1 0 0 1 0 0 0 0 ...
## $ curio_3 : int 1 0 3 0 0 2 0 4 4 0 ...
## $ curio_4 : int 1 0 1 0 0 0 0 4 0 1 ...
## $ curio_5 : int 1 0 0 4 1 1 0 1 0 1 ...
## $ curio_6 : int 0 0 0 4 2 2 0 0 0 1 ...
## $ curio_7 : int 1 0 0 0 0 0 0 0 0 1 ...
## $ curio_8 : int 2 0 1 2 1 3 0 4 0 4 ...
## $ curio_9 : int 1 0 0 2 0 0 0 0 0 1 ...
## $ curio_10 : int 0 0 0 4 2 0 0 4 0 0 ...
## $ curio_11 : int 0 0 0 0 0 0 0 0 0 1 ...
## $ info_1 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ info_2 : int 0 0 1 0 1 0 0 1 0 0 ...
## $ info_3 : int 0 0 1 0 0 0 0 0 0 1 ...
## $ info_4 : int 0 0 0 0 0 0 2 0 1 2 ...
## $ info_5 : int 0 0 0 0 0 0 0 1 0 0 ...
## $ info_6 : int 2 0 1 0 2 0 2 0 0 3 ...
## $ inter_d_1 : int 1 0 2 4 4 4 2 4 2 2 ...
## $ inter_d_2 : int 1 4 0 2 4 3 2 4 2 1 ...
## $ inter_d_3 : int 2 4 1 2 4 3 2 4 2 2 ...
## $ inter_d_4 : int 1 0 2 1 4 1 4 4 2 0 ...
## $ inter_d_5 : int 1 4 2 2 0 1 2 0 2 0 ...
## $ inter_d_6 : int 0 0 4 2 0 3 2 0 2 2 ...
## $ inter_d_7 : int 0 0 3 0 0 1 0 1 2 1 ...
## $ inter_d_8 : int 0 0 0 3 0 2 0 0 2 1 ...
## $ deci_1 : int 3 4 1 1 4 1 4 4 2 3 ...
## $ deci_2 : int 3 0 2 2 4 4 2 0 2 3 ...
## $ deci_3 : int 2 4 4 2 4 4 4 3 2 3 ...
## $ deci_4 : int 2 2 0 2 2 2 4 4 2 4 ...
## $ deci_5 : int 2 2 4 4 3 2 4 3 2 4 ...
hls2 <- hls2[2:45]
hls2[hls2 =="2"]<- NA
모델 피팅
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You can also embed plots, for example:
## ------------------------------------------------------------
## TAM 3.5-19 (2020-05-05 22:45:39)
## R version 4.0.2 (2020-06-22) x86_64, mingw32 | nodename=5-2박정 | login=user
##
## Date of Analysis: 2020-08-24 14:12:35
## Time difference of 5.238999 secs
## Computation time: 5.238999
##
## Multidimensional Item Response Model in TAM
##
## IRT Model: 1PL
## Call:
## tam.mml(resp = resp)
##
## ------------------------------------------------------------
## Number of iterations = 1000
## Numeric integration with 21 integration points
##
## Deviance = 47707.84
## Log likelihood = -23853.92
## Number of persons = 748
## Number of persons used = 746
## Number of items = 44
## Number of estimated parameters = 177
## Item threshold parameters = 176
## Item slope parameters = 0
## Regression parameters = 0
## Variance/covariance parameters = 1
##
## AIC = 48062 | penalty=354 | AIC=-2*LL + 2*p
## AIC3 = 48239 | penalty=531 | AIC3=-2*LL + 3*p
## BIC = 48879 | penalty=1170.81 | BIC=-2*LL + log(n)*p
## aBIC = 48316 | penalty=607.82 | aBIC=-2*LL + log((n-2)/24)*p (adjusted BIC)
## CAIC = 49056 | penalty=1347.81 | CAIC=-2*LL + [log(n)+1]*p (consistent AIC)
## AICc = 48173 | penalty=464.94 | AICc=-2*LL + 2*p + 2*p*(p+1)/(n-p-1) (bias corrected AIC)
## GHP = 1.07042 | GHP=( -LL + p ) / (#Persons * #Items) (Gilula-Haberman log penalty)
##
## ------------------------------------------------------------
## EAP Reliability
## [1] 0.889
## ------------------------------------------------------------
## Covariances and Variances
## [,1]
## [1,] 0.289
## ------------------------------------------------------------
## Correlations and Standard Deviations (in the diagonal)
## [,1]
## [1,] 0.538
## ------------------------------------------------------------
## Regression Coefficients
## [,1]
## [1,] 0
## ------------------------------------------------------------
## Item Parameters -A*Xsi
## item N M xsi.item AXsi_.Cat1 AXsi_.Cat2 AXsi_.Cat3 AXsi_.Cat4
## 1 癤풹chieve_1 567 3.171 -0.860 -1.589 4.672 -3.669 -3.438
## 2 achieve_2 416 2.856 -0.767 -2.752 3.555 -4.173 -3.068
## 3 achieve_3 510 2.733 -0.426 -1.267 5.256 -2.508 -1.704
## 4 achieve_4 495 2.360 -0.195 -1.012 5.379 -1.523 -0.781
## 5 achieve_5 506 3.057 -0.836 -2.066 4.257 -4.487 -3.345
## 6 achieve_6 445 2.849 -0.528 -1.845 4.311 -3.651 -2.114
## 7 self_1 475 2.665 -0.359 -1.398 5.167 -2.652 -1.435
## 8 self_2 534 2.787 -0.538 -1.510 5.015 -2.717 -2.152
## 9 self_3 484 2.760 -0.467 -1.560 4.978 -2.955 -1.869
## 10 self_4 548 2.918 -0.581 -1.409 4.953 -3.227 -2.322
## 11 self_5 593 3.204 -0.917 -1.388 4.701 -4.254 -3.669
## 12 self_6 500 2.310 -0.210 -0.939 5.463 -1.271 -0.840
## 13 self_7 475 2.592 -0.383 -1.629 4.700 -2.664 -1.531
## 14 self_8 612 3.208 -0.989 -1.936 3.978 -4.367 -3.955
## 15 curio_1 558 3.065 -0.681 -1.126 5.105 -3.323 -2.726
## 16 curio_2 506 2.917 -0.616 -1.576 4.525 -3.138 -2.466
## 17 curio_3 553 2.976 -0.630 -1.262 5.016 -3.150 -2.519
## 18 curio_4 476 2.721 -0.465 -1.362 5.220 -2.384 -1.862
## 19 curio_5 558 2.683 -0.475 -1.552 5.093 -2.449 -1.898
## 20 curio_6 537 3.052 -0.623 -0.919 5.217 -3.175 -2.494
## 21 curio_7 475 2.659 -0.397 -1.385 5.237 -2.343 -1.587
## 22 curio_8 493 2.870 -0.543 -1.385 5.049 -2.890 -2.171
## 23 curio_9 555 2.773 -0.489 -1.384 5.142 -2.595 -1.957
## 24 curio_10 520 2.763 -0.496 -1.442 5.105 -2.551 -1.983
## 25 curio_11 482 2.633 -0.430 -1.543 5.155 -2.334 -1.719
## 26 info_1 467 1.368 0.365 -0.962 6.483 0.326 1.459
## 27 info_2 414 1.966 -0.013 -1.524 5.406 -1.239 -0.054
## 28 info_3 443 1.616 0.339 -1.074 6.307 -0.469 1.356
## 29 info_4 418 2.423 -0.254 -1.382 5.365 -1.960 -1.017
## 30 info_5 476 1.992 -0.011 -1.231 5.911 -0.999 -0.044
## 31 info_6 491 2.731 -0.472 -1.573 4.705 -2.601 -1.889
## 32 inter_d_1 555 3.050 -0.697 -1.330 4.932 -3.344 -2.787
## 33 inter_d_2 561 2.709 -0.413 -1.216 4.995 -2.206 -1.653
## 34 inter_d_3 536 2.991 -0.656 -1.443 4.899 -3.281 -2.624
## 35 inter_d_4 532 2.814 -0.437 -0.992 5.396 -2.430 -1.747
## 36 inter_d_5 443 2.666 -0.436 -1.673 5.044 -2.504 -1.746
## 37 inter_d_6 527 2.364 -0.198 -1.097 5.686 -1.573 -0.792
## 38 inter_d_7 479 2.693 -0.405 -1.485 5.126 -2.597 -1.620
## 39 inter_d_8 500 2.556 -0.314 -1.468 5.226 -2.373 -1.257
## 40 deci_1 566 2.864 -0.598 -1.554 4.901 -2.975 -2.391
## 41 deci_2 503 2.594 -0.341 -1.369 5.258 -2.382 -1.364
## 42 deci_3 560 3.018 -0.705 -1.350 4.952 -3.272 -2.820
## 43 deci_4 575 2.969 -0.701 -1.703 4.734 -3.212 -2.802
## 44 deci_5 531 2.968 -0.636 -1.340 4.612 -3.196 -2.546
## B.Cat1.Dim1 B.Cat2.Dim1 B.Cat3.Dim1 B.Cat4.Dim1
## 1 1 2 3 4
## 2 1 2 3 4
## 3 1 2 3 4
## 4 1 2 3 4
## 5 1 2 3 4
## 6 1 2 3 4
## 7 1 2 3 4
## 8 1 2 3 4
## 9 1 2 3 4
## 10 1 2 3 4
## 11 1 2 3 4
## 12 1 2 3 4
## 13 1 2 3 4
## 14 1 2 3 4
## 15 1 2 3 4
## 16 1 2 3 4
## 17 1 2 3 4
## 18 1 2 3 4
## 19 1 2 3 4
## 20 1 2 3 4
## 21 1 2 3 4
## 22 1 2 3 4
## 23 1 2 3 4
## 24 1 2 3 4
## 25 1 2 3 4
## 26 1 2 3 4
## 27 1 2 3 4
## 28 1 2 3 4
## 29 1 2 3 4
## 30 1 2 3 4
## 31 1 2 3 4
## 32 1 2 3 4
## 33 1 2 3 4
## 34 1 2 3 4
## 35 1 2 3 4
## 36 1 2 3 4
## 37 1 2 3 4
## 38 1 2 3 4
## 39 1 2 3 4
## 40 1 2 3 4
## 41 1 2 3 4
## 42 1 2 3 4
## 43 1 2 3 4
## 44 1 2 3 4
##
## Item Parameters Xsi
## xsi se.xsi
## 癤풹chieve_1_Cat1 -1.589 0.264
## 癤풹chieve_1_Cat2 6.263 0.145
## 癤풹chieve_1_Cat3 -8.342 0.145
## 癤풹chieve_1_Cat4 0.231 0.090
## achieve_2_Cat1 -2.753 0.389
## achieve_2_Cat2 6.308 0.139
## achieve_2_Cat3 -7.730 0.139
## achieve_2_Cat4 1.104 0.120
## achieve_3_Cat1 -1.267 0.185
## achieve_3_Cat2 6.524 0.117
## achieve_3_Cat3 -7.764 0.117
## achieve_3_Cat4 0.804 0.105
## achieve_4_Cat1 -1.013 0.145
## achieve_4_Cat2 6.391 0.107
## achieve_4_Cat3 -6.904 0.106
## achieve_4_Cat4 0.742 0.114
## achieve_5_Cat1 -2.065 0.366
## achieve_5_Cat2 6.324 0.164
## achieve_5_Cat3 -8.745 0.164
## achieve_5_Cat4 1.141 0.106
## achieve_6_Cat1 -1.845 0.291
## achieve_6_Cat2 6.156 0.143
## achieve_6_Cat3 -7.964 0.143
## achieve_6_Cat4 1.537 0.126
## self_1_Cat1 -1.397 0.198
## self_1_Cat2 6.566 0.120
## self_1_Cat3 -7.820 0.120
## self_1_Cat4 1.218 0.118
## self_2_Cat1 -1.510 0.194
## self_2_Cat2 6.527 0.115
## self_2_Cat3 -7.733 0.114
## self_2_Cat4 0.566 0.100
## self_3_Cat1 -1.560 0.216
## self_3_Cat2 6.539 0.124
## self_3_Cat3 -7.933 0.124
## self_3_Cat4 1.086 0.112
## self_4_Cat1 -1.409 0.222
## self_4_Cat2 6.364 0.127
## self_4_Cat3 -8.181 0.127
## self_4_Cat4 0.905 0.100
## self_5_Cat1 -1.388 0.302
## self_5_Cat2 6.090 0.172
## self_5_Cat3 -8.955 0.172
## self_5_Cat4 0.585 0.089
## self_6_Cat1 -0.939 0.136
## self_6_Cat2 6.402 0.106
## self_6_Cat3 -6.736 0.106
## self_6_Cat4 0.431 0.110
## self_7_Cat1 -1.629 0.197
## self_7_Cat2 6.329 0.116
## self_7_Cat3 -7.365 0.116
## self_7_Cat4 1.133 0.119
## self_8_Cat1 -1.936 0.328
## self_8_Cat2 5.913 0.155
## self_8_Cat3 -8.346 0.155
## self_8_Cat4 0.412 0.086
## curio_1_Cat1 -1.126 0.225
## curio_1_Cat2 6.232 0.142
## curio_1_Cat3 -8.429 0.142
## curio_1_Cat4 0.598 0.093
## curio_2_Cat1 -1.576 0.228
## curio_2_Cat2 6.101 0.129
## curio_2_Cat3 -7.666 0.129
## curio_2_Cat4 0.673 0.101
## curio_3_Cat1 -1.262 0.211
## curio_3_Cat2 6.279 0.130
## curio_3_Cat3 -8.166 0.130
## curio_3_Cat4 0.631 0.095
## curio_4_Cat1 -1.362 0.186
## curio_4_Cat2 6.583 0.120
## curio_4_Cat3 -7.604 0.120
## curio_4_Cat4 0.522 0.106
## curio_5_Cat1 -1.552 0.179
## curio_5_Cat2 6.647 0.108
## curio_5_Cat3 -7.542 0.108
## curio_5_Cat4 0.550 0.099
## curio_6_Cat1 -0.919 0.220
## curio_6_Cat2 6.137 0.145
## curio_6_Cat3 -8.392 0.145
## curio_6_Cat4 0.681 0.096
## curio_7_Cat1 -1.385 0.186
## curio_7_Cat2 6.624 0.118
## curio_7_Cat3 -7.580 0.118
## curio_7_Cat4 0.755 0.110
## curio_8_Cat1 -1.385 0.212
## curio_8_Cat2 6.436 0.128
## curio_8_Cat3 -7.939 0.128
## curio_8_Cat4 0.719 0.104
## curio_9_Cat1 -1.384 0.184
## curio_9_Cat2 6.527 0.113
## curio_9_Cat3 -7.737 0.113
## curio_9_Cat4 0.638 0.098
## curio_10_Cat1 -1.442 0.189
## curio_10_Cat2 6.549 0.116
## curio_10_Cat3 -7.656 0.116
## curio_10_Cat4 0.568 0.101
## curio_11_Cat1 -1.543 0.187
## curio_11_Cat2 6.700 0.115
## curio_11_Cat3 -7.490 0.115
## curio_11_Cat4 0.615 0.108
## info_1_Cat1 -0.963 0.114
## info_1_Cat2 7.445 0.124
## info_1_Cat3 -6.159 0.124
## info_1_Cat4 1.132 0.178
## info_2_Cat1 -1.524 0.157
## info_2_Cat2 6.930 0.117
## info_2_Cat3 -6.647 0.117
## info_2_Cat4 1.185 0.150
## info_3_Cat1 -1.074 0.127
## info_3_Cat2 7.382 0.115
## info_3_Cat3 -6.775 0.115
## info_3_Cat4 1.825 0.190
## info_4_Cat1 -1.382 0.178
## info_4_Cat2 6.748 0.118
## info_4_Cat3 -7.325 0.118
## info_4_Cat4 0.944 0.126
## info_5_Cat1 -1.231 0.138
## info_5_Cat2 7.144 0.107
## info_5_Cat3 -6.911 0.107
## info_5_Cat4 0.955 0.132
## info_6_Cat1 -1.573 0.203
## info_6_Cat2 6.278 0.117
## info_6_Cat3 -7.308 0.117
## info_6_Cat4 0.712 0.106
## inter_d_1_Cat1 -1.330 0.232
## inter_d_1_Cat2 6.264 0.137
## inter_d_1_Cat3 -8.277 0.137
## inter_d_1_Cat4 0.557 0.093
## inter_d_2_Cat1 -1.216 0.167
## inter_d_2_Cat2 6.212 0.108
## inter_d_2_Cat3 -7.203 0.108
## inter_d_2_Cat4 0.553 0.098
## inter_d_3_Cat1 -1.443 0.232
## inter_d_3_Cat2 6.343 0.133
## inter_d_3_Cat3 -8.180 0.132
## inter_d_3_Cat4 0.657 0.097
## inter_d_4_Cat1 -0.992 0.177
## inter_d_4_Cat2 6.390 0.119
## inter_d_4_Cat3 -7.827 0.119
## inter_d_4_Cat4 0.683 0.100
## inter_d_5_Cat1 -1.673 0.211
## inter_d_5_Cat2 6.719 0.121
## inter_d_5_Cat3 -7.549 0.121
## inter_d_5_Cat4 0.758 0.114
## inter_d_6_Cat1 -1.097 0.143
## inter_d_6_Cat2 6.785 0.103
## inter_d_6_Cat3 -7.260 0.103
## inter_d_6_Cat4 0.781 0.111
## inter_d_7_Cat1 -1.485 0.201
## inter_d_7_Cat2 6.612 0.119
## inter_d_7_Cat3 -7.724 0.119
## inter_d_7_Cat4 0.977 0.112
## inter_d_8_Cat1 -1.468 0.181
## inter_d_8_Cat2 6.696 0.111
## inter_d_8_Cat3 -7.600 0.111
## inter_d_8_Cat4 1.117 0.116
## deci_1_Cat1 -1.554 0.203
## deci_1_Cat2 6.456 0.116
## deci_1_Cat3 -7.876 0.116
## deci_1_Cat4 0.584 0.096
## deci_2_Cat1 -1.368 0.179
## deci_2_Cat2 6.628 0.111
## deci_2_Cat3 -7.640 0.111
## deci_2_Cat4 1.018 0.112
## deci_3_Cat1 -1.350 0.218
## deci_3_Cat2 6.303 0.130
## deci_3_Cat3 -8.224 0.130
## deci_3_Cat4 0.452 0.093
## deci_4_Cat1 -1.703 0.225
## deci_4_Cat2 6.439 0.120
## deci_4_Cat3 -7.947 0.120
## deci_4_Cat4 0.410 0.092
## deci_5_Cat1 -1.340 0.219
## deci_5_Cat2 5.951 0.132
## deci_5_Cat3 -7.810 0.132
## deci_5_Cat4 0.650 0.098
##
## Item Parameters in IRT parameterization
## item alpha beta tau.Cat1 tau.Cat2 tau.Cat3 tau.Cat4
## 1 癤풹chieve_1 1 -0.860 -0.729 7.121 -7.482 1.091
## 2 achieve_2 1 -0.767 -1.985 7.075 -6.961 1.872
## 3 achieve_3 1 -0.426 -0.841 6.949 -7.338 1.230
## 4 achieve_4 1 -0.195 -0.817 6.586 -6.707 0.938
## 5 achieve_5 1 -0.836 -1.229 7.159 -7.908 1.978
## 6 achieve_6 1 -0.528 -1.317 6.684 -7.433 2.065
## 7 self_1 1 -0.359 -1.039 6.923 -7.461 1.576
## 8 self_2 1 -0.538 -0.972 7.063 -7.195 1.104
## 9 self_3 1 -0.467 -1.092 7.004 -7.465 1.553
## 10 self_4 1 -0.581 -0.828 6.943 -7.600 1.485
## 11 self_5 1 -0.917 -0.471 7.006 -8.037 1.502
## 12 self_6 1 -0.210 -0.729 6.612 -6.524 0.641
## 13 self_7 1 -0.383 -1.247 6.712 -6.981 1.516
## 14 self_8 1 -0.989 -0.947 6.902 -7.356 1.400
## 15 curio_1 1 -0.681 -0.445 6.912 -7.747 1.279
## 16 curio_2 1 -0.616 -0.959 6.718 -7.047 1.289
## 17 curio_3 1 -0.630 -0.632 6.907 -7.536 1.261
## 18 curio_4 1 -0.465 -0.896 7.047 -7.138 0.988
## 19 curio_5 1 -0.475 -1.078 7.120 -7.067 1.025
## 20 curio_6 1 -0.623 -0.296 6.759 -7.768 1.304
## 21 curio_7 1 -0.397 -0.989 7.019 -7.183 1.152
## 22 curio_8 1 -0.543 -0.842 6.977 -7.396 1.262
## 23 curio_9 1 -0.489 -0.895 7.015 -7.248 1.127
## 24 curio_10 1 -0.496 -0.947 7.043 -7.160 1.064
## 25 curio_11 1 -0.430 -1.114 7.129 -7.060 1.045
## 26 info_1 1 0.365 -1.327 7.081 -6.521 0.768
## 27 info_2 1 -0.013 -1.510 6.943 -6.631 1.198
## 28 info_3 1 0.339 -1.413 7.041 -7.114 1.486
## 29 info_4 1 -0.254 -1.128 7.001 -7.071 1.198
## 30 info_5 1 -0.011 -1.220 7.153 -6.899 0.966
## 31 info_6 1 -0.472 -1.101 6.750 -6.834 1.185
## 32 inter_d_1 1 -0.697 -0.633 6.959 -7.580 1.254
## 33 inter_d_2 1 -0.413 -0.803 6.625 -6.788 0.967
## 34 inter_d_3 1 -0.656 -0.787 6.998 -7.524 1.313
## 35 inter_d_4 1 -0.437 -0.555 6.825 -7.390 1.120
## 36 inter_d_5 1 -0.436 -1.237 7.154 -7.112 1.194
## 37 inter_d_6 1 -0.198 -0.899 6.981 -7.061 0.979
## 38 inter_d_7 1 -0.405 -1.080 7.016 -7.318 1.382
## 39 inter_d_8 1 -0.314 -1.154 7.008 -7.285 1.431
## 40 deci_1 1 -0.598 -0.956 7.052 -7.278 1.181
## 41 deci_2 1 -0.341 -1.028 6.967 -7.299 1.359
## 42 deci_3 1 -0.705 -0.645 7.007 -7.519 1.157
## 43 deci_4 1 -0.701 -1.002 7.138 -7.246 1.111
## 44 deci_5 1 -0.636 -0.703 6.588 -7.171 1.287
## Iteration in WLE/MLE estimation 1 | Maximal change 2.1117
## Iteration in WLE/MLE estimation 2 | Maximal change 1.6241
## Iteration in WLE/MLE estimation 3 | Maximal change 1.0457
## Iteration in WLE/MLE estimation 4 | Maximal change 0.515
## Iteration in WLE/MLE estimation 5 | Maximal change 0.1071
## Iteration in WLE/MLE estimation 6 | Maximal change 0.0332
## Iteration in WLE/MLE estimation 7 | Maximal change 0.0089
## Iteration in WLE/MLE estimation 8 | Maximal change 0.0025
## Iteration in WLE/MLE estimation 9 | Maximal change 7e-04
## Iteration in WLE/MLE estimation 10 | Maximal change 2e-04
## Iteration in WLE/MLE estimation 11 | Maximal change 1e-04
## ----
## WLE Reliability= 0.88
## ....................................................
## Plots exported in png format into folder:
## C:/Users/user/Documents/R/R_work/rasch/Rasch_1/Plots
Note that the echo = FALSE parameter was added to the code chunk to
prevent printing of the R code that generated the plot.