Dr. Sun’s Project
Cheng Hua
1/9/2021
Import the dataset
library(readxl)
Teacher_Leadership <- read_excel("Teacher_Leadership.xlsx")Descriptive Data Analysis
First, we take a look at the overall data.
library(psych)
summary <- describe(Teacher_Leadership)
mean(summary$mean) # Total_mean=4.44## [1] 4.440501mean(summary$sd) # Mean_sd=0.72## [1] 0.7161432Then, we take out these data that contains all unique responses.
library(dplyr)
## Take the observation with non-unique values
TL_data_clean <- Teacher_Leadership[rowSums(Teacher_Leadership[-1] != Teacher_Leadership[[2]], na.rm = TRUE) != 0,]
## Descriptive Analysis
summary <- describe(TL_data_clean)
summary## vars n mean sd median trimmed mad min max range skew kurtosis se
## JS58 1 400 4.21 0.79 4 4.31 1.48 1 5 4 -1.18 2.19 0.04
## JS59 2 400 4.09 0.83 4 4.18 1.48 1 5 4 -0.93 1.13 0.04
## JS60 3 400 4.07 0.87 4 4.17 1.48 1 5 4 -1.02 1.23 0.04
## JS61 4 400 4.13 0.80 4 4.22 1.48 1 5 4 -0.99 1.52 0.04
## JS62 5 400 4.01 0.88 4 4.11 1.48 1 5 4 -0.98 1.20 0.04
## JS63 6 400 4.24 0.80 4 4.36 1.48 1 5 4 -1.30 2.59 0.04
## JS64 7 400 3.99 0.87 4 4.08 0.74 1 5 4 -0.96 1.27 0.04
## JS65 8 400 4.03 0.92 4 4.15 1.48 1 5 4 -1.11 1.38 0.05
## JS66 9 400 3.96 0.92 4 4.07 1.48 1 5 4 -1.08 1.50 0.05
## JS67 10 400 4.03 0.82 4 4.11 0.00 1 5 4 -1.04 1.87 0.04
## JS68 11 400 4.26 0.81 4 4.39 1.48 1 5 4 -1.40 2.88 0.04
## JS69 12 400 4.08 0.93 4 4.21 1.48 1 5 4 -1.18 1.46 0.05
## JS70 13 400 4.16 0.78 4 4.24 1.48 1 5 4 -0.85 0.93 0.04
## JS71 14 400 4.07 0.77 4 4.12 0.00 1 5 4 -0.67 0.68 0.04
## JS72 15 400 4.20 0.82 4 4.32 1.48 1 5 4 -1.15 1.78 0.04
## JS73 16 400 4.22 0.76 4 4.32 1.48 1 5 4 -1.07 1.94 0.04
## JS74 17 400 4.11 0.81 4 4.20 0.00 1 5 4 -1.10 1.93 0.04
## JS75 18 400 4.12 0.90 4 4.25 1.48 1 5 4 -1.40 2.57 0.05
## JS76 19 400 4.16 0.77 4 4.25 0.00 1 5 4 -1.02 1.80 0.04
## JS77 20 400 4.22 0.75 4 4.32 0.00 1 5 4 -1.02 1.75 0.04mean(summary$mean) # Total_mean=4.12 Dropped from 4.44## [1] 4.117125mean(summary$sd) # Mean_sd=0.83 increased from 0.72## [1] 0.8296068library("Hmisc")## Loading required package: lattice## Loading required package: survival## Loading required package: Formula## Loading required package: ggplot2##
## Attaching package: 'ggplot2'## The following objects are masked from 'package:psych':
##
## %+%, alpha##
## Attaching package: 'Hmisc'## The following objects are masked from 'package:dplyr':
##
## src, summarize## The following object is masked from 'package:psych':
##
## describe## The following objects are masked from 'package:base':
##
## format.pval, units# Check the correlation matrix
cor(TL_data_clean, method = "pearson", use = "complete.obs")## JS58 JS59 JS60 JS61 JS62 JS63 JS64
## JS58 1.0000000 0.8138565 0.7760672 0.6776922 0.6708147 0.6998951 0.6380549
## JS59 0.8138565 1.0000000 0.7876629 0.6529497 0.6679926 0.6616871 0.6023454
## JS60 0.7760672 0.7876629 1.0000000 0.6780249 0.7328208 0.6825637 0.6548540
## JS61 0.6776922 0.6529497 0.6780249 1.0000000 0.6685119 0.6690538 0.6699278
## JS62 0.6708147 0.6679926 0.7328208 0.6685119 1.0000000 0.7068326 0.7095943
## JS63 0.6998951 0.6616871 0.6825637 0.6690538 0.7068326 1.0000000 0.7017664
## JS64 0.6380549 0.6023454 0.6548540 0.6699278 0.7095943 0.7017664 1.0000000
## JS65 0.6823366 0.6999976 0.7162558 0.6334924 0.7393530 0.7601843 0.7367483
## JS66 0.6502440 0.6725319 0.6664616 0.6057488 0.6941742 0.6800630 0.6574367
## JS67 0.6279700 0.6358567 0.6122398 0.5716388 0.6640119 0.6561686 0.6334049
## JS68 0.6969125 0.6737871 0.6655756 0.6880987 0.6704104 0.7241064 0.6764813
## JS69 0.6753029 0.7122736 0.7006363 0.6313982 0.7023624 0.6927508 0.7193776
## JS70 0.5608750 0.5968816 0.6014462 0.5629996 0.6018411 0.5970628 0.5952824
## JS71 0.4827282 0.5509434 0.5443482 0.4842123 0.5521685 0.5172176 0.5562053
## JS72 0.6910316 0.7065386 0.6879130 0.6073069 0.6807126 0.7094066 0.6708354
## JS73 0.5945429 0.5864912 0.6056969 0.5548402 0.5970966 0.6072322 0.5773295
## JS74 0.6761088 0.6620484 0.6748790 0.6315241 0.6808258 0.6842230 0.6923120
## JS75 0.6540311 0.7177837 0.6886329 0.6211248 0.6626373 0.6949230 0.6549893
## JS76 0.5802160 0.5861576 0.5434227 0.4895273 0.5710828 0.5550543 0.5301387
## JS77 0.6494520 0.6627411 0.6290709 0.5952342 0.5819078 0.6492749 0.6192514
## JS65 JS66 JS67 JS68 JS69 JS70 JS71
## JS58 0.6823366 0.6502440 0.6279700 0.6969125 0.6753029 0.5608750 0.4827282
## JS59 0.6999976 0.6725319 0.6358567 0.6737871 0.7122736 0.5968816 0.5509434
## JS60 0.7162558 0.6664616 0.6122398 0.6655756 0.7006363 0.6014462 0.5443482
## JS61 0.6334924 0.6057488 0.5716388 0.6880987 0.6313982 0.5629996 0.4842123
## JS62 0.7393530 0.6941742 0.6640119 0.6704104 0.7023624 0.6018411 0.5521685
## JS63 0.7601843 0.6800630 0.6561686 0.7241064 0.6927508 0.5970628 0.5172176
## JS64 0.7367483 0.6574367 0.6334049 0.6764813 0.7193776 0.5952824 0.5562053
## JS65 1.0000000 0.7757335 0.7389735 0.7266591 0.7863496 0.6806453 0.6186145
## JS66 0.7757335 1.0000000 0.7615049 0.7002520 0.7391887 0.6505408 0.6328665
## JS67 0.7389735 0.7615049 1.0000000 0.6937737 0.7254068 0.6124868 0.5361175
## JS68 0.7266591 0.7002520 0.6937737 1.0000000 0.7257525 0.6372354 0.5345013
## JS69 0.7863496 0.7391887 0.7254068 0.7257525 1.0000000 0.6940818 0.6282202
## JS70 0.6806453 0.6505408 0.6124868 0.6372354 0.6940818 1.0000000 0.6684057
## JS71 0.6186145 0.6328665 0.5361175 0.5345013 0.6282202 0.6684057 1.0000000
## JS72 0.7373634 0.7092327 0.7062125 0.7022633 0.7396959 0.6744340 0.6483535
## JS73 0.6482403 0.6202860 0.5646811 0.6420586 0.6655504 0.6105514 0.5152109
## JS74 0.7639598 0.7168431 0.6965316 0.6769747 0.7251425 0.6238852 0.5791299
## JS75 0.7989311 0.7329530 0.7147194 0.7141173 0.7680038 0.6476338 0.6028787
## JS76 0.6204741 0.5837785 0.5663990 0.5843984 0.6098526 0.5408368 0.4706382
## JS77 0.6790428 0.6538798 0.6126141 0.6636714 0.6966276 0.5711569 0.5296983
## JS72 JS73 JS74 JS75 JS76 JS77
## JS58 0.6910316 0.5945429 0.6761088 0.6540311 0.5802160 0.6494520
## JS59 0.7065386 0.5864912 0.6620484 0.7177837 0.5861576 0.6627411
## JS60 0.6879130 0.6056969 0.6748790 0.6886329 0.5434227 0.6290709
## JS61 0.6073069 0.5548402 0.6315241 0.6211248 0.4895273 0.5952342
## JS62 0.6807126 0.5970966 0.6808258 0.6626373 0.5710828 0.5819078
## JS63 0.7094066 0.6072322 0.6842230 0.6949230 0.5550543 0.6492749
## JS64 0.6708354 0.5773295 0.6923120 0.6549893 0.5301387 0.6192514
## JS65 0.7373634 0.6482403 0.7639598 0.7989311 0.6204741 0.6790428
## JS66 0.7092327 0.6202860 0.7168431 0.7329530 0.5837785 0.6538798
## JS67 0.7062125 0.5646811 0.6965316 0.7147194 0.5663990 0.6126141
## JS68 0.7022633 0.6420586 0.6769747 0.7141173 0.5843984 0.6636714
## JS69 0.7396959 0.6655504 0.7251425 0.7680038 0.6098526 0.6966276
## JS70 0.6744340 0.6105514 0.6238852 0.6476338 0.5408368 0.5711569
## JS71 0.6483535 0.5152109 0.5791299 0.6028787 0.4706382 0.5296983
## JS72 1.0000000 0.6540364 0.7157182 0.7288200 0.6193478 0.6796874
## JS73 0.6540364 1.0000000 0.6526084 0.6854277 0.5362726 0.5914680
## JS74 0.7157182 0.6526084 1.0000000 0.8154330 0.6814625 0.7317992
## JS75 0.7288200 0.6854277 0.8154330 1.0000000 0.6681020 0.7362299
## JS76 0.6193478 0.5362726 0.6814625 0.6681020 1.0000000 0.7356782
## JS77 0.6796874 0.5914680 0.7317992 0.7362299 0.7356782 1.0000000Principal Components / Factor Analysis
# Principal Components Analysis
# entering raw data and extracting PCs from the correlation matrix
fit <- princomp(TL_data_clean, cor=TRUE)
summary(fit) # print variance accounted for## Importance of components:
## Comp.1 Comp.2 Comp.3 Comp.4 Comp.5
## Standard deviation 3.6704732 0.8951011 0.84325058 0.74605890 0.6950841
## Proportion of Variance 0.6736187 0.0400603 0.03555358 0.02783019 0.0241571
## Cumulative Proportion 0.6736187 0.7136790 0.74923255 0.77706274 0.8012198
## Comp.6 Comp.7 Comp.8 Comp.9 Comp.10
## Standard deviation 0.67908829 0.62305494 0.59077317 0.5792633 0.55393642
## Proportion of Variance 0.02305805 0.01940987 0.01745065 0.0167773 0.01534228
## Cumulative Proportion 0.82427789 0.84368776 0.86113841 0.8779157 0.89325798
## Comp.11 Comp.12 Comp.13 Comp.14 Comp.15
## Standard deviation 0.54000157 0.52107943 0.49723589 0.49011608 0.4651022
## Proportion of Variance 0.01458008 0.01357619 0.01236218 0.01201069 0.0108160
## Cumulative Proportion 0.90783807 0.92141426 0.93377643 0.94578712 0.9566031
## Comp.16 Comp.17 Comp.18 Comp.19
## Standard deviation 0.44837599 0.435325742 0.424347893 0.404925614
## Proportion of Variance 0.01005205 0.009475425 0.009003557 0.008198238
## Cumulative Proportion 0.96665517 0.976130598 0.985134155 0.993332393
## Comp.20
## Standard deviation 0.365174133
## Proportion of Variance 0.006667607
## Cumulative Proportion 1.000000000loadings(fit) # pc loadings##
## Loadings:
## Comp.1 Comp.2 Comp.3 Comp.4 Comp.5 Comp.6 Comp.7 Comp.8 Comp.9 Comp.10
## JS58 0.225 0.393 0.281 0.120 0.108 0.137
## JS59 0.227 0.262 0.429 0.246 0.143 0.121
## JS60 0.227 0.318 0.304 -0.270 0.124
## JS61 0.211 0.369 -0.133 -0.311 -0.316 0.332 -0.223 -0.454 -0.194
## JS62 0.225 0.174 -0.175 -0.144 -0.152 -0.401 0.464 -0.221 -0.243
## JS63 0.227 0.184 -0.242 0.550 -0.125
## JS64 0.221 -0.183 -0.329 -0.155 -0.383 -0.222 0.189 0.291
## JS65 0.242 -0.195 0.117 -0.172 0.206
## JS66 0.231 -0.142 -0.105 -0.147 0.300 0.148 -0.210 -0.263
## JS67 0.222 -0.111 -0.338 0.437 0.266 0.236 -0.175
## JS68 0.230 -0.166 -0.145 0.109 0.509
## JS69 0.239 -0.104 0.393
## JS70 0.211 -0.317 -0.280 0.232 -0.190 0.312 0.411 -0.140 0.469
## JS71 0.193 -0.449 -0.379 0.395 -0.328 -0.256 -0.356
## JS72 0.234 -0.106 0.103 0.434 -0.232
## JS73 0.208 -0.111 -0.647 0.560 -0.236 -0.216
## JS74 0.234 -0.108 0.212 -0.131 -0.242 -0.270 -0.181
## JS75 0.238 -0.152 0.176 0.154 -0.116 -0.337 -0.127 0.147
## JS76 0.200 -0.198 0.603 -0.283 0.465 -0.100 -0.134
## JS77 0.220 0.460 -0.223 0.145 -0.229 0.128
## Comp.11 Comp.12 Comp.13 Comp.14 Comp.15 Comp.16 Comp.17 Comp.18 Comp.19
## JS58 0.120 0.121 0.289 0.352 0.138 0.216 0.224 0.122 0.305
## JS59 0.271 -0.105 -0.463 -0.259
## JS60 -0.457 -0.515 0.359 -0.111
## JS61 0.191 -0.243 0.235 -0.154 0.108
## JS62 -0.110 -0.248 -0.146 -0.134 0.206 0.341 -0.267
## JS63 -0.537 0.131 -0.136 0.213 0.203 0.115 -0.295
## JS64 0.459 0.208 0.235 -0.122 -0.172 -0.226 -0.208
## JS65 -0.268 -0.164 0.159 -0.275 -0.160 0.725
## JS66 -0.306 0.536 -0.113 -0.408 0.213 -0.202
## JS67 0.202 0.291 0.402 -0.390
## JS68 -0.337 -0.398 0.440 -0.338
## JS69 0.312 -0.258 -0.241 -0.318 0.289 0.108 0.301 0.497
## JS70 -0.246 0.182 0.211 -0.133 -0.115
## JS71 -0.131 0.171 0.122 0.242 -0.118
## JS72 0.200 0.511 -0.210 -0.260 -0.184 -0.438 0.116
## JS73 0.171 0.154 0.111 -0.124
## JS74 -0.189 0.417 0.312 -0.207 0.173 0.332 0.237
## JS75 -0.286 -0.346 -0.130 -0.239 -0.213
## JS76 0.167 0.284 -0.167 -0.210 0.172 -0.104
## JS77 -0.206 0.205 -0.425 -0.361 0.266 -0.258 0.200
## Comp.20
## JS58 0.443
## JS59 -0.453
## JS60
## JS61
## JS62
## JS63
## JS64
## JS65 -0.200
## JS66
## JS67
## JS68 -0.105
## JS69
## JS70
## JS71
## JS72
## JS73
## JS74 -0.387
## JS75 0.605
## JS76
## JS77
##
## Comp.1 Comp.2 Comp.3 Comp.4 Comp.5 Comp.6 Comp.7 Comp.8 Comp.9
## SS loadings 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
## Proportion Var 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05
## Cumulative Var 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45
## Comp.10 Comp.11 Comp.12 Comp.13 Comp.14 Comp.15 Comp.16 Comp.17
## SS loadings 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
## Proportion Var 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05
## Cumulative Var 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85
## Comp.18 Comp.19 Comp.20
## SS loadings 1.00 1.00 1.00
## Proportion Var 0.05 0.05 0.05
## Cumulative Var 0.90 0.95 1.00plot(fit,type="lines") # scree plot
fit$scores # the principal components## Comp.1 Comp.2 Comp.3 Comp.4 Comp.5
## [1,] -2.20725523 -0.2263117646 0.625367885 -0.5111852397 0.260259680
## [2,] 0.19738759 0.4606807529 0.194450864 -0.2863615130 0.425763787
## [3,] 3.89923963 0.2569080352 -1.173955897 0.2620005890 0.140474238
## [4,] 0.44108347 -0.5478163878 0.138290011 -0.9809886766 0.908529398
## [5,] 2.65331593 0.5006714968 0.333268553 1.1424989594 -0.847097860
## [6,] 2.85515841 -0.5915168822 -0.763367526 0.2397838225 -1.316502926
## [7,] -0.62027521 0.0003834008 -0.068319573 -0.2722969952 0.108363711
## [8,] 3.43760560 -0.5562402288 0.367753737 -1.1568730214 -0.097043031
## [9,] -7.38743289 0.1105756554 -1.109577794 -1.5771402272 -1.849548215
## [10,] 1.52442748 -0.6628943147 -1.338798304 0.5070963282 -0.697823310
## [11,] 1.02666855 -0.3664739949 1.253787756 -0.4047637622 -0.035064367
## [12,] 3.40522121 0.0241033187 -0.923633255 -1.0380144659 0.125586353
## [13,] -4.37039847 1.6833008418 -0.402834887 -0.7550929922 0.207628895
## [14,] 4.20823648 -0.5985991160 0.174757685 0.5828026783 0.041143149
## [15,] -4.95410869 -0.3890118024 -0.508815860 -0.3718945736 -0.655651031
## [16,] -4.91849994 0.0885900803 1.184569716 0.2744721478 0.649268827
## [17,] -8.86235749 2.8825696857 1.350655405 0.9185202009 -0.990789389
## [18,] -0.12798498 -1.0256467554 -1.045475440 0.6808620215 0.118161292
## [19,] 3.16603976 1.1157364738 0.486035360 0.1587623950 -1.043235357
## [20,] 2.87146600 -2.3485697047 0.441673092 -0.2139191803 0.045183849
## [21,] 4.49394688 -0.2812048721 0.111894237 0.4951817520 0.193122123
## [22,] -0.90437254 -0.1448536179 0.019159255 0.2480298495 0.452546062
## [23,] 4.47556442 -0.0235653156 -0.115190045 0.0425581884 0.866896128
## [24,] 4.22747463 -0.2756834276 -0.803469859 -0.3251789214 -0.085217315
## [25,] 1.29558906 -1.0645636765 0.639041810 1.6921215987 0.737749235
## [26,] 0.46080131 0.3834379272 -0.545011417 -0.6761995720 0.139545248
## [27,] -6.24539027 0.5039359752 -0.482321895 0.0262457345 0.655241678
## [28,] 3.40515954 0.1985801279 0.644349216 0.3112371639 -0.287723551
## [29,] 2.29324312 -0.2377635598 -1.178805479 0.6337822399 0.261861673
## [30,] 3.39950713 0.0311271131 0.288919047 0.6596163352 0.827218704
## [31,] 2.80923131 -0.3222613434 -0.429092653 -0.1496395948 0.528535689
## [32,] 2.04640315 -0.0011888748 -0.078206192 -0.5783064165 -0.612221532
## [33,] 2.30490792 0.1982034539 0.850912693 0.3529203785 -0.606718946
## [34,] 1.79376514 0.2601572593 0.494669779 -0.2599436492 0.362422466
## [35,] 1.01784294 -0.0010644191 0.859098276 -0.5076316591 0.032029062
## [36,] 1.48630657 -0.9910494384 -1.458745216 0.4211394763 -0.868408592
## [37,] 2.61310424 -1.3725626286 0.482490058 -1.1472274538 -0.141003985
## [38,] 1.79951857 0.3945246622 -0.706477874 0.4995256316 0.819353973
## [39,] 2.07432635 -0.4727161273 0.325602374 -0.0793652176 -0.710737925
## [40,] 4.23151546 -0.7404550656 0.277764563 0.5410286686 0.579955779
## [41,] 0.19804078 0.1664195881 0.520834360 -0.2634018002 -0.240918576
## [42,] 1.53417799 -0.0168666015 -0.150558178 1.5829486860 0.110809653
## [43,] 0.77449195 0.3762133001 0.350154526 0.0790404755 0.270439275
## [44,] -0.10171538 -3.3475215449 0.561125566 -0.2604079483 -0.090641129
## [45,] -0.88447400 2.6326924401 -4.438648676 0.1627141541 -2.414822774
## [46,] -4.66961875 1.7346926270 -0.992019926 -0.9309689370 0.012301366
## [47,] 0.14398798 -0.0593828788 -0.447640753 -0.4347313163 -0.379860539
## [48,] 0.42676929 -0.6752097711 -0.612761359 -0.2426412460 0.559089891
## [49,] -0.35368487 -0.1594673118 0.424937914 -0.0560122587 0.179108037
## [50,] -0.38934745 0.3303185466 -0.275115215 0.2162354618 0.386672027
## [51,] -0.37852131 -0.4413180812 -0.552376126 0.1664768747 0.030396760
## [52,] 3.08933746 0.3136237043 -0.152881890 0.3373033834 1.154301917
## [53,] 3.19128020 1.1139941262 1.204454180 0.3067443856 -0.548121356
## [54,] 3.42966383 0.0034278397 0.381012979 1.3233932126 -0.525548871
## [55,] 3.93235506 0.5201993439 0.299786542 0.1590702318 0.574143111
## [56,] -3.81240297 -1.3226388580 0.647490100 0.9159866453 1.643778515
## [57,] -4.92546858 -1.7927145448 0.689086354 -1.6319051077 -0.036981044
## [58,] -1.16680397 -0.6041038115 0.185029581 0.2938767661 0.839379718
## [59,] -0.09242413 -0.4185510076 1.211961414 0.0370527224 0.166738242
## [60,] -0.59459844 0.2316724847 -0.027830892 -0.4271275649 -0.104662261
## [61,] 3.41645365 -1.2252368736 0.449293892 -1.5750153334 -0.247184979
## [62,] -0.90437254 -0.1448536179 0.019159255 0.2480298495 0.452546062
## [63,] -0.91326556 0.5331262172 0.365533983 -0.6995750135 -0.735844845
## [64,] 3.96048915 0.7292893652 0.182219632 -0.4115027745 0.776435997
## [65,] -0.09242413 -0.4185510076 1.211961414 0.0370527224 0.166738242
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## [68,] -8.45858599 -0.9357333953 0.190755298 -1.4893857472 1.254704466
## [69,] 1.81074560 -1.4493783059 0.812767489 0.9108608873 -0.549148701
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## [76,] 1.44229621 -0.1532832569 -1.707682547 0.4058663244 0.095594573
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## [79,] -0.36636861 0.0849195311 -0.222034238 -0.3357868055 0.095588807
## [80,] 2.29212926 0.1624672650 -1.220954621 -0.5094952988 0.366818341
## [81,] 0.69262425 -0.0826718668 -0.339429944 -1.0153823449 -0.721347291
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## [84,] 0.49441490 -0.4783546184 -0.479155139 0.2376081376 -0.847875453
## [85,] 3.10994836 -1.4250632014 -1.447915115 -1.2291980995 -0.051904261
## [86,] 2.07093503 -0.7972984221 -1.086892377 -0.0801840575 0.768328911
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## [89,] -7.07818695 1.3610063516 0.752927943 -0.9816085680 0.329045571
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## [93,] 2.36446964 0.3143067004 0.025335206 -1.8755620828 0.113548538
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## [95,] 1.92039326 -2.5859155224 1.743292759 1.3000352946 0.562804844
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## [101,] -3.32460959 0.4620893571 -0.023106297 0.5430037377 -0.121156562
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## [106,] 3.15087269 0.3976869881 -0.174960139 1.0170672975 0.621157899
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## [113,] -0.90000209 0.5502800128 0.300951036 -0.6459003373 0.186489895
## [114,] 0.65768272 -0.6431284786 -0.742065114 -0.4301366502 0.557408609
## [115,] -2.24841766 -0.0144000650 -1.062529661 0.4834546944 -0.164161021
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## [119,] 2.90329086 0.0876847111 -0.224717509 0.6978488752 -0.473330515
## [120,] 4.47658876 -0.0339046760 -0.044664556 0.5301408206 -0.521780196
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## [122,] -1.45800800 0.5052384582 -1.482148569 -0.1400884117 0.055405035
## [123,] 3.65947971 0.4011328085 -0.396289071 0.4430576599 -0.169451045
## [124,] 2.08612669 0.0895349781 0.893274420 1.0933830923 0.377110027
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## [127,] 0.97196606 1.1956316363 -0.482969896 0.6111211294 0.510506244
## [128,] 3.69432396 -1.0861409305 0.277724483 0.3432052321 0.100752656
## [129,] -1.69322675 0.7405718677 -0.122120480 -1.3207559472 -0.538287891
## [130,] -0.90096638 0.1207361119 -0.078038877 0.0284795012 -0.052111150
## [131,] 4.18987353 -0.5240359537 -0.229339527 -0.3152599397 0.714058582
## [132,] -0.90437254 -0.1448536179 0.019159255 0.2480298495 0.452546062
## [133,] 4.45955945 -0.0370366219 -0.361180068 0.2771793369 0.048023446
## [134,] 2.27066134 -1.1365734118 -1.309740156 -0.7032826393 -0.034944092
## [135,] 4.23151546 -0.7404550656 0.277764563 0.5410286686 0.579955779
## [136,] -11.46120492 0.3246370505 -0.346921368 0.0830245677 1.004667849
## [137,] 3.40881368 -0.8246243800 0.083187979 0.2817421176 1.352796776
## [138,] -1.93846907 -0.5708194207 0.570408206 0.8301661071 0.315063467
## [139,] -0.11163757 -0.3494092679 0.019318108 -0.1187608508 -0.575115614
## [140,] -0.90437254 -0.1448536179 0.019159255 0.2480298495 0.452546062
## [141,] 2.55533518 0.4356722497 -1.154707735 0.0371004121 1.782601862
## [142,] 0.97908910 -1.0681268568 -0.653805991 0.2456268220 -1.186007992
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## [144,] -3.85558764 -1.8522025521 0.690326231 0.5802429464 -0.542224852
## [145,] -0.09714558 -1.3522111289 -0.895281794 0.9708073021 0.118641365
## [146,] -9.02654131 0.3982786478 0.436141938 1.4056405192 -0.397167326
## [147,] -4.88929691 0.4169803049 1.001755071 0.3170035383 -0.429755744
## [148,] -1.14916100 0.8123127011 -0.060518923 1.0367533676 -1.126801947
## [149,] 4.24778100 0.9982574327 0.886785332 -0.9131335816 -0.160698576
## [150,] 3.69442640 -0.0264455872 0.819670075 -0.1001096780 0.421922146
## [151,] 3.37886644 -0.9578683646 -1.258466021 -1.0379994593 -0.500691350
## [152,] 3.96978747 -0.0119537905 0.525913644 -0.5357484296 -0.190471855
## [153,] 4.19712802 -0.4962868154 -0.195309742 0.3230262535 0.434857102
## [154,] 0.45147126 0.1002058820 0.346456571 -0.5835024089 0.155490975
## [155,] 0.47364597 -0.5946031392 0.050600856 0.1107867152 -1.095480890
## [156,] -1.95961994 -0.0091303134 0.687901450 0.2584283147 0.920715388
## [157,] -8.71002736 -0.7766364762 0.375470023 -0.3477545730 -1.014670979
## [158,] -5.78652444 -0.1567811030 0.502140240 -0.2856021120 0.521308570
## [159,] -0.63988379 0.9146472207 0.217984099 -0.2981496850 0.298907495
## [160,] 1.49965570 -0.7385443550 -0.773245749 -1.2391352239 0.783823309
## [161,] 0.96335511 -0.4115307920 -0.946789756 0.5770374011 -0.369101315
## [162,] 1.51924350 0.7783533403 -0.113010480 -0.2099649389 0.481386185
## [163,] 2.01549801 -1.5513731016 -1.631200544 -0.5401653243 0.004905759
## [164,] -1.18929631 0.6836433064 0.039184264 -0.4843577123 0.219682852
## [165,] 3.38880422 -1.7785145546 0.064495233 -0.6393111369 -0.519941442
## [166,] -2.47602501 -0.3132835604 0.084110070 -0.1334033482 -0.447284157
## [167,] -0.92173067 0.1024465782 -0.137399539 0.2829889182 -0.262356257
## [168,] -1.16963024 -0.1555490439 0.079120946 0.2447794589 0.076303754
## [169,] -2.23257053 0.8549248980 1.192561838 -0.3148059130 0.340419423
## [170,] -0.10279472 0.2006377422 -0.323921413 0.3429886616 0.456941128
## [171,] 2.06771069 1.7562822409 -0.686790047 -0.1313020723 -0.318084946
## [172,] 0.17831865 -0.0960655476 -0.522339285 -0.2640805671 -0.813800205
## [173,] -0.05172773 0.7705527573 0.692644039 -0.3765463106 -0.545931156
## [174,] 4.24341055 0.3031238020 0.604993551 -0.0192033948 0.105357591
## [175,] -2.30524286 -0.1909820207 -3.100546260 -1.0473927202 -1.201969812
## [176,] -2.23480112 -0.9301614877 1.492718409 -0.4172001641 -0.448436380
## [177,] 0.70409632 -0.5771091737 -1.290037923 0.5574966897 -0.377068883
## [178,] 3.43700602 0.0858753043 0.890044716 -0.0506686327 0.387561793
## [179,] 2.59893866 -1.0508549195 0.279257814 -0.2824368533 -1.677450138
## [180,] -2.76897097 0.5627373440 0.934184654 -0.9799766290 -0.696570477
## [181,] 2.35365104 0.0578812458 1.087681188 1.7056696822 -0.383540188
## [182,] 4.22048886 0.3491903958 0.331189193 -0.1329143080 0.224327804
## [183,] 1.25147793 0.0459350923 0.723334968 -0.2214033963 0.109391972
## [184,] -0.37617650 -0.1808832613 -0.176371529 -0.0584366670 -0.577811212
## [185,] 3.66698998 -1.8095655477 -0.043805422 -1.0606301867 -0.159420446
## [186,] -5.16528492 -0.6400013068 1.311912863 -0.8298247285 -0.882877395
## [187,] -3.30391398 0.5792517075 -0.684932690 1.5813377873 -0.421208451
## [188,] -4.97374201 -0.2866290415 0.347130900 -0.9538188809 0.913613987
## [189,] 1.52449215 -0.4566935856 0.204068291 -1.4616243573 0.932534587
## [190,] 2.36205259 0.5832734838 1.177671426 0.4442527928 0.980547446
## [191,] -4.91964238 0.7120409841 0.314579279 0.5291578191 0.774056222
## [192,] 0.17852031 -0.8258204275 0.851733567 0.3350447876 -0.077119426
## [193,] 2.61485849 0.9820237641 -0.038473956 0.3532340970 0.102660678
## [194,] 1.78397377 -0.7197716972 0.350417660 -0.2108588497 -0.083462026
## [195,] -6.24339036 1.5040745538 2.090303575 -1.1903927689 -2.105235896
## [196,] 2.56345318 0.3593760522 -0.069780104 1.1188469469 -1.107963645
## [197,] 4.47790923 0.2368695044 0.260814552 -0.1823553533 0.258688156
## [198,] -2.00520717 -0.0716179499 -0.133952533 1.2631839717 2.113873850
## [199,] -0.92308883 -0.3491262539 -0.271228185 -0.6480602253 -0.021575018
## [200,] -0.39892942 -0.6183773354 -0.685247592 0.3828699562 0.362018960
## [201,] -6.27939821 0.1267591874 0.318801660 -1.0430117257 0.637047115
## [202,] -1.94187680 1.1360841130 0.441744262 -0.0665246068 -0.801798270
## [203,] 0.12412215 -0.2946482921 0.313193048 -0.4674362948 0.117953350
## [204,] 0.46140903 -0.7204403079 1.669417824 -0.1848140865 0.136240883
## [205,] 2.87665329 -1.1090843106 0.142405486 -0.4418647456 -0.626953753
## [206,] -1.46889802 -1.2139640999 -0.302410731 -1.3536290057 -0.286830164
## [207,] -1.21642290 2.2997549809 -1.855460566 0.8386314262 0.063559610
## [208,] -2.56074894 0.0326513478 -0.673630387 0.5346875815 -0.511058751
## [209,] -2.26773393 -1.7497451516 0.052740134 -0.8438135119 -0.130260397
## [210,] 0.43239793 1.6051169709 -0.247756151 1.0447517081 0.448505362
## [211,] 2.02948443 1.8097955124 -0.808566516 -0.0492241788 0.732414657
## [212,] -3.83045680 0.1502814610 -0.064193781 0.3649238868 0.860687754
## [213,] 4.49831734 0.4139287586 0.393686018 -0.3987484348 -0.072934044
## [214,] -0.55253516 0.1317703109 1.357970154 -0.0482997296 -1.122890373
## [215,] -2.25537988 0.3966374672 -1.863477432 -0.5714483991 0.490153227
## [216,] 4.49735305 -0.0156151423 0.014696106 0.2756314037 -0.311535089
## [217,] 1.59037352 1.6686833229 1.517195751 1.3497730300 -2.136333592
## [218,] -0.08318615 -0.7136260777 -0.610225085 0.3688413513 0.266397344
## [219,] 3.34691985 -0.4693710460 -0.371903087 0.6777054911 -0.013967562
## [220,] 2.06949441 -0.9593281105 -0.023534542 -0.2591906364 -0.838249168
## [221,] -0.32421990 1.1269616676 2.415757623 0.8093924812 0.345579729
## [222,] -0.90096638 0.1207361119 -0.078038877 0.0284795012 -0.052111150
## [223,] -11.65974984 -0.6867589938 -0.034482756 -0.3765583860 0.269196021
## [224,] 4.49314035 -0.3672834847 0.099586547 0.2788287928 -0.054958539
## [225,] -1.74759019 -1.1654486536 -0.156491864 -0.6384146576 -0.065535972
## [226,] 3.40010141 0.4083187204 -1.433156353 0.8014421316 -0.238667974
## [227,] -0.37617650 -0.1808832613 -0.176371529 -0.0584366670 -0.577811212
## [228,] 3.92086761 0.6213718507 -1.143295141 -0.3509232662 0.366204342
## [229,] 0.77969312 -0.0419336617 -0.622474613 1.9845022885 -1.422500853
## [230,] 0.17211480 -0.5870770143 1.407651052 -0.0232714615 0.169433840
## [231,] 1.52567926 1.5391010249 -0.593969535 -0.4383816795 0.702080519
## [232,] -0.40276978 -0.4716145310 -1.542645733 0.2403639299 0.408749107
## [233,] 0.18211922 1.6721043896 0.248456062 0.5883349445 0.900531066
## [234,] -3.84649292 -1.0565153361 0.047459312 -0.6518116630 1.040937599
## [235,] -1.71626667 0.3929191195 0.009364952 -0.3781866118 0.603820910
## [236,] 1.23875858 0.0577743583 0.430703755 -0.6757851527 -0.657188043
## [237,] -0.91391691 0.0413345253 -0.119878897 0.0815873780 0.146092782
## [238,] 3.44125422 -1.7028620479 0.468343746 -0.3764278969 -0.146160956
## [239,] -2.48244807 1.5000569029 0.328013082 3.0456598995 0.010582060
## [240,] 3.69631015 0.8641003905 1.197108650 -1.3424832176 0.302363691
## [241,] 4.20564432 0.3733647439 0.315563291 0.2321487554 -0.277922528
## [242,] 3.16948345 0.3523927575 0.908984521 0.8560189005 -1.037759290
## [243,] -5.78535376 0.5615527864 -0.450753587 -0.4245140096 0.146844710
## [244,] 4.19944115 -0.4014038298 -0.278213131 -0.0705713154 -0.064394153
## [245,] -5.13893497 1.5227380246 0.945728521 0.6813143320 -2.184958290
## [246,] 0.42677245 0.2850142333 -0.442502456 -0.3579962438 -1.108950136
## [247,] 0.45089375 -0.3039167647 -0.325438328 -0.1853961274 -0.651847379
## [248,] -0.65339868 0.3548101418 -0.770145359 0.0871442707 -1.407382420
## [249,] 1.00120756 0.8700376983 0.453874030 -0.1616459749 -1.098944426
## [250,] 2.66890032 1.3184259388 0.865867181 -0.6625312940 0.218852326
## [251,] -9.84309397 0.4243091927 -1.349856436 0.9193586039 -0.336634981
## [252,] -3.02893600 1.9938240304 0.038774106 -0.2663439852 -0.655745601
## [253,] 4.22737290 0.8211981785 0.753913866 -0.6967405000 0.170923624
## [254,] -5.49062830 -0.3175717348 0.027066261 -0.7309133965 0.730728708
## [255,] 0.97288797 1.5539934332 1.012102437 1.4646316488 -0.125832480
## [256,] -13.83869857 -2.6346265994 2.673092898 0.8710310980 -0.223609514
## [257,] -13.05093203 -0.8063689433 0.617954584 1.2943496220 1.284488174
## [258,] -11.69353217 -0.7504912376 1.004592385 3.1621590690 0.812647306
## [259,] 0.43760998 -0.1397554890 -0.954424253 1.1373323437 1.983324984
## [260,] -3.63505849 -0.1817615119 -0.535997070 -0.2683783548 1.560453578
## [261,] 3.38527790 -1.2526855474 0.066105367 0.1378950432 -0.287604825
## [262,] -3.81717057 -0.2563876186 1.349624782 0.2099962772 -1.182709243
## [263,] 1.76892297 0.2703371324 -0.309211639 -0.6961662513 -0.049883407
## [264,] -1.97514768 -0.8265189950 0.389688426 -1.7048220717 -0.444383724
## [265,] -0.91189718 -0.4932988549 -0.026277952 -0.0856682739 0.661088083
## [266,] -3.04280520 -1.9820504906 0.535316891 -0.0879738226 -0.149919435
## [267,] -1.72873571 -1.2917118478 0.007495038 -0.7456923461 0.431506658
## [268,] -3.33634124 -0.7143521018 0.067469586 1.2159110966 0.071377557
## [269,] -3.90108558 -0.2756418398 -1.111411143 -0.2105640779 -1.243628682
## [270,] 2.55479766 -0.6427690224 -1.840223592 -0.2007452129 0.274834821
## [271,] 1.01233451 -0.3618036473 -0.222549026 0.8531284963 -0.275280998
## [272,] 4.22737290 0.8211981785 0.753913866 -0.6967405000 0.170923624
## [273,] -8.95807240 -0.8705006998 0.470659186 0.1432649335 -1.092101835
## [274,] -0.36636861 0.0849195311 -0.222034238 -0.3357868055 0.095588807
## [275,] 1.26456593 -1.3186135398 0.781110841 -0.0009088386 0.685412538
## [276,] 0.99822904 0.3866490602 -0.566479791 -0.5352169295 -1.134782723
## [277,] -0.59740000 -0.4144448694 0.881195680 0.8859247327 1.040062773
## [278,] 2.80537567 -0.1527218996 -2.169985536 -0.7785060785 0.556242681
## [279,] -7.37883252 0.3674355056 0.139408251 1.0562445051 0.186096982
## [280,] -2.23513112 0.7487002196 0.447221901 -0.4479225267 -0.248411818
## [281,] 3.69768761 1.0700143095 0.879037246 -0.2327953460 -0.400047413
## [282,] -0.90517908 -0.2309322305 0.006851565 0.0316768903 0.204465399
## [283,] 3.13253577 0.9895154487 -1.256572551 0.0340955012 0.243371135
## [284,] 3.98599017 0.4154446935 0.675368192 0.0302376505 0.070997238
## [285,] 3.17765147 0.0232710600 1.268807401 -0.2045950871 0.087020630
## [286,] 2.87854037 0.8467524869 0.620852808 0.5868344401 -1.170937122
## [287,] 4.20574241 -0.5585496622 -0.143188137 -0.1927403708 -0.172367410
## [288,] -1.67572496 -0.3369981468 0.369513623 0.5033125031 0.478653788
## [289,] -1.40640950 0.5942598295 0.626367970 -0.1063606056 0.038415952
## [290,] 0.98623109 1.3032276706 0.209700258 0.8228848992 0.418008004
## [291,] 1.56277919 -0.1215698616 0.599205159 -0.4315000564 0.285913615
## [292,] 3.46653393 0.0828459414 0.862031581 -0.2102097461 -0.709667893
## [293,] 3.70694600 -1.0294390869 0.433000881 0.4063805848 0.339376534
## [294,] 1.82324366 0.1645614674 0.240529622 0.2027751063 -1.269837394
## [295,] 3.90850526 0.0472105623 -0.435351547 -0.7744033199 0.058005101
## [296,] 1.54764555 0.8307039308 -0.042255033 -0.0596798146 -0.156865417
## [297,] -1.73334918 -1.1385809133 -0.230141350 -1.1405264372 -0.414991809
## [298,] -1.16680397 -0.6041038115 0.185029581 0.2938767661 0.839379718
## [299,] 0.70152976 -0.4666935393 -0.992448021 0.1155357133 -0.446090239
## [300,] 1.25961220 1.0027420222 0.385679170 0.2896727610 -0.084080142
## [301,] 1.33012644 -2.1362452473 1.525405562 -0.3704765153 -0.126453742
## [302,] 3.95201930 -0.3228886973 0.110571761 0.3954927369 -0.762359440
## [303,] 3.15237613 0.3802468071 -1.008124949 0.0677711568 -0.282235382
## [304,] 0.98129981 -1.2393725351 -0.957986389 0.5163956755 -0.757041336
## [305,] 2.59789452 0.5128359318 -0.961926011 1.1133225124 0.155663613
## [306,] -1.15927933 -0.2556585744 0.230466788 0.6275748895 0.630837696
## [307,] 1.01804435 -0.6272390897 1.423339459 0.4709961068 0.045220762
## [308,] -1.68124916 -0.3651314785 0.276197284 0.0570234982 -0.362479423
## [309,] -16.29784553 0.0813359013 -0.438799727 -0.7268138508 -0.651605036
## [310,] 0.45487038 1.3771824086 -0.157056963 0.7866247392 0.739237330
## [311,] -0.91391691 0.0413345253 -0.119878897 0.0815873780 0.146092782
## [312,] 2.55800969 -0.5211078218 -1.065134723 0.8744161472 0.676708482
## [313,] 3.67232695 -0.3006420772 0.314083495 1.4267623147 -0.375548518
## [314,] 3.97616628 -0.3050833580 -0.488437110 0.3489558926 -0.112377771
## [315,] -1.95916322 1.3242126321 0.902306405 -0.1562910336 -0.560790345
## [316,] 2.37466965 1.7303667865 -1.144194987 -1.0673716645 -1.233978654
## [317,] 4.48873537 -0.5347671235 -0.016446359 -0.2321139404 -0.097587111
## [318,] -1.70076147 -0.2651629249 -0.197543339 -0.3751029153 -0.128419997
## [319,] 2.62925524 0.6813384032 -0.116578266 0.5036541130 0.785496998
## [320,] 0.16288665 -0.5913391682 0.741758662 0.0279788064 0.334849331
## [321,] 2.57527355 0.6900000179 0.291926734 -0.0072542924 -0.401920001
## [322,] 4.22633220 0.3477674762 -1.673460296 -0.0704932501 0.039570080
## [323,] -6.31872962 0.5095720128 0.075344587 -0.6766591583 0.777536033
## [324,] -0.39796514 -0.1888334346 -0.306257679 -0.2915098822 0.600620005
## [325,] -8.69127226 0.2342912433 0.157679450 -0.7887419903 0.571396060
## [326,] -0.35162826 -0.0344404706 -0.049780598 -0.5359518234 0.851285058
## [327,] 3.42123559 -1.3468333308 0.495864329 0.4940015111 0.187397561
## [328,] 2.02191202 1.0912485604 0.092791888 0.1474875091 -0.071178714
## [329,] 4.47556442 -0.0235653156 -0.115190045 0.0425581884 0.866896128
## [330,] 3.98555598 0.8277972277 -0.279228081 -0.3318187241 -0.386929826
## [331,] 3.18688482 -0.3697629972 0.035737559 -0.2541372975 0.149319403
## [332,] 4.49831734 0.4139287586 0.393686018 -0.3987484348 -0.072934044
## [333,] -0.10134345 0.9256721704 -0.243869122 0.1804560210 0.040258317
## [334,] 3.17595794 0.8016577197 1.016563871 0.1675339374 -0.013746390
## [335,] -0.12463189 -2.2068544311 0.004062516 -2.4291064663 -0.260560106
## [336,] -0.90437254 -0.1448536179 0.019159255 0.2480298495 0.452546062
## [337,] -0.36017153 -0.1674119550 0.069618494 -0.2930578155 0.241061470
## [338,] 4.23705660 0.6730124544 -0.393337482 -0.4918134158 -0.060564248
## [339,] -6.80508480 -0.5550746002 0.494895949 -0.9832655529 0.566108811
## [340,] 1.23481506 0.5122745745 -0.499623022 2.2976949153 -0.304984495
## [341,] 3.96995252 0.9335190700 0.824288507 -0.6472994547 0.136563271
## [342,] -1.16761051 -0.6901824241 0.172721891 0.0775238069 0.591299055
## [343,] 3.93541994 -0.8275980959 0.107985468 0.2826106027 -0.006605634
## [344,] 4.49394688 -0.2812048721 0.111894237 0.4951817520 0.193122123
## [345,] 4.23588591 -0.0453214350 0.559556344 -0.3529015182 0.313899612
## [346,] -1.42717379 0.5759702957 0.567007308 0.1481488114 -0.171829155
## [347,] 0.95190636 -1.0326908516 -1.003172531 -0.3185883046 1.150959055
## [348,] 2.61847029 1.6163798001 0.121882916 -0.3003084964 0.668936870
## [349,] 1.00039895 1.9554007946 -0.352813249 0.5365062076 0.173738054
## [350,] -1.72580909 -0.0711667102 -0.798137955 -0.4883333661 0.098817311
## [351,] -3.57879886 3.2866475329 0.928920457 -3.7827761021 2.751383528
## [352,] 2.27337241 -0.1252777529 -0.568162810 -0.0146191268 -0.599943979
## [353,] 4.48642225 -0.6296501091 0.066457030 0.1614836286 0.401664145
## [354,] 3.11697595 1.4901605724 -0.261846958 -0.8280945795 0.998282915
## [355,] -3.34108428 0.3390002778 -1.449198696 0.6712983276 0.595646289
## [356,] 4.20151838 -0.8609657404 0.141628168 0.4654575141 0.497765833
## [357,] 2.65214942 1.1662102644 2.173699425 -0.6197571783 0.661878160
## [358,] 0.99930031 1.8889074688 1.865827669 0.1766511918 -0.290334296
## [359,] -0.37617650 -0.1808832613 -0.176371529 -0.0584366670 -0.577811212
## [360,] -5.26152817 -0.1696104876 -0.928076151 0.1629496607 -0.617456397
## [361,] -14.94603387 -1.4415991390 0.127759553 0.3272097976 -1.767279996
## [362,] -0.38820502 -0.2931323572 0.594875222 -0.0384502095 0.261884632
## [363,] -9.87464896 -0.3310163375 -1.392760732 0.9818778048 1.911901275
## [364,] -3.84547910 1.1777087023 1.472201364 0.9889895339 -0.208536979
## [365,] 1.25160903 -0.0564544108 -0.638400195 0.8781170788 -0.068687207
## [366,] -15.00434764 -2.4861889608 -2.638553364 1.4123257199 -0.876026774
## [367,] 1.80015216 -2.1008746978 0.712686573 0.7779538036 -0.767288438
## [368,] 1.22674142 -0.1915043590 -0.578474725 -0.5511528990 0.164289256
## [369,] 0.94818097 -0.6493220205 -1.011899388 0.5532662174 0.059729082
## [370,] 2.53213858 -0.3315776966 -1.563462328 -0.8734134269 0.599781489
## [371,] 2.29855512 -1.1612037623 -0.216017155 0.7204106067 -0.324320563
## [372,] 4.22419644 -0.3662411168 -0.212135996 -0.1717897565 -0.100282709
## [373,] -3.54595702 0.4974397533 -0.048159465 -0.8269341639 0.223688969
## [374,] -4.93310916 0.9003237765 -0.176288571 -0.1230796538 1.340290422
## [375,] 3.67245410 0.1786806609 -1.219946074 0.5397164076 0.172476664
## [376,] -0.38820502 -0.2931323572 0.594875222 -0.0384502095 0.261884632
## [377,] -4.69884857 1.1683343399 -0.700593399 -0.7896390498 0.952972179
## [378,] 4.47556442 -0.0235653156 -0.115190045 0.0425581884 0.866896128
## [379,] 3.12609926 1.0097209267 -0.856647238 0.5740531518 -0.363217019
## [380,] -3.80655202 1.7746208704 1.666004505 -0.4697636677 1.384351932
## [381,] 3.93842675 -0.1804562619 -0.319434101 0.0739199697 -0.820305240
## [382,] -2.48033458 0.3700799205 0.793818759 -0.2734771212 0.922369260
## [383,] -0.35594421 0.7164189511 -0.236176951 0.0722562680 -0.035795239
## [384,] -2.79501417 -0.3818274232 -0.454456844 -0.0478299389 1.098560513
## [385,] -0.09015179 0.7814995694 0.001081111 0.7428479724 0.722921419
## [386,] 2.91150678 0.8770409063 1.088833252 0.3806365060 -0.141908035
## [387,] -1.44485081 1.5093911496 -1.091878558 -0.7643469662 0.250972433
## [388,] -1.72196873 -0.2179295146 0.059260186 -0.3458273398 0.052087163
## [389,] 2.02296870 0.3906137250 -0.088607794 0.1758870453 0.351898027
## [390,] -1.75199517 -1.3329322924 -0.272524771 -1.1493573908 -0.108164544
## [391,] 0.93896922 -0.1631817577 0.165769593 0.1859453937 -0.011339702
## [392,] 0.96535706 -0.8361928695 -0.503014423 0.6505616708 -0.389438678
## [393,] 0.77949336 0.2921210640 0.741459780 -0.0906321175 -0.649414702
## [394,] -0.04838049 1.1319505272 0.002227156 1.0295724407 0.126117795
## [395,] 4.49831734 0.4139287586 0.393686018 -0.3987484348 -0.072934044
## [396,] 4.22737290 0.8211981785 0.753913866 -0.6967405000 0.170923624
## [397,] -8.79631829 0.6874609507 -1.717475197 -0.8743503788 -1.154584836
## [398,] -4.12257071 0.3051164773 0.791806376 -0.9042156422 -0.959342779
## [399,] 0.20573934 0.6783460499 0.139401306 -1.2941698827 -0.812181408
## [400,] -0.90000209 0.5502800128 0.300951036 -0.6459003373 0.186489895
## Comp.6 Comp.7 Comp.8 Comp.9 Comp.10
## [1,] 0.667109619 0.526320713 0.404115333 0.6807835391 0.533254450
## [2,] 1.254106008 -0.503916370 -0.301377300 0.4240209774 -1.181521474
## [3,] -0.033710227 0.180677335 1.078066990 0.0008515598 -0.418470310
## [4,] 0.415839125 -0.548082867 -0.692110287 -0.6960119283 0.435474041
## [5,] 0.714551627 0.521977568 -0.711176519 -0.4646774298 0.752648703
## [6,] -0.635352811 -0.384679007 -0.547445265 -0.5644997231 0.199728577
## [7,] 0.052826372 0.303891006 -0.484871711 0.7434337072 0.202510551
## [8,] 0.211228055 0.027368926 1.114826601 0.5086119773 0.112060287
## [9,] -0.023949043 0.745900629 -1.768346596 -1.6298289970 -0.863322525
## [10,] 0.462918958 0.041324130 0.430935579 0.9785419003 -0.251480723
## [11,] -0.400324155 0.592179420 0.118271560 1.0303639066 -0.431351565
## [12,] 1.098757606 -0.601531218 0.476443228 0.2162142924 0.538556049
## [13,] 0.139026719 0.852714662 0.012062450 1.2661454189 0.257472798
## [14,] 0.005902333 0.332293350 -0.551003561 -0.6297546915 0.292219810
## [15,] 0.908680955 -0.361926275 0.122852675 0.1161909118 0.632711909
## [16,] -0.360364753 -0.061457730 0.296240707 0.5450931997 -0.094920703
## [17,] 0.299832071 1.686982842 1.509203995 1.8696402386 0.423108506
## [18,] -0.527950830 0.096525105 0.149383161 -0.2638157510 0.222722346
## [19,] -0.616261174 -0.222140441 0.719822526 -0.2656983579 0.400746277
## [20,] 0.483513799 0.369537514 -0.156579073 -0.3508175921 -0.092254518
## [21,] 0.221347363 0.203792373 0.153902064 -0.4088516121 -0.476039942
## [22,] 0.375449771 0.032987898 0.046214701 -0.4140837912 -0.251836468
## [23,] -0.957590165 0.259531527 0.027626091 -0.1398302789 0.143350796
## [24,] 0.102848662 0.261600512 -0.580873905 0.0511166874 -0.107835471
## [25,] -0.276687486 0.670282514 0.816292571 1.1590757593 0.091315464
## [26,] -0.074143318 0.074897270 0.718965434 0.8796944131 -0.750386404
## [27,] 0.404265333 1.851340388 -1.395424154 0.3507683708 -0.512760104
## [28,] -0.361180198 -1.257737561 -0.297918581 0.4653153135 0.163639509
## [29,] 0.466561726 -0.114325912 -0.018676525 -1.6025928806 -0.328959065
## [30,] -0.894954781 -0.215861538 0.052410537 -0.7667596968 0.494819771
## [31,] 0.217617567 -1.229234127 0.540618028 0.4164286101 -0.871320793
## [32,] 0.320622974 -1.005727612 -0.156748065 0.3698579603 0.467642092
## [33,] -0.234305300 -0.742178107 -0.499658316 -0.1769298436 0.589531824
## [34,] -0.213854914 -0.564332699 -1.262541944 -0.0778989475 1.517550148
## [35,] -0.743183080 0.265703669 1.019204364 0.9205356668 -0.871037576
## [36,] 0.277389538 0.917343194 -0.087514117 -0.4572480935 -0.565174910
## [37,] 0.110661978 -0.232594118 0.503517829 0.4787936367 0.502332594
## [38,] -0.403083557 -0.087880379 -0.967669779 0.3775993251 -0.915733755
## [39,] 0.577555350 0.509692134 0.413217638 -1.1755609951 -0.146149773
## [40,] 0.615093965 -0.209333968 0.431739030 0.1565562790 -0.234643138
## [41,] -0.816160448 0.086870542 -0.964034542 -0.8128253781 -0.044049781
## [42,] 0.797370034 -1.183647564 -0.969342449 0.1010128250 -0.434991695
## [43,] -0.029343061 0.752194833 -0.218073779 1.3072012778 -0.273408197
## [44,] -0.907237630 -0.006086796 0.485929054 0.6645328842 -0.067863680
## [45,] 0.491513024 0.178017277 0.369000301 1.2946584762 -0.358448471
## [46,] -0.762718786 -0.333514822 -0.781477145 0.3673208123 0.200598762
## [47,] 0.542244089 -1.176584218 0.490295395 -0.4195887700 -0.251879593
## [48,] -0.443086714 -0.481861714 -0.709001594 0.1540386790 -0.763875222
## [49,] -0.364463975 -0.027679990 -0.352345858 -0.0242422058 0.138043047
## [50,] -0.017953580 -0.531879555 -0.008992956 -0.3071612526 0.225625496
## [51,] -0.100606801 0.177812636 0.482659517 -0.3760679078 0.686201417
## [52,] -0.866174989 -1.084240652 -0.238748205 -0.6988876963 0.045151336
## [53,] 0.112964963 -0.442042615 0.016444321 0.0869655344 -0.657887883
## [54,] -0.484121095 -0.750766900 0.167771071 -0.0864828048 -0.402017785
## [55,] -1.249157102 -0.430155466 -0.587473539 0.2542512877 -0.363659996
## [56,] 2.372348681 -0.357787018 -0.885076250 -0.0494022576 -1.284758438
## [57,] 0.173559681 0.981374491 -0.058203101 -0.3080344296 1.668914602
## [58,] 0.769196373 -0.380138444 0.324051666 0.1513241000 -0.010439664
## [59,] -0.734618059 -0.031790731 0.255269494 -0.1553520312 -0.037351891
## [60,] 0.104755071 0.943699691 -0.381294024 0.8351921163 -0.338295743
## [61,] 0.244246722 -0.188845987 0.699234636 0.1936143432 0.273236298
## [62,] 0.375449771 0.032987898 0.046214701 -0.4140837912 -0.251836468
## [63,] 1.017370701 -0.506367664 0.216211223 -0.8908445076 0.546638011
## [64,] -0.701111209 0.469630377 0.735023370 -0.1114939723 0.443311493
## [65,] -0.734618059 -0.031790731 0.255269494 -0.1553520312 -0.037351891
## [66,] -0.803487758 0.088727052 -0.080061273 -0.1450624579 0.367554270
## [67,] -0.474478230 -0.565608241 -0.239627647 -0.5132545803 0.463305273
## [68,] -0.618551446 0.070646174 -0.538189310 0.8392607134 -0.173077460
## [69,] 0.130804448 -0.621251976 -0.035827376 -0.1993652092 -0.083883611
## [70,] 0.647607643 0.220827303 0.085794596 -0.8513294776 -0.025540480
## [71,] -0.956395831 0.326892979 -0.413575756 -1.2487874739 0.450901983
## [72,] -0.964862425 0.039329363 0.003752417 0.0829927427 0.653597313
## [73,] -0.506606365 -0.478182157 -0.136153573 0.0216972215 0.418435029
## [74,] -1.256064693 -0.726284799 0.532705931 0.7498600065 -0.303097965
## [75,] -0.726652755 -0.381162373 -0.190436917 -0.3590770648 -0.130257360
## [76,] -0.667193552 0.410363996 0.332994874 -1.2987701768 -0.130646693
## [77,] 0.049564694 -0.863272943 0.684666508 0.9115792323 -0.077733212
## [78,] -0.133218188 1.010449365 0.691167614 0.0394118739 -2.252342754
## [79,] 0.069135228 0.405249391 -0.001943589 -0.0903674118 -0.033147752
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## [285,] 0.703246341 -0.508451005 0.113939276 0.5493536567 -0.420501075
## [286,] -0.174574331 0.578324793 0.118828486 0.0032205821 0.980243819
## [287,] -0.440311936 -0.127234084 0.081798725 -0.3794377405 -0.567605818
## [288,] 0.525036881 -0.417573969 0.468417197 0.3653118367 -0.148755883
## [289,] 0.641419133 0.064877739 0.463304747 -0.2982807473 0.497685646
## [290,] 0.010753507 -0.431643394 -1.056182429 -1.0567846352 0.355460210
## [291,] -0.261959964 -0.189354226 -1.130779050 0.5502697955 0.666750022
## [292,] 0.128751015 0.932042521 -0.056341501 0.2080745642 0.517215588
## [293,] 0.525562470 0.287324296 0.422401437 0.1893722020 -0.602213107
## [294,] 0.345542284 0.986877800 0.752002848 0.2364086573 -0.406502626
## [295,] -0.057458603 -0.674212912 -0.054683695 -0.1881766444 -0.944616900
## [296,] 1.074266970 0.600287755 -0.613001466 -0.9506726376 -0.022618483
## [297,] -0.464648280 0.159564186 0.007072837 -0.3429256151 -0.432679855
## [298,] 0.769196373 -0.380138444 0.324051666 0.1513241000 -0.010439664
## [299,] 0.101708590 -0.945560962 0.377755067 0.8349898699 -1.381673432
## [300,] -0.184376032 0.650640556 -0.944382217 -0.5469040204 0.512745424
## [301,] 1.163260719 1.113672115 -0.163832454 0.1715893228 -0.520182123
## [302,] -0.635807641 0.155588382 -0.034090342 0.0560617609 -0.412582819
## [303,] -1.417963344 0.026685316 -0.106674416 0.5689910717 0.391094941
## [304,] 0.409539011 -0.218675446 0.004451216 0.7649434868 -0.339085285
## [305,] -1.151041062 0.179795028 -0.445511336 0.9418962655 0.870472439
## [306,] 0.816477839 0.288572925 0.137398838 -0.6319742975 -0.586972216
## [307,] -0.518884957 0.028635500 0.116396849 -0.5245812280 0.790714958
## [308,] -0.144490606 0.679950515 -0.497305221 0.3150945419 0.277939992
## [309,] 1.872547848 -1.357658919 -0.297847854 -0.3141514757 0.187399725
## [310,] 0.237995723 -0.346181541 0.016536785 0.5615972895 0.217078297
## [311,] -0.107485076 -0.035221292 -0.018330549 -0.2743453297 -0.141944472
## [312,] 1.485362144 0.228787562 -0.255557205 -0.6311715183 0.543942709
## [313,] -0.093565672 0.030689917 0.006160668 -0.9620070022 -0.448435985
## [314,] 0.494461086 0.862892226 -1.598521188 0.4409821259 0.586826018
## [315,] -0.133082650 -0.693018444 -0.216340133 0.2355392808 0.100566849
## [316,] 0.931754183 -0.429719359 -0.018837879 0.0978587503 0.893608378
## [317,] -0.267305421 0.257489772 0.026741447 -0.0799931380 -0.283230409
## [318,] -0.318926424 0.346370069 -0.034257646 0.1756053353 -0.374477522
## [319,] 0.214791548 0.677133495 -0.307701088 0.2569581953 1.066442791
## [320,] -0.182562816 -0.301785306 0.295712527 0.0633766656 -0.212691932
## [321,] -1.222324050 0.346958310 0.569077489 -0.3704744649 0.985988809
## [322,] 0.520627463 -0.043571173 -1.152512776 0.0712585450 0.209885682
## [323,] 0.123552616 -0.793811371 -0.680285753 -0.0215508409 -0.295399381
## [324,] 0.095796370 -0.173199441 -0.128783126 -0.4242484854 -0.202743762
## [325,] 0.059897008 -0.199505364 0.914921070 0.8888312335 0.337460531
## [326,] 0.351238833 0.463366119 0.047995803 -0.1250230900 -0.152575916
## [327,] 0.310117440 0.415825272 -0.282504189 -0.0315308774 0.166046645
## [328,] 0.117420783 -1.571826562 1.007680991 0.4390499492 0.465999496
## [329,] -0.957590165 0.259531527 0.027626091 -0.1398302789 0.143350796
## [330,] 0.416442741 -0.015792072 -0.127807378 0.0559517634 0.784012858
## [331,] 0.542242955 -0.146046213 -1.273664084 1.2748711053 0.092869876
## [332,] 0.207663324 0.029494877 0.395994284 -0.3032132626 0.322574877
## [333,] -0.321478493 0.277932806 -0.281335359 -0.5871920052 -0.155755160
## [334,] 0.752288954 0.589135328 -0.149597006 0.3604180390 -0.112556305
## [335,] -1.219925158 -0.042400878 1.268948478 -0.9346984725 0.100125625
## [336,] 0.375449771 0.032987898 0.046214701 -0.4140837912 -0.251836468
## [337,] -0.123528168 -0.521172938 -0.378821154 -0.4193685660 0.142603258
## [338,] 0.577817408 0.033605617 -0.211621068 -0.1721034372 0.497969815
## [339,] 2.851648132 1.436063010 0.429117572 0.1526805733 -0.256099835
## [340,] -1.107230522 0.208543715 -0.609256130 -0.3604178700 0.847055296
## [341,] 0.159907003 -0.358952725 -0.071082830 -0.1374061035 -0.704686520
## [342,] 0.500162158 -0.180436401 -0.293944352 0.6196313095 0.600863722
## [343,] 0.103244466 0.105497953 0.169843366 -1.1032009835 -0.465150380
## [344,] 0.221347363 0.203792373 0.153902064 -0.4088516121 -0.476039942
## [345,] 0.601409926 -0.383631465 0.673831249 0.2621946286 0.563971681
## [346,] 0.476198359 -0.175001800 0.292020381 -0.3121290042 0.307533947
## [347,] 0.294850625 0.704408497 -0.284927265 0.1249583038 -0.738316596
## [348,] 0.362721770 0.860763916 1.884525694 -0.1623572326 0.743650115
## [349,] -0.021037354 0.694791320 -0.218274334 0.1020152714 -0.140765539
## [350,] 0.491607280 -0.043728600 -0.565737276 -0.8193812874 0.061606314
## [351,] -2.400029963 0.385320297 0.446389324 0.1399745061 -0.157811062
## [352,] -0.339236895 -0.154473378 -1.071051114 -0.8046662084 -0.460665341
## [353,] 0.174065897 -0.464918995 0.340554893 0.3744467854 0.100492610
## [354,] -0.149418169 0.189361959 -0.547677674 -0.2491909453 0.404133340
## [355,] -0.050468212 1.243560914 -0.204763577 0.4574090965 -0.065263645
## [356,] 0.227655082 -0.536120061 0.253645286 -0.3147635035 0.257448977
## [357,] 1.432053550 -0.968177193 0.039937919 -0.1693538769 -0.070489859
## [358,] 0.840881418 -1.066200551 -0.607827837 -1.1714028213 -0.243612782
## [359,] 0.672331164 -0.533921311 -0.009877600 -0.2473241117 -0.200955709
## [360,] 0.005342941 -0.372886976 -0.728678285 -0.7057120251 -0.681628109
## [361,] 1.479045013 -1.159054467 0.231835510 -0.3920635151 -0.078083372
## [362,] -0.435732380 -0.226707870 0.562645916 -0.3273031102 -0.092095657
## [363,] -1.031429872 -1.245437684 1.955907721 -0.9742781224 -0.553466149
## [364,] 0.381897173 -0.027703824 -0.489192745 -0.5637539676 -0.024530307
## [365,] -0.947679930 0.441824905 -0.128704028 0.2952929104 0.640823406
## [366,] 0.520458752 -0.800701980 -0.242419016 -0.3371442513 0.002766784
## [367,] -0.181076613 -0.409608086 -0.176623019 -0.0925333657 0.180883148
## [368,] -0.273309469 -0.693843191 -0.277424863 -0.1717540256 0.943486322
## [369,] -0.491708219 0.367068633 -0.375746961 -0.0755487525 0.750996240
## [370,] -0.897891733 -0.715390059 -0.300894514 -1.0113813620 0.091795220
## [371,] -0.310575468 -0.626191698 1.097233900 0.3710007962 -0.618780033
## [372,] -0.438170494 0.386301092 0.400862370 0.0605953254 -0.446748783
## [373,] -0.068735533 1.380242076 -0.345767619 -0.2286263272 0.840462711
## [374,] 0.859371564 0.638219091 -0.083540142 -0.1302582813 0.243573546
## [375,] 0.848480347 0.200361813 -0.119697979 -0.5278449107 -0.580632523
## [376,] -0.435732380 -0.226707870 0.562645916 -0.3273031102 -0.092095657
## [377,] -0.032518006 -0.047990685 0.167847491 -0.5371076305 -0.316842591
## [378,] -0.957590165 0.259531527 0.027626091 -0.1398302789 0.143350796
## [379,] -0.295915537 -0.122605941 -0.425385527 0.6198419860 -0.920586152
## [380,] -1.346039367 0.118011934 -0.637841422 0.3826180911 -1.260005796
## [381,] -0.888833300 -0.239351917 0.452219082 0.1586952188 -0.354598028
## [382,] -0.361613395 0.069599990 0.409762424 -0.2560752896 0.331702190
## [383,] -0.232917432 -0.510076178 0.161730341 0.6101042369 0.354712172
## [384,] -0.172695962 0.506393351 0.420581001 1.0469420430 0.490428534
## [385,] 0.243960191 -0.108100182 -0.106349303 -0.0166450316 0.231708448
## [386,] 0.710382176 0.776511166 -0.122958119 0.2822659942 -0.337800058
## [387,] 0.509946675 1.179967677 0.224936807 -0.6713387513 -0.063180962
## [388,] 0.038668371 -0.035877176 0.102429916 -0.9645585768 -0.538147885
## [389,] -0.537139442 0.040644658 0.871096909 -1.6960837767 0.163692713
## [390,] -0.557455026 -0.655658172 -0.062591897 -0.3705994433 -0.090989070
## [391,] 0.421487103 -1.199469974 1.183899958 -0.4366055695 -1.080349759
## [392,] -1.074833499 1.187121110 0.629374929 -0.3232393553 -0.594631077
## [393,] 0.399752835 -0.478975321 -0.522725090 0.5650711458 -0.241521970
## [394,] -0.136704768 -0.260480297 0.060829002 1.4039729763 -0.537830485
## [395,] 0.207663324 0.029494877 0.395994284 -0.3032132626 0.322574877
## [396,] 0.242691829 -0.370914889 -0.131634670 -0.1233386396 -0.280327258
## [397,] 0.574456612 -1.126724880 -0.283547823 -0.3385882344 -1.099831739
## [398,] -0.113321674 0.410878702 0.008133568 0.0960652786 -0.386959856
## [399,] 1.222706311 0.059037968 0.426695324 0.5136119383 0.214363716
## [400,] 0.361765732 -0.141309599 0.288306920 -0.3084454416 0.546778352
## Comp.11 Comp.12 Comp.13 Comp.14 Comp.15
## [1,] 0.844015827 0.245517419 0.9092739036 0.2167274245 1.899094e-02
## [2,] 1.262907400 0.791605861 0.0904986788 -0.0089278490 4.108764e-01
## [3,] 0.561973498 -0.242901809 0.2495601352 0.1854113602 7.628477e-01
## [4,] -0.522768714 0.695563064 -0.3272704290 0.3901181170 1.333014e-01
## [5,] 0.266553172 0.564556863 -0.3628601641 -0.2790047381 -7.162802e-01
## [6,] 0.598506786 0.250149002 -0.7916786424 -0.4032533591 -1.203803e+00
## [7,] -0.571308079 0.013814411 0.4834400356 -0.0186145206 4.576858e-01
## [8,] 0.530132824 0.097115453 0.8329136151 0.1824113867 -2.311536e-01
## [9,] -0.961804570 0.417612972 0.9088162622 -0.1012847109 1.197240e-01
## [10,] -0.696266129 -0.184094292 -0.2496920353 0.1864697767 -5.518810e-01
## [11,] -0.393784280 -0.201746519 -0.6919664184 -0.2689115753 -3.816938e-01
## [12,] -0.052445097 0.391709426 0.1725260237 0.4700475975 -5.697344e-01
## [13,] 0.385458199 -0.656716778 0.0604467544 2.0119684399 -2.255529e-01
## [14,] 0.826386681 0.233910690 0.2923974867 0.3797491200 -2.205377e-02
## [15,] -1.059257373 0.016467788 0.1545130550 -0.2450631668 2.974510e-01
## [16,] 0.599895823 0.294938672 0.2494369187 -0.2917946150 -1.818078e-01
## [17,] 0.196648774 -0.108089021 0.8116974079 -1.4248554888 -3.819083e-01
## [18,] -0.214891386 0.018556732 0.1961008720 0.1963214733 2.650717e-02
## [19,] -0.399328038 -0.205695252 0.5975445572 0.5722908388 -2.062200e-01
## [20,] 0.259135713 -0.056327219 -0.1549843846 0.0656184373 -2.995860e-01
## [21,] -0.404298092 -0.023682071 -0.0646319170 -0.2273203449 8.514548e-02
## [22,] -0.455221135 -0.113230629 -0.2016913287 -0.2836648104 3.048413e-02
## [23,] -0.101042607 0.109701436 -0.0271824606 0.0778367403 -5.403869e-02
## [24,] 0.147047040 0.221374804 0.2523038234 -0.0678234928 2.456085e-01
## [25,] 0.578125593 -0.269943052 -0.0116042720 0.8229701576 -5.214352e-01
## [26,] -0.282230387 -0.024692622 -0.8262913292 -0.1255055250 -4.899966e-01
## [27,] 0.841585743 0.987143942 0.4168961262 -1.4279278666 7.226543e-02
## [28,] 0.036546812 -1.076162064 -0.4026622781 0.8108551421 2.131511e-01
## [29,] 0.442673973 0.414958243 0.7304670071 0.0568401943 8.544162e-01
## [30,] -0.959671044 0.164324635 -0.1020619301 -0.3885597648 7.041522e-01
## [31,] 0.782425267 -0.005737804 0.2322469766 -0.0819000007 6.282935e-01
## [32,] 0.900073333 -0.744539987 -0.9820795441 -0.6163991202 -1.054886e+00
## [33,] 0.863235408 -0.106103579 -0.3698171213 -1.0727960522 5.032313e-01
## [34,] 0.267161381 -0.731071054 -0.7052021962 0.2919661692 -7.526491e-01
## [35,] -0.103928743 -0.374321254 -0.5890975173 -0.4772413729 -6.044609e-01
## [36,] 0.605048138 -0.210227118 -0.0546217339 -0.2877564130 1.163169e-02
## [37,] 0.304937621 0.483766219 1.2364207419 -0.6430223876 1.631357e-01
## [38,] -0.744376172 0.674388254 0.6702051769 0.3068661726 8.268246e-01
## [39,] -0.069680997 1.312930193 -0.6805184930 0.2957605475 -5.677380e-01
## [40,] -0.331860687 -0.260935423 -0.0366991911 0.0748393744 -2.068567e-01
## [41,] -0.117671785 0.430998436 0.3200432666 -0.4999942066 -4.104133e-01
## [42,] 0.132041717 0.893554873 -0.2432472162 0.6304913226 -8.958308e-02
## [43,] -0.096186486 -0.241438280 -0.3635659111 -0.5259977918 -4.962847e-01
## [44,] -0.147431386 0.120862397 -0.4152013875 -0.4746003849 -5.134341e-01
## [45,] 0.076496532 0.931225351 0.1633492382 0.0144120776 -1.799337e+00
## [46,] -0.018343520 -0.067784348 0.6770221964 -0.7774439620 -2.825916e-01
## [47,] -0.021543153 -0.413707919 -0.0662500680 -0.1332662479 2.062276e-01
## [48,] -0.821025648 -0.098222591 0.7063230665 0.3962353973 8.547391e-02
## [49,] 0.188199919 -0.321104690 0.3132836410 -0.5831053121 -4.468965e-01
## [50,] -0.012342962 -0.148521123 -0.0009358231 -0.1200343678 -4.853268e-01
## [51,] -0.242746325 0.188394260 0.3091000514 -0.0264858456 -1.321751e-01
## [52,] 0.690486621 0.965775849 -0.8291340872 0.3182180602 8.738494e-01
## [53,] -0.684497419 0.166840255 -0.5542711114 0.0392245980 -1.990740e-01
## [54,] -1.073383311 0.646401411 0.0940166827 -0.2941750648 2.063499e-01
## [55,] -0.032326206 -0.480386419 -0.3076805729 0.1960311181 9.610672e-03
## [56,] -1.241615069 -0.291431257 -0.5891660248 0.1485520981 -1.683053e+00
## [57,] -0.302388426 0.697587155 -1.1504707101 1.0339311586 6.465833e-01
## [58,] -0.382783729 -0.350483981 -0.1737586028 0.0184949088 -2.615180e-01
## [59,] 0.252184403 -0.394847452 0.2754125715 -0.3645687100 -7.641169e-02
## [60,] -0.808200312 -0.123940697 0.2532542471 0.8670970646 -2.714126e-01
## [61,] 0.058803792 -0.008058832 0.0808055677 -0.2225944498 -3.359320e-01
## [62,] -0.455221135 -0.113230629 -0.2016913287 -0.2836648104 3.048413e-02
## [63,] 0.026520246 -0.566645742 0.6106636624 0.0490238269 2.519706e-01
## [64,] 0.189153011 0.231271321 0.4698559157 -0.1880724473 -2.830553e-01
## [65,] 0.252184403 -0.394847452 0.2754125715 -0.3645687100 -7.641169e-02
## [66,] -0.151965650 0.020152878 -0.1642418723 0.0214922747 -1.087000e-01
## [67,] -0.419385910 -1.027586348 0.2855870308 0.4106976769 1.573219e-01
## [68,] 0.714918198 -0.270385101 -0.0886857026 -0.0214915611 -3.548542e-01
## [69,] -1.944020966 -0.248724464 0.1456356163 -0.2312901798 -2.162815e-01
## [70,] -0.767950041 -0.139303946 0.2169652270 0.3486682947 1.834929e-01
## [71,] -0.148710914 -0.824792739 0.2107986809 -0.8882793607 2.664148e-01
## [72,] -0.136022460 0.352895036 -0.7466020268 0.0494925716 1.424240e-02
## [73,] 0.602986655 0.022792990 0.2781288478 0.2579990864 4.562106e-02
## [74,] -0.220570876 0.671029379 -0.3555425158 -0.3920164041 3.781148e-01
## [75,] 0.118749294 -0.475233620 -0.5272411699 -0.1386900295 1.946544e-01
## [76,] 0.019423002 -0.998357568 -0.3204221524 -0.2068715664 -5.850856e-01
## [77,] 0.265095988 -0.178632390 0.9288171335 -0.0663288751 6.079029e-01
## [78,] -1.780429311 0.367180628 -0.5758414418 0.7075628356 -3.856852e-01
## [79,] 0.173994506 -0.461004423 -0.4521869221 0.5297211362 -3.789167e-01
## [80,] 0.823502563 0.054717611 -0.1922218266 0.7783239365 -1.630865e-02
## [81,] -0.455680654 -0.238395235 0.2348420995 0.1748859106 7.037636e-01
## [82,] -0.101042607 0.109701436 -0.0271824606 0.0778367403 -5.403869e-02
## [83,] -0.298604853 0.894267656 -0.0067065124 0.0509912700 -4.520995e-01
## [84,] -0.873919937 0.199844042 -0.3116891980 -0.2790876647 -3.686073e-01
## [85,] -0.091642914 0.171732271 -0.2693874236 0.3519487171 -6.278553e-02
## [86,] -0.415744234 0.264733563 -0.6795715034 0.3715070117 4.889002e-01
## [87,] 0.177556058 1.307222742 -0.0689884111 0.0343071418 -9.952426e-03
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## [282,] 0.102077779 0.079088271 0.3193890553 0.1523950669 1.904853e-01
## [283,] -0.058969819 -0.067333329 0.1605202958 -0.5267645093 2.261121e-01
## [284,] -0.769157009 0.424185953 0.3085871555 -0.1069700768 -3.856658e-01
## [285,] -0.204773503 -0.577883446 -0.1650435415 0.0774279391 2.214899e-01
## [286,] 0.174334005 -0.647190477 0.2255225751 -0.0269274553 4.103400e-01
## [287,] -0.365476652 0.168918305 0.0674292138 -0.0614385146 -3.945279e-01
## [288,] -0.703844519 0.260288672 -0.4958988643 0.3896527928 -4.507046e-01
## [289,] -0.467132884 0.389349057 -0.6710523039 -0.4784718324 -5.255655e-03
## [290,] -0.439455022 0.740124698 -0.1036563029 0.4588385657 1.228318e-01
## [291,] 0.261739110 0.276154498 -0.6628128121 0.4233361174 -7.672462e-01
## [292,] 0.520394098 0.953329130 0.0520012380 0.0420143364 5.589313e-01
## [293,] 0.047444338 0.021177192 0.0282145551 0.1029212003 1.426677e-01
## [294,] -0.518041043 0.633076015 -0.1535532514 0.3993307403 5.468953e-01
## [295,] 0.283586005 0.151769408 -0.2771582430 0.6228847829 4.216625e-01
## [296,] 0.875698074 0.392446336 -0.2190106459 0.5834680830 7.243675e-01
## [297,] 0.256377585 0.148618744 -0.1714265857 -0.4374109955 -1.137640e-01
## [298,] -0.382783729 -0.350483981 -0.1737586028 0.0184949088 -2.615180e-01
## [299,] -0.128638785 0.155883756 -0.2464241951 -0.4795773409 2.324076e-01
## [300,] 0.301880437 -0.679260168 -0.5203995885 -0.3018605522 -5.376670e-01
## [301,] -1.000824658 1.080460445 0.9788653036 -0.6051170739 4.081612e-01
## [302,] 0.256198143 -0.030032423 0.2305750970 0.1761348237 3.356600e-01
## [303,] -0.122477753 0.176610814 -0.1037394101 -0.0558122935 -8.047220e-01
## [304,] -0.735123406 0.562071571 -0.0784118043 -0.2849005269 2.849471e-01
## [305,] 0.082571542 0.136686856 0.5396344567 -0.8138569333 3.464272e-01
## [306,] -0.984325030 -0.181242438 -0.4416014170 -0.5544967588 2.291567e-02
## [307,] -0.462651059 0.555324976 0.5650158686 0.4982587050 -2.567112e-01
## [308,] 0.497325993 0.693943044 -0.1980573531 0.2084771898 6.629521e-01
## [309,] 0.372810450 -0.444607889 0.0319617881 -0.2505165322 1.675738e-01
## [310,] -0.488918621 -0.125519932 0.4376742487 0.1616160040 2.832146e-01
## [311,] 0.366962063 0.133591491 0.0639779231 -0.0919525419 -1.358025e-01
## [312,] 0.179496861 -0.862468367 0.0655190526 0.6965310586 2.742064e-01
## [313,] 0.314254386 -0.136072675 -0.2125405542 -0.0308890429 -4.624883e-01
## [314,] 0.117211357 0.366686682 0.7754898323 0.1554308593 2.709456e-02
## [315,] 0.423766714 0.046083322 -0.6858811644 -0.1685651860 -1.078929e-01
## [316,] -0.785695398 1.126840945 -0.0362935351 0.2022432354 -1.102664e+00
## [317,] 0.211031524 0.147632042 0.2144327539 0.1507131093 6.160934e-01
## [318,] 0.039592634 0.374018001 1.0571579044 0.4478985311 -5.182063e-01
## [319,] -0.544525163 0.643254995 0.0383011714 -1.3689357263 3.570892e-01
## [320,] 0.065172674 0.555198816 -0.6406765985 -0.0701835359 2.530242e-01
## [321,] -0.232987900 -0.859567799 -0.6261772030 -0.6059379526 -6.395812e-02
## [322,] -0.003163166 0.191815262 0.2510203103 -0.3935616007 -6.482557e-01
## [323,] 0.339588802 -0.368380457 -0.3697219440 -0.0555243440 1.536189e-01
## [324,] 0.057939571 -0.377960977 0.6205789141 -0.0408331590 -8.488984e-02
## [325,] -1.818060063 0.388757260 -1.1462055544 0.2286045227 9.182036e-03
## [326,] 0.561299642 0.568000189 0.4550590132 0.4379349546 8.431231e-01
## [327,] 1.278129111 0.278769952 0.3852439588 0.7099906652 3.546843e-02
## [328,] 0.345747824 -0.777770480 0.2750245468 0.1873935817 1.141572e+00
## [329,] -0.101042607 0.109701436 -0.0271824606 0.0778367403 -5.403869e-02
## [330,] 0.048909569 0.620652186 -0.2562117344 -0.3698320206 -3.135107e-01
## [331,] 0.580251738 0.207557620 -0.2918346014 0.4412174359 3.992092e-01
## [332,] 0.096950864 0.214167267 0.2882773506 -0.1792957154 -6.596828e-02
## [333,] 0.154723831 0.345476462 0.3783548842 0.1331151238 5.051676e-01
## [334,] 0.162048561 -0.145258148 -0.5583962398 -0.6285172792 6.275850e-01
## [335,] 0.312266664 1.048010324 0.0780280201 0.3401272587 4.899227e-01
## [336,] -0.455221135 -0.113230629 -0.2016913287 -0.2836648104 3.048413e-02
## [337,] -0.159551539 0.469630955 0.0729111110 0.3724379628 -2.174663e-01
## [338,] 0.032966380 0.287910029 0.3261484202 -0.3978323176 -4.364531e-01
## [339,] 0.737302283 -0.836049763 0.4176047805 -0.0769307754 -3.966415e-03
## [340,] 0.026664139 -0.669608311 0.4088008229 -0.5692684351 1.707253e-02
## [341,] 0.076575971 0.258584683 0.2776159518 0.1775148552 -2.078697e-01
## [342,] 0.174515185 -0.158165081 0.3473217812 0.4545547862 -1.015169e-01
## [343,] 0.225556044 0.106758668 -0.1351731382 -0.0608630116 -5.082832e-01
## [344,] -0.404298092 -0.023682071 -0.0646319170 -0.2273203449 8.514548e-02
## [345,] 0.169388270 -0.023086085 0.3162100765 0.1228640038 -3.579705e-01
## [346,] -0.730988758 -0.299867876 -0.0983089698 -0.4019307351 -2.347764e-01
## [347,] 1.016178903 -0.259247076 -0.4904141112 -0.0421599677 -1.503172e-01
## [348,] -0.232745494 0.426875294 -0.5491723807 -0.4687097924 4.141045e-01
## [349,] -0.461244280 -0.304052184 -0.0806641588 0.4020102829 1.582475e-01
## [350,] -0.808093327 -0.600213742 0.1866745916 -0.1877645222 -4.403814e-01
## [351,] -0.384887240 -0.125926221 1.8862272602 1.3442077666 -7.883426e-01
## [352,] 1.017028439 -1.418813337 -0.3122622161 -0.3721285926 1.744561e-01
## [353,] 0.197243208 -0.192923613 0.2032108971 0.3456713228 -1.992882e-01
## [354,] 0.111825369 -1.021073881 0.0750992366 -0.4161358774 6.838838e-02
## [355,] -0.148298973 -0.211402788 0.0444682944 -0.0281253700 5.787592e-01
## [356,] 0.870629067 -0.127649753 0.0391599168 0.5166809103 -4.664887e-01
## [357,] 0.935016654 0.009529492 -1.0988745510 -0.1444594119 -3.280238e-01
## [358,] 0.139152018 0.537234688 -0.0969488531 0.4338956958 6.516147e-01
## [359,] 0.299731169 -0.110590517 0.2406793914 -0.0471579988 1.848052e-01
## [360,] 0.204225659 -0.132723252 -0.0373119256 -0.1828548646 5.808283e-01
## [361,] 0.488186357 -0.795832668 0.6294983443 -0.4274231815 1.883167e-01
## [362,] 0.137867244 -0.118961581 0.0003476900 0.2057037401 4.085374e-01
## [363,] 0.808551339 0.989424749 -0.1252369954 -0.3104312336 3.020984e-01
## [364,] 0.386710485 -0.022529732 0.5714698109 0.1864715016 1.054470e+00
## [365,] 0.595694169 -0.554963308 0.5495844281 0.7803411692 -1.216109e+00
## [366,] -0.176882904 -0.486894315 0.2347268337 0.3905994575 3.031652e-01
## [367,] 0.220133776 0.514536078 -0.2307965144 -0.4235135495 -4.010758e-02
## [368,] -1.040682054 0.318205167 0.9069198466 0.3665074060 -6.889126e-01
## [369,] 0.139805421 -0.346116297 -0.5319436773 1.0573615428 1.366890e-02
## [370,] -1.158626159 0.438978364 0.4686753024 0.0965053623 -1.102276e-01
## [371,] -0.032131158 -0.674206753 0.5446365875 -1.3233255622 -3.864772e-01
## [372,] 0.529082080 0.099364398 0.5984719507 0.1076112407 5.457590e-01
## [373,] -0.320302886 0.325889703 0.2449762234 -0.1980385212 -1.912511e-01
## [374,] 0.567794347 -0.105803155 -0.3050704219 0.8214952357 1.743412e-01
## [375,] -0.289520432 0.504756872 -0.2760665654 0.0452958232 2.575472e-02
## [376,] 0.137867244 -0.118961581 0.0003476900 0.2057037401 4.085374e-01
## [377,] -0.459614159 0.204212921 -0.3277856322 -0.8075637033 8.229677e-01
## [378,] -0.101042607 0.109701436 -0.0271824606 0.0778367403 -5.403869e-02
## [379,] 0.974101877 -0.856322463 0.3077571374 -0.5643229941 -2.027920e-01
## [380,] -0.828187150 0.534565123 -1.0419994394 0.4364228024 -3.396176e-01
## [381,] 0.151411951 -0.295245803 0.6432103068 0.1003988749 -4.104269e-01
## [382,] -1.043871296 1.251839158 -0.0837327784 -0.5363416011 4.762114e-01
## [383,] -0.669785631 0.118947174 -0.4192449973 -0.2630436584 -9.518395e-02
## [384,] -0.167051153 0.382317670 -0.4478817624 1.1522409379 8.263914e-01
## [385,] 0.270692960 0.043056231 0.3127778510 0.4398270973 5.393936e-01
## [386,] 0.455127865 0.033552163 -0.5326370762 -0.7076369590 4.537300e-01
## [387,] 1.002082774 0.407782491 0.5458791120 -1.3683702699 -8.120448e-02
## [388,] -1.081112821 -0.395926008 0.4090234152 0.3739296669 -3.820256e-01
## [389,] -0.764433309 -0.353359720 -0.0696507207 0.6009580627 -4.408476e-01
## [390,] -0.136813464 0.385594037 0.2932199323 -0.9008453138 4.770603e-01
## [391,] 0.478707709 -0.118792078 0.2078585064 -0.4480402729 -4.693121e-01
## [392,] 0.122123424 0.392174471 -0.6170936967 0.3362632098 4.617731e-02
## [393,] -0.339493352 0.216541456 1.0825564552 0.0449384935 -1.133496e-01
## [394,] -0.742253577 0.525230844 0.4704468123 0.3975273465 1.620392e-01
## [395,] 0.096950864 0.214167267 0.2882773506 -0.1792957154 -6.596828e-02
## [396,] 0.413579949 -0.019445813 0.0173960587 -0.1656427319 1.042594e-01
## [397,] 0.204616878 -1.261042714 0.2036799577 0.0684221604 -2.680354e-01
## [398,] -0.511681052 -0.972384131 -0.0392327992 -0.3067339410 3.317680e-01
## [399,] -0.594477185 -0.600622764 0.0015647059 0.1806987728 5.020918e-02
## [400,] 0.046027822 0.124618709 0.1512179389 -0.2356401810 -1.206296e-01
## Comp.16 Comp.17 Comp.18 Comp.19 Comp.20
## [1,] 0.032015950 0.6469551148 0.0519227227 -0.700066265 -0.571698243
## [2,] 0.214974022 -0.3334777699 0.1463043171 0.581677532 0.351471771
## [3,] -0.286544929 -0.5598080752 0.2294965943 0.012445617 -0.270276217
## [4,] 0.171562451 -0.3348783814 -0.1735273212 0.463777924 -0.100904134
## [5,] -0.054294189 0.5625037663 0.1389179363 0.007091804 0.021525969
## [6,] 0.206352435 0.2053501151 0.0231471264 -0.191852851 0.180401345
## [7,] -0.069705938 -0.4733039418 0.4222356655 -0.450734844 -0.197085949
## [8,] 0.322083295 0.6112934628 0.1685111957 0.447610783 -0.184145822
## [9,] -0.420172158 -0.8965227069 -0.9090129962 0.468244516 -0.245107618
## [10,] -0.282844008 -0.8721989073 0.3319413367 0.393150131 -0.446235625
## [11,] -0.413850126 -0.1733695742 -0.1960243238 -0.409333636 0.481469881
## [12,] 0.004381923 0.1732352263 0.4367488713 -0.049398364 0.489737689
## [13,] 0.273667287 0.5422026251 0.2475829731 0.129355175 0.888506252
## [14,] -0.348798660 -0.4867212031 0.0698695722 0.271672558 -0.119646428
## [15,] -0.066650923 -0.0843389087 -0.3243152191 -0.631412073 0.585480274
## [16,] -0.442314960 0.3237509853 0.1375108092 0.618195549 0.613888978
## [17,] 0.583002204 -0.1319680649 -0.0729999905 -0.098312952 0.297601664
## [18,] 0.259978220 -0.0815963406 -0.1269201313 -0.025879713 0.046735785
## [19,] 0.339012346 -0.1608310012 -0.4652160948 0.320474466 -0.810120707
## [20,] -0.129818629 -0.0198362454 0.2133642346 0.426738979 -0.172511647
## [21,] 0.279394861 0.0360907245 0.1718891072 0.202333824 -0.132263820
## [22,] 0.050223994 0.1759941690 0.2357892646 0.218460461 -0.083452662
## [23,] 0.030507314 0.0011795165 0.0055174193 -0.077277218 0.037210541
## [24,] 0.392233729 0.7016276045 -0.7251930896 0.225103337 -0.049367141
## [25,] 0.166781894 0.3632539114 -0.6863012145 0.133273872 -0.023513776
## [26,] -0.173532097 0.5021414350 -0.1122133307 -0.245818123 -0.069711317
## [27,] -0.335364794 -0.2113341794 -1.8846265718 -0.239103840 0.070835016
## [28,] 0.782914706 -0.0803492126 -0.1072326373 -0.002869667 -0.183845511
## [29,] 0.937360938 0.9510604891 0.0054237533 -0.073497751 -0.410455917
## [30,] 1.185812614 -0.2325292659 0.0973315496 0.298337131 -0.006372863
## [31,] 0.187327872 -0.6433845099 0.6297931697 -0.759484273 1.246425448
## [32,] -0.465149720 -0.2501926010 -0.3494441058 0.551506674 0.383703549
## [33,] -1.201157301 -0.9345409815 -0.2785675746 0.195415536 -0.171462912
## [34,] -0.184717683 -0.0970466216 -0.2808843133 -0.043980724 -0.676569136
## [35,] -0.035280311 0.2822956256 -0.2339265305 -0.112177269 -0.080958201
## [36,] -0.721678890 0.4409062067 0.5910517146 -0.056908733 -0.099550273
## [37,] -0.151219615 -0.1195356080 0.3088943370 0.015664950 -0.727790317
## [38,] -0.630816661 0.6912690214 0.2524567085 0.467420508 -0.659303593
## [39,] -0.401567045 -0.9640713175 0.4730890375 -0.392121405 -0.060168992
## [40,] 0.471280495 0.1072240310 0.0645200427 0.067728321 -0.117571493
## [41,] 0.288401855 0.3715272415 0.0291506981 0.300887354 -0.514113277
## [42,] -0.020549944 -0.0527235037 0.0295223397 -0.192176817 0.112972025
## [43,] -0.177229878 0.2779846917 -0.7132184152 -0.349585770 -0.721155547
## [44,] -0.204087768 0.0401202599 -0.5663201826 -0.112190318 0.751014835
## [45,] 0.369257044 0.2747973826 -0.1962967155 0.143975186 1.072945219
## [46,] 0.686577387 0.7856280032 -0.6887232932 0.374510717 0.696318688
## [47,] -0.047699108 0.0254352339 -0.4961660909 0.871291186 -0.244073397
## [48,] 0.248962052 0.4028846374 0.5562141202 -0.635629369 -0.481492294
## [49,] 0.266757535 0.0322339757 -0.3714590598 0.248025513 -0.021057616
## [50,] -0.124717502 -0.6122996962 0.3866249666 -0.147679751 -0.033752066
## [51,] -0.055222543 0.0713849134 -0.1730860658 -0.082064856 0.038422098
## [52,] -0.136580284 -0.3754716938 0.2516405786 0.321479721 0.086893135
## [53,] -0.236454539 0.0172983078 -0.2568109080 0.485276801 -0.222559659
## [54,] 0.148843965 -0.1004973063 -0.3656570910 0.497381576 -0.022230171
## [55,] -0.497235115 0.3859525521 0.2565251921 -0.027749708 0.025705625
## [56,] -0.097394835 -0.3619291444 -0.6032780349 0.683722331 -0.818421518
## [57,] 0.211707878 -0.1288715031 0.8612000457 0.794849310 0.230372777
## [58,] 0.242109628 0.2471274755 0.1284202001 0.083854959 -0.068760336
## [59,] 0.048091398 -0.2426942416 -0.1466353054 0.112806417 -0.035744202
## [60,] -0.221512112 -0.7392720996 -0.1069614009 -0.398253681 -0.320479559
## [61,] -0.097594637 0.2582717338 -0.2522049052 -0.177374693 -0.075532036
## [62,] 0.050223994 0.1759941690 0.2357892646 0.218460461 -0.083452662
## [63,] 0.239162963 -0.1757714066 -0.2299801751 -0.137503432 -0.180874455
## [64,] -0.139800978 0.2226135523 0.2243740812 0.103060618 -0.642994520
## [65,] 0.048091398 -0.2426942416 -0.1466353054 0.112806417 -0.035744202
## [66,] -0.198663553 0.1410829611 0.0694175766 -0.061150580 0.086021699
## [67,] -0.046944021 0.3141851138 0.0133692543 -0.133337343 -0.010627251
## [68,] -0.173242262 0.3110331390 0.8061918860 -0.683308498 -0.484830746
## [69,] 0.635610490 -0.7522488657 0.4277569940 0.364169297 -0.231357862
## [70,] 0.330373380 1.4024266896 0.5055530937 -0.452331647 0.657735187
## [71,] -0.427137367 -0.3659595292 0.0814091293 -0.722596470 0.208489797
## [72,] 0.245076518 -0.0904478818 -0.0280790532 0.158818816 0.009841687
## [73,] -0.230544772 -0.2216910334 -0.2856334758 -0.260129333 0.034458026
## [74,] -0.061064959 0.1979140583 -0.4633943189 -0.089820113 0.039596661
## [75,] 0.462257549 0.3734051435 0.0181023495 -0.665248371 0.003066630
## [76,] -0.095040872 0.2606259187 0.7294612131 -0.264236800 0.073632854
## [77,] -0.172142371 0.6876901213 0.1391452919 0.457345875 0.494288970
## [78,] 0.067975875 0.0323646192 0.8020952780 0.332579501 0.878616876
## [79,] -0.125320284 0.0361992735 -0.0180739483 -0.037984488 -0.153593703
## [80,] -0.583230750 1.2189722320 0.6448738816 0.883238960 -0.017138137
## [81,] -0.312521511 -0.6923156587 -0.5747422865 -0.034427098 0.314184690
## [82,] 0.030507314 0.0011795165 0.0055174193 -0.077277218 0.037210541
## [83,] -0.692878567 0.0006260859 -0.7226798855 0.013780648 0.176446013
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## [287,] -0.252421261 -0.7723366873 -0.7805609912 -0.355792356 -0.630883289
## [288,] 0.569203421 -0.3094192307 -0.5051216535 0.373455570 -0.139237572
## [289,] 0.178763302 0.0974445802 0.0921267002 0.382244714 -0.167946361
## [290,] -0.100118554 0.0510830018 0.1205126992 -0.254872599 0.162940595
## [291,] -0.802827800 0.3093616141 -1.1639241564 0.253295802 -0.624067180
## [292,] 0.368148782 0.1359347391 -0.2671275964 -0.598140983 -0.039490364
## [293,] 0.805556835 0.8716726537 -0.2730475295 -0.596602453 0.110203609
## [294,] -0.544427214 -0.0847143891 0.1710715569 -0.176039862 0.979015841
## [295,] -0.125906930 -0.4200408971 0.9632715849 0.067403606 0.405753047
## [296,] 0.762125161 0.4501128423 0.3196981095 0.073733482 -0.796428710
## [297,] 0.096268852 0.3490579764 0.0392097511 -0.761633500 0.185420836
## [298,] 0.242109628 0.2471274755 0.1284202001 0.083854959 -0.068760336
## [299,] 0.285331725 0.1261810821 -0.1672352357 -0.132166783 -0.042820261
## [300,] 0.251694160 -0.0281708605 0.5810213660 0.320943952 1.055365113
## [301,] -0.031390602 0.2619171537 -0.0053935118 -0.397601183 -0.049795046
## [302,] -0.019517766 1.0807031271 -0.3235460226 -0.712994758 0.205881127
## [303,] 0.471939771 0.4840627870 0.6084563775 0.814725551 -0.099339118
## [304,] -0.058300245 -0.2352507721 -0.2774969892 -0.490553570 0.582527237
## [305,] -0.067045993 -0.2646506421 0.0538993965 0.540991667 -0.146763330
## [306,] 0.190608377 0.3748367702 0.4965006348 0.457755358 -0.142408006
## [307,] 0.426452187 0.4780818418 -0.1108876642 0.121771855 0.783980842
## [308,] 0.454178679 0.1228569296 -0.1570615046 -0.525829203 0.017634480
## [309,] -0.560666660 0.0689991149 -0.0219009980 0.108177765 -0.099101878
## [310,] 0.277261392 -0.2830005738 0.1291585057 -0.440478481 -0.079020457
## [311,] 0.209558838 0.1521489264 0.0490573944 -0.812010525 0.194023037
## [312,] 0.167710568 -0.5492988935 -0.0128680685 0.223664763 0.288156340
## [313,] -0.167822291 0.7533375559 0.2044794519 -0.231278156 0.200796374
## [314,] -0.109678072 -0.6622484955 0.2922035889 -0.023008754 -0.277548473
## [315,] -0.189644283 0.4583723732 0.1564026029 -0.598698763 0.098024421
## [316,] -0.449749128 0.4524710659 -0.2575697940 0.442138791 0.462355526
## [317,] 0.173567591 0.4266993873 -0.5003693352 0.089884241 -0.064053728
## [318,] -0.168653178 -0.7745971987 0.5643730037 0.536680578 -0.254728568
## [319,] 0.106049739 -0.4602859499 -0.0994215769 0.499281352 0.406444513
## [320,] -0.989739949 -0.2242565961 -0.0005684949 -0.291776514 0.670251903
## [321,] 0.013666801 -0.2603346871 -0.4748084832 -1.123890798 0.100193010
## [322,] 0.576342752 0.3871045577 -0.5384697717 0.233477118 -0.043935303
## [323,] -0.354269101 0.0228216668 0.1871420120 0.056522621 -0.038605577
## [324,] -0.533900460 0.2086824106 0.0725745243 -0.240803832 0.051682694
## [325,] -0.619771206 0.9879574183 -0.2926950903 -1.409542231 -0.338874113
## [326,] 0.711986769 0.3721653978 -0.3836194859 0.506176286 0.496620519
## [327,] 0.177363314 0.3488607261 -0.3750670645 -0.527263719 0.122821000
## [328,] 0.077318431 -0.3834718626 0.1580721282 0.007501933 -0.260030554
## [329,] 0.030507314 0.0011795165 0.0055174193 -0.077277218 0.037210541
## [330,] 0.486215923 0.0336267517 -0.4573085817 0.262042275 -0.143115588
## [331,] 0.759244245 0.0597843047 -0.4789700206 0.311064263 -0.283237535
## [332,] -0.176190286 -0.0097706227 -0.1349881975 -0.093146217 -0.081622162
## [333,] -0.007260562 0.1905872084 0.2381404634 0.502233563 0.524087945
## [334,] -0.074210975 -0.9343312003 0.1860746128 0.448458769 0.089223108
## [335,] 0.447005945 0.7026070182 -0.7428963195 -0.288763871 -0.336971140
## [336,] 0.050223994 0.1759941690 0.2357892646 0.218460461 -0.083452662
## [337,] 0.123369565 0.3875781402 0.2683185878 -0.102578097 -0.502860653
## [338,] 0.042475852 0.2651575945 -0.3598119518 0.042072879 -0.066935576
## [339,] -0.292785178 0.1544625804 -0.2745677473 -0.784524442 0.353562390
## [340,] 0.162142190 0.5094659553 0.2826486586 0.245874587 0.089797086
## [341,] -0.327774410 -0.4290198318 -0.5228694609 0.037715418 -0.138838803
## [342,] -0.131952098 -0.3389275436 0.1706336330 -0.216073326 -0.119268284
## [343,] 0.152201427 -0.0086394508 0.5850490727 0.883595051 0.476282160
## [344,] 0.279394861 0.0360907245 0.1718891072 0.202333824 -0.132263820
## [345,] 0.015695349 0.0613626838 -0.2423572620 -0.227751719 -0.066929836
## [346,] -0.757781353 0.8079818042 0.2924671427 0.150572407 -0.040351849
## [347,] -0.180429681 0.1027311797 0.6233424799 -0.158897049 -0.088672847
## [348,] -0.441325166 -0.1226024155 0.3947191478 0.319023479 -0.311519930
## [349,] 0.050215862 -0.2950861747 0.2433757274 -0.323023031 -0.222809169
## [350,] 0.931849444 0.2009762842 0.5038059909 0.564873768 0.439110132
## [351,] 1.147801369 -0.8830999298 0.8420999890 0.694607986 0.355661837
## [352,] -0.042215731 0.4876727357 -1.0579254354 -0.554797056 0.098314949
## [353,] 0.330896112 -0.0916185702 -0.1961913275 -0.171566576 -0.058616149
## [354,] 0.221525840 -0.2175437654 -0.4751014556 0.043930819 0.421482926
## [355,] -0.657374026 1.0740401669 0.4918250932 -0.373896970 0.014511510
## [356,] 0.076764318 -0.0283754786 -0.3404242954 0.197700444 0.004509190
## [357,] -0.039388446 0.0564320966 0.0267864963 0.667055290 -0.273092373
## [358,] -0.560420136 -0.3290287003 0.3529947971 -0.344730274 -0.033498112
## [359,] 0.018342775 -0.1867798254 -0.1192617878 0.019481708 -0.135016335
## [360,] -0.087512962 -0.2709909415 0.0981733685 0.226398991 -0.092583816
## [361,] 0.036226899 -0.3735259961 -0.3399519057 0.277089486 -0.149634676
## [362,] -0.308826526 -0.2977766494 0.1999016488 -0.156053532 -0.039183904
## [363,] 2.514874979 -0.7652975740 0.2622305269 0.016095726 0.407650979
## [364,] 0.013278150 0.2708028825 -0.5807342867 0.532262509 1.140881524
## [365,] 0.681580213 -0.4711911452 -0.1600797217 0.248152470 0.534057288
## [366,] 0.454811321 -0.2014779559 -0.1797311149 0.154272354 0.051678015
## [367,] 0.155995980 0.3435889460 0.2858427601 -0.139020573 0.150339581
## [368,] -0.351134834 -0.2066474100 0.2476973310 -1.355708123 0.294705407
## [369,] -0.187396890 -0.1818707511 -1.2031988741 -0.830841849 0.103065478
## [370,] 0.198942996 -0.6975532924 -0.0785157857 -0.301405090 0.127855205
## [371,] 0.096870451 -0.0323359394 0.6079765300 -0.476202276 0.070074760
## [372,] 0.318460063 0.4951521691 -0.2353467388 0.326407220 -0.735945102
## [373,] 1.197377056 0.7320470751 0.6848629361 0.199900693 -0.088444115
## [374,] 0.286160533 0.0896385508 -0.4587170325 0.066313349 -0.138340098
## [375,] 0.440862301 0.4309338924 0.3675818071 -0.722483119 0.097503419
## [376,] -0.308826526 -0.2977766494 0.1999016488 -0.156053532 -0.039183904
## [377,] 0.342458471 -0.0011420821 -0.6725814649 -0.479027226 -0.540875675
## [378,] 0.030507314 0.0011795165 0.0055174193 -0.077277218 0.037210541
## [379,] 0.061015930 0.3299729441 -0.0168768415 -0.325123918 -0.045134490
## [380,] -0.499939517 0.8302639524 -0.7296802218 -0.112697990 0.217847993
## [381,] -0.081963273 0.2767340194 0.8364370795 0.499853203 -0.148364709
## [382,] 0.023330868 0.4667636683 -0.7679740707 0.555555151 0.086626564
## [383,] 0.573154363 -0.9070736306 0.4333613047 -0.296977374 -0.173057417
## [384,] -0.449252234 -0.6076005729 -0.7268193498 -0.027059833 0.404951877
## [385,] 0.057686711 0.3696937818 -0.4266215345 0.055633853 -0.006640370
## [386,] 0.225508252 -0.7593338417 0.2600541128 -0.342717320 0.307743463
## [387,] 0.345305678 -0.3120550806 -0.2456251396 -0.268401521 -0.059238929
## [388,] 0.596537028 -0.3989677965 0.1925845216 0.499285887 0.430126321
## [389,] -0.958681685 0.1570655727 0.0339420693 0.011428396 -1.185968974
## [390,] -0.168290480 0.1150129122 -0.0416179062 0.046692642 0.095996867
## [391,] -0.980964155 -0.2904432107 0.3762333183 -0.301118714 0.064230069
## [392,] -0.721754398 -0.2266373236 0.2766732976 0.057156638 -0.074195079
## [393,] 1.117707908 0.5000550103 0.1273684239 0.225793474 -0.109787718
## [394,] -0.833653308 0.6024140431 -0.6510375249 -0.154904865 0.024896000
## [395,] -0.176190286 -0.0097706227 -0.1349881975 -0.093146217 -0.081622162
## [396,] -0.211128131 -0.1040039683 0.0131757628 -0.031915797 -0.144541579
## [397,] -0.374212989 -0.4687648805 0.1642224977 -0.629051519 -0.111169499
## [398,] -0.345209267 -0.5170482414 0.0073958594 0.708613719 -0.522886466
## [399,] -0.377605316 -0.2129913160 -0.0883260971 0.368055583 -0.554072101
## [400,] -0.405361152 0.1301328218 -0.0710880401 -0.077019579 -0.032811005biplot(fit)
# Varimax Rotated Principal Components
# retaining 5 components
fit <- principal(TL_data_clean, nfactors=4, rotate="varimax")
fit # print results## Principal Components Analysis
## Call: principal(r = TL_data_clean, nfactors = 4, rotate = "varimax")
## Standardized loadings (pattern matrix) based upon correlation matrix
## RC1 RC2 RC3 RC4 h2 u2 com
## JS58 0.34 0.76 0.35 0.20 0.85 0.15 2.0
## JS59 0.26 0.73 0.38 0.33 0.86 0.14 2.2
## JS60 0.36 0.73 0.26 0.32 0.83 0.17 2.2
## JS61 0.54 0.61 0.17 0.18 0.72 0.28 2.3
## JS62 0.62 0.47 0.22 0.29 0.74 0.26 2.6
## JS63 0.66 0.44 0.30 0.21 0.76 0.24 2.5
## JS64 0.71 0.34 0.23 0.27 0.75 0.25 2.0
## JS65 0.64 0.32 0.39 0.39 0.82 0.18 3.0
## JS66 0.59 0.27 0.37 0.45 0.76 0.24 3.1
## JS67 0.66 0.21 0.38 0.33 0.74 0.26 2.4
## JS68 0.60 0.42 0.36 0.27 0.73 0.27 3.0
## JS69 0.54 0.35 0.40 0.45 0.78 0.22 3.6
## JS70 0.36 0.27 0.26 0.70 0.77 0.23 2.1
## JS71 0.23 0.22 0.20 0.84 0.85 0.15 1.4
## JS72 0.44 0.39 0.41 0.48 0.75 0.25 3.9
## JS73 0.40 0.32 0.40 0.41 0.59 0.41 3.9
## JS74 0.51 0.30 0.59 0.31 0.79 0.21 3.1
## JS75 0.48 0.31 0.58 0.38 0.81 0.19 3.3
## JS76 0.22 0.25 0.82 0.20 0.83 0.17 1.5
## JS77 0.32 0.35 0.73 0.23 0.81 0.19 2.1
##
## RC1 RC2 RC3 RC4
## SS loadings 4.96 3.81 3.62 3.16
## Proportion Var 0.25 0.19 0.18 0.16
## Cumulative Var 0.25 0.44 0.62 0.78
## Proportion Explained 0.32 0.24 0.23 0.20
## Cumulative Proportion 0.32 0.56 0.80 1.00
##
## Mean item complexity = 2.6
## Test of the hypothesis that 4 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0.03
## with the empirical chi square 135.06 with prob < 0.11
##
## Fit based upon off diagonal values = 1summary(fit) # print variance accounted for##
## Factor analysis with Call: principal(r = TL_data_clean, nfactors = 4, rotate = "varimax")
##
## Test of the hypothesis that 4 factors are sufficient.
## The degrees of freedom for the model is 116 and the objective function was 1.3
## The number of observations was 400 with Chi Square = 504.53 with prob < 7.1e-50
##
## The root mean square of the residuals (RMSA) is 0.03# the principal components
biplot(fit)
# Let's run another factor anlaysis function on our data set
TL.fa <- factanal(TL_data_clean, factors=4)
TL.fa##
## Call:
## factanal(x = TL_data_clean, factors = 4)
##
## Uniquenesses:
## JS58 JS59 JS60 JS61 JS62 JS63 JS64 JS65 JS66 JS67 JS68 JS69 JS70
## 0.190 0.131 0.237 0.356 0.289 0.275 0.291 0.194 0.269 0.333 0.300 0.230 0.362
## JS71 JS72 JS73 JS74 JS75 JS76 JS77
## 0.411 0.273 0.441 0.227 0.200 0.338 0.239
##
## Loadings:
## Factor1 Factor2 Factor3 Factor4
## JS58 0.248 0.409 0.343 0.681
## JS59 0.383 0.234 0.341 0.743
## JS60 0.367 0.419 0.277 0.614
## JS61 0.271 0.550 0.279 0.436
## JS62 0.424 0.561 0.261 0.385
## JS63 0.361 0.586 0.349 0.361
## JS64 0.404 0.615 0.308 0.269
## JS65 0.559 0.488 0.399 0.311
## JS66 0.587 0.399 0.364 0.309
## JS67 0.536 0.407 0.369 0.278
## JS68 0.412 0.501 0.382 0.365
## JS69 0.574 0.403 0.397 0.347
## JS70 0.629 0.300 0.284 0.267
## JS71 0.658 0.208 0.242 0.231
## JS72 0.537 0.367 0.398 0.381
## JS73 0.450 0.352 0.388 0.288
## JS74 0.435 0.407 0.582 0.281
## JS75 0.520 0.329 0.565 0.319
## JS76 0.294 0.223 0.676 0.262
## JS77 0.313 0.291 0.688 0.325
##
## Factor1 Factor2 Factor3 Factor4
## SS loadings 4.296 3.512 3.440 3.165
## Proportion Var 0.215 0.176 0.172 0.158
## Cumulative Var 0.215 0.390 0.562 0.721
##
## Test of the hypothesis that 4 factors are sufficient.
## The chi square statistic is 238.85 on 116 degrees of freedom.
## The p-value is 1.58e-10# The first chunk provides the uniquenesses, which range from 0 to 1. The uniqueness, sometimes referred to as noise, corresponds to the proportion of variability, which can not be explained by a linear combination of the factors. A high uniqueness for a variable indicates that the factors do not account well for its variance.
# The next section is the loadings, which range from −1 to 1. The loadings are the contribution of each original variable to the factor. Variables with a high loading are well explained by the factor. Notice there is no entry for certain variables.One-level CFA
Now, Let’s do a CFA to confirm the factor.
# Load the R packages that needed for the analysis
library(foreign)
library(lavaan)## This is lavaan 0.6-7## lavaan is BETA software! Please report any bugs.##
## Attaching package: 'lavaan'## The following object is masked from 'package:psych':
##
## cor2cov# Establish our model
model <-'TL=~Direction+Cultivation+Organization+Tutor
Direction=~JS58+JS59+JS60+JS61
Cultivation=~JS62+JS63+JS64+JS65+JS66+JS67
Organization=~JS68+JS69+JS70+JS71
Tutor=~JS72+JS73+JS74+JS75+JS76+JS77'
# Factor 1 = Setting the Direction
# Factor 2 = Teacher Development
# Factor 3 = Establish Organization
# Factor 4 = Improving Tutor
str(TL_data_clean)## tibble [400 × 20] (S3: tbl_df/tbl/data.frame)
## $ JS58: num [1:400] 4 5 5 4 5 4 4 5 2 4 ...
## $ JS59: num [1:400] 4 4 5 4 5 4 4 4 2 4 ...
## $ JS60: num [1:400] 3 4 5 4 5 5 4 4 2 5 ...
## $ JS61: num [1:400] 3 4 5 4 5 5 4 4 5 4 ...
## $ JS62: num [1:400] 3 4 5 4 4 5 3 5 2 4 ...
## $ JS63: num [1:400] 4 4 5 4 4 4 5 5 3 5 ...
## $ JS64: num [1:400] 4 4 5 4 4 5 4 5 3 4 ...
## $ JS65: num [1:400] 3 4 5 5 4 4 4 5 3 5 ...
## $ JS66: num [1:400] 4 4 5 4 4 4 4 5 3 4 ...
## $ JS67: num [1:400] 4 5 5 5 4 4 4 5 3 4 ...
## $ JS68: num [1:400] 4 4 5 4 5 5 4 5 3 5 ...
## $ JS69: num [1:400] 4 4 5 4 5 5 4 5 1 4 ...
## $ JS70: num [1:400] 4 3 5 4 5 5 4 5 3 5 ...
## $ JS71: num [1:400] 3 4 5 4 4 5 4 4 3 5 ...
## $ JS72: num [1:400] 4 5 5 4 5 5 4 5 2 5 ...
## $ JS73: num [1:400] 4 5 5 4 5 5 4 5 4 5 ...
## $ JS74: num [1:400] 4 4 4 5 5 5 4 5 3 4 ...
## $ JS75: num [1:400] 3 4 4 5 5 5 4 4 3 4 ...
## $ JS76: num [1:400] 4 4 5 4 4 4 4 5 2 4 ...
## $ JS77: num [1:400] 4 4 4 4 5 5 4 5 3 4 ...# Fit the CFA model
fit <- cfa(model, data=TL_data_clean)
# Check the model summary
summary(fit,fit.measure=TRUE,standardized=TRUE)## lavaan 0.6-7 ended normally after 63 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 44
##
## Number of observations 400
##
## Model Test User Model:
##
## Test statistic 473.988
## Degrees of freedom 166
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 8006.856
## Degrees of freedom 190
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.961
## Tucker-Lewis Index (TLI) 0.955
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -6062.426
## Loglikelihood unrestricted model (H1) -5825.432
##
## Akaike (AIC) 12212.852
## Bayesian (BIC) 12388.477
## Sample-size adjusted Bayesian (BIC) 12248.862
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.068
## 90 Percent confidence interval - lower 0.061
## 90 Percent confidence interval - upper 0.075
## P-value RMSEA <= 0.05 0.000
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.030
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## TL =~
## Direction 1.000 0.910 0.910
## Cultivation 1.129 0.058 19.361 0.000 0.984 0.984
## Organization 1.059 0.053 19.877 0.000 0.990 0.990
## Tutor 1.053 0.054 19.663 0.000 0.965 0.965
## Direction =~
## JS58 1.000 0.696 0.886
## JS59 1.063 0.041 26.028 0.000 0.741 0.892
## JS60 1.105 0.044 25.344 0.000 0.769 0.881
## JS61 0.891 0.045 19.707 0.000 0.620 0.772
## Cultivation =~
## JS62 1.000 0.728 0.825
## JS63 0.912 0.045 20.473 0.000 0.664 0.832
## JS64 0.967 0.049 19.683 0.000 0.704 0.811
## JS65 1.138 0.048 23.467 0.000 0.828 0.904
## JS66 1.081 0.051 21.365 0.000 0.786 0.855
## JS67 0.920 0.046 20.065 0.000 0.670 0.821
## Organization =~
## JS68 1.000 0.678 0.837
## JS69 1.209 0.052 23.131 0.000 0.820 0.885
## JS70 0.889 0.048 18.615 0.000 0.603 0.774
## JS71 0.797 0.049 16.209 0.000 0.541 0.704
## Tutor =~
## JS72 1.000 0.691 0.847
## JS73 0.831 0.046 18.265 0.000 0.575 0.757
## JS74 1.030 0.044 23.441 0.000 0.712 0.879
## JS75 1.167 0.048 24.281 0.000 0.807 0.896
## JS76 0.832 0.046 18.069 0.000 0.575 0.752
## JS77 0.886 0.043 20.837 0.000 0.613 0.822
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .JS58 0.133 0.012 10.889 0.000 0.133 0.215
## .JS59 0.141 0.013 10.660 0.000 0.141 0.204
## .JS60 0.170 0.015 11.050 0.000 0.170 0.224
## .JS61 0.260 0.020 12.848 0.000 0.260 0.403
## .JS62 0.248 0.019 12.969 0.000 0.248 0.319
## .JS63 0.196 0.015 12.903 0.000 0.196 0.308
## .JS64 0.257 0.020 13.087 0.000 0.257 0.342
## .JS65 0.153 0.013 11.618 0.000 0.153 0.183
## .JS66 0.228 0.018 12.643 0.000 0.228 0.270
## .JS67 0.216 0.017 13.002 0.000 0.216 0.325
## .JS68 0.197 0.016 12.425 0.000 0.197 0.300
## .JS69 0.186 0.017 11.238 0.000 0.186 0.217
## .JS70 0.243 0.019 13.102 0.000 0.243 0.400
## .JS71 0.298 0.022 13.485 0.000 0.298 0.505
## .JS72 0.188 0.015 12.530 0.000 0.188 0.283
## .JS73 0.246 0.019 13.298 0.000 0.246 0.427
## .JS74 0.149 0.012 11.955 0.000 0.149 0.227
## .JS75 0.160 0.014 11.512 0.000 0.160 0.197
## .JS76 0.255 0.019 13.326 0.000 0.255 0.435
## .JS77 0.180 0.014 12.820 0.000 0.180 0.324
## TL 0.402 0.041 9.842 0.000 1.000 1.000
## .Direction 0.083 0.011 7.753 0.000 0.171 0.171
## .Cultivation 0.017 0.006 2.770 0.006 0.032 0.032
## .Organization 0.009 0.007 1.345 0.179 0.020 0.020
## .Tutor 0.033 0.007 4.883 0.000 0.068 0.068# Print out the paramarter Estimates
parameterEstimates(fit)## lhs op rhs est se z pvalue ci.lower ci.upper
## 1 TL =~ Direction 1.000 0.000 NA NA 1.000 1.000
## 2 TL =~ Cultivation 1.129 0.058 19.361 0.000 1.015 1.243
## 3 TL =~ Organization 1.059 0.053 19.877 0.000 0.955 1.164
## 4 TL =~ Tutor 1.053 0.054 19.663 0.000 0.948 1.158
## 5 Direction =~ JS58 1.000 0.000 NA NA 1.000 1.000
## 6 Direction =~ JS59 1.063 0.041 26.028 0.000 0.983 1.143
## 7 Direction =~ JS60 1.105 0.044 25.344 0.000 1.019 1.190
## 8 Direction =~ JS61 0.891 0.045 19.707 0.000 0.802 0.979
## 9 Cultivation =~ JS62 1.000 0.000 NA NA 1.000 1.000
## 10 Cultivation =~ JS63 0.912 0.045 20.473 0.000 0.825 0.999
## 11 Cultivation =~ JS64 0.967 0.049 19.683 0.000 0.871 1.063
## 12 Cultivation =~ JS65 1.138 0.048 23.467 0.000 1.043 1.233
## 13 Cultivation =~ JS66 1.081 0.051 21.365 0.000 0.981 1.180
## 14 Cultivation =~ JS67 0.920 0.046 20.065 0.000 0.830 1.010
## 15 Organization =~ JS68 1.000 0.000 NA NA 1.000 1.000
## 16 Organization =~ JS69 1.209 0.052 23.131 0.000 1.107 1.312
## 17 Organization =~ JS70 0.889 0.048 18.615 0.000 0.795 0.982
## 18 Organization =~ JS71 0.797 0.049 16.209 0.000 0.701 0.894
## 19 Tutor =~ JS72 1.000 0.000 NA NA 1.000 1.000
## 20 Tutor =~ JS73 0.831 0.046 18.265 0.000 0.742 0.921
## 21 Tutor =~ JS74 1.030 0.044 23.441 0.000 0.944 1.116
## 22 Tutor =~ JS75 1.167 0.048 24.281 0.000 1.073 1.261
## 23 Tutor =~ JS76 0.832 0.046 18.069 0.000 0.742 0.922
## 24 Tutor =~ JS77 0.886 0.043 20.837 0.000 0.803 0.970
## 25 JS58 ~~ JS58 0.133 0.012 10.889 0.000 0.109 0.157
## 26 JS59 ~~ JS59 0.141 0.013 10.660 0.000 0.115 0.166
## 27 JS60 ~~ JS60 0.170 0.015 11.050 0.000 0.140 0.201
## 28 JS61 ~~ JS61 0.260 0.020 12.848 0.000 0.220 0.300
## 29 JS62 ~~ JS62 0.248 0.019 12.969 0.000 0.210 0.285
## 30 JS63 ~~ JS63 0.196 0.015 12.903 0.000 0.166 0.225
## 31 JS64 ~~ JS64 0.257 0.020 13.087 0.000 0.219 0.296
## 32 JS65 ~~ JS65 0.153 0.013 11.618 0.000 0.128 0.179
## 33 JS66 ~~ JS66 0.228 0.018 12.643 0.000 0.193 0.263
## 34 JS67 ~~ JS67 0.216 0.017 13.002 0.000 0.184 0.249
## 35 JS68 ~~ JS68 0.197 0.016 12.425 0.000 0.166 0.228
## 36 JS69 ~~ JS69 0.186 0.017 11.238 0.000 0.154 0.219
## 37 JS70 ~~ JS70 0.243 0.019 13.102 0.000 0.206 0.279
## 38 JS71 ~~ JS71 0.298 0.022 13.485 0.000 0.255 0.342
## 39 JS72 ~~ JS72 0.188 0.015 12.530 0.000 0.159 0.218
## 40 JS73 ~~ JS73 0.246 0.019 13.298 0.000 0.210 0.283
## 41 JS74 ~~ JS74 0.149 0.012 11.955 0.000 0.124 0.173
## 42 JS75 ~~ JS75 0.160 0.014 11.512 0.000 0.132 0.187
## 43 JS76 ~~ JS76 0.255 0.019 13.326 0.000 0.218 0.293
## 44 JS77 ~~ JS77 0.180 0.014 12.820 0.000 0.152 0.207
## 45 TL ~~ TL 0.402 0.041 9.842 0.000 0.322 0.482
## 46 Direction ~~ Direction 0.083 0.011 7.753 0.000 0.062 0.104
## 47 Cultivation ~~ Cultivation 0.017 0.006 2.770 0.006 0.005 0.029
## 48 Organization ~~ Organization 0.009 0.007 1.345 0.179 -0.004 0.022
## 49 Tutor ~~ Tutor 0.033 0.007 4.883 0.000 0.019 0.046#
modificationindices(fit)## lhs op rhs mi epc sepc.lv sepc.all sepc.nox
## 50 TL =~ JS58 6.046 -0.298 -0.189 -0.240 -0.240
## 51 TL =~ JS59 1.450 -0.154 -0.098 -0.118 -0.118
## 52 TL =~ JS60 0.312 0.075 0.048 0.055 0.055
## 53 TL =~ JS61 15.974 0.553 0.351 0.437 0.437
## 54 TL =~ JS62 0.587 -0.425 -0.269 -0.305 -0.305
## 55 TL =~ JS63 0.045 0.105 0.067 0.084 0.084
## 56 TL =~ JS64 0.003 0.031 0.020 0.023 0.023
## 57 TL =~ JS65 0.128 -0.188 -0.119 -0.130 -0.130
## 58 TL =~ JS66 0.367 0.337 0.214 0.232 0.232
## 59 TL =~ JS67 0.075 0.141 0.090 0.110 0.110
## 60 TL =~ JS68 16.066 4.928 3.124 3.853 3.853
## 61 TL =~ JS69 0.394 0.973 0.617 0.665 0.665
## 62 TL =~ JS70 10.752 -3.691 -2.340 -3.006 -3.006
## 63 TL =~ JS71 2.660 -1.826 -1.158 -1.507 -1.507
## 64 TL =~ JS72 35.351 1.525 0.967 1.185 1.185
## 65 TL =~ JS73 2.877 0.454 0.288 0.379 0.379
## 66 TL =~ JS74 2.887 -0.416 -0.264 -0.326 -0.326
## 67 TL =~ JS75 0.207 -0.122 -0.077 -0.086 -0.086
## 68 TL =~ JS76 12.629 -0.964 -0.611 -0.799 -0.799
## 69 TL =~ JS77 5.285 -0.556 -0.352 -0.473 -0.473
## 70 Direction =~ JS62 12.488 0.388 0.270 0.306 0.306
## 71 Direction =~ JS63 6.624 0.252 0.175 0.220 0.220
## 72 Direction =~ JS64 0.041 0.023 0.016 0.018 0.018
## 73 Direction =~ JS65 3.665 -0.180 -0.125 -0.137 -0.137
## 74 Direction =~ JS66 1.202 -0.118 -0.082 -0.089 -0.089
## 75 Direction =~ JS67 3.683 -0.196 -0.137 -0.168 -0.168
## 76 Direction =~ JS68 5.699 0.254 0.177 0.218 0.218
## 77 Direction =~ JS69 0.558 -0.082 -0.057 -0.061 -0.061
## 78 Direction =~ JS70 4.091 -0.230 -0.160 -0.206 -0.206
## 79 Direction =~ JS71 4.903 -0.273 -0.190 -0.247 -0.247
## 80 Direction =~ JS72 12.420 0.318 0.222 0.272 0.272
## 81 Direction =~ JS73 0.598 0.076 0.053 0.070 0.070
## 82 Direction =~ JS74 1.296 -0.095 -0.066 -0.081 -0.081
## 83 Direction =~ JS75 1.170 -0.096 -0.067 -0.074 -0.074
## 84 Direction =~ JS76 2.381 -0.154 -0.107 -0.140 -0.140
## 85 Direction =~ JS77 0.219 0.040 0.028 0.038 0.038
## 86 Cultivation =~ JS58 4.810 -0.210 -0.153 -0.194 -0.194
## 87 Cultivation =~ JS59 3.508 -0.189 -0.137 -0.166 -0.166
## 88 Cultivation =~ JS60 0.975 0.105 0.077 0.088 0.088
## 89 Cultivation =~ JS61 17.404 0.459 0.334 0.416 0.416
## 90 Cultivation =~ JS68 6.559 0.936 0.681 0.840 0.840
## 91 Cultivation =~ JS69 0.455 0.275 0.200 0.216 0.216
## 92 Cultivation =~ JS70 4.548 -0.779 -0.567 -0.728 -0.728
## 93 Cultivation =~ JS71 1.065 -0.392 -0.285 -0.371 -0.371
## 94 Cultivation =~ JS72 24.980 0.844 0.614 0.752 0.752
## 95 Cultivation =~ JS73 0.619 0.140 0.102 0.134 0.134
## 96 Cultivation =~ JS74 0.144 -0.061 -0.044 -0.055 -0.055
## 97 Cultivation =~ JS75 0.050 -0.039 -0.028 -0.032 -0.032
## 98 Cultivation =~ JS76 12.150 -0.628 -0.457 -0.597 -0.597
## 99 Cultivation =~ JS77 8.475 -0.465 -0.338 -0.454 -0.454
## 100 Organization =~ JS58 7.227 -0.293 -0.199 -0.253 -0.253
## 101 Organization =~ JS59 1.120 -0.122 -0.083 -0.100 -0.100
## 102 Organization =~ JS60 0.179 0.051 0.035 0.040 0.040
## 103 Organization =~ JS61 16.335 0.505 0.343 0.427 0.427
## 104 Organization =~ JS62 1.272 -0.430 -0.291 -0.331 -0.331
## 105 Organization =~ JS63 0.314 -0.191 -0.130 -0.163 -0.163
## 106 Organization =~ JS64 0.329 0.219 0.149 0.171 0.171
## 107 Organization =~ JS65 0.074 -0.097 -0.066 -0.072 -0.072
## 108 Organization =~ JS66 1.092 0.398 0.270 0.293 0.293
## 109 Organization =~ JS67 0.481 0.246 0.167 0.204 0.204
## 110 Organization =~ JS72 35.779 1.266 0.859 1.052 1.052
## 111 Organization =~ JS73 5.024 0.497 0.337 0.444 0.444
## 112 Organization =~ JS74 5.804 -0.485 -0.329 -0.407 -0.407
## 113 Organization =~ JS75 0.125 -0.078 -0.053 -0.059 -0.059
## 114 Organization =~ JS76 11.591 -0.765 -0.519 -0.678 -0.678
## 115 Organization =~ JS77 4.263 -0.413 -0.280 -0.376 -0.376
## 116 Tutor =~ JS58 3.019 -0.157 -0.109 -0.138 -0.138
## 117 Tutor =~ JS59 0.004 -0.006 -0.004 -0.005 -0.005
## 118 Tutor =~ JS60 0.000 0.001 0.001 0.001 0.001
## 119 Tutor =~ JS61 7.769 0.295 0.204 0.254 0.254
## 120 Tutor =~ JS62 5.208 -0.438 -0.303 -0.344 -0.344
## 121 Tutor =~ JS63 0.013 -0.019 -0.013 -0.017 -0.017
## 122 Tutor =~ JS64 1.046 -0.198 -0.137 -0.158 -0.158
## 123 Tutor =~ JS65 0.789 0.152 0.105 0.115 0.115
## 124 Tutor =~ JS66 0.182 0.081 0.056 0.061 0.061
## 125 Tutor =~ JS67 0.517 0.128 0.089 0.109 0.109
## 126 Tutor =~ JS68 0.209 0.099 0.068 0.084 0.084
## 127 Tutor =~ JS69 0.264 0.118 0.082 0.088 0.088
## 128 Tutor =~ JS70 0.644 -0.179 -0.124 -0.159 -0.159
## 129 Tutor =~ JS71 0.076 0.065 0.045 0.059 0.059
## 130 JS58 ~~ JS59 12.299 0.038 0.038 0.274 0.274
## 131 JS58 ~~ JS60 0.388 -0.007 -0.007 -0.047 -0.047
## 132 JS58 ~~ JS61 0.324 -0.007 -0.007 -0.036 -0.036
## 133 JS58 ~~ JS62 0.037 -0.002 -0.002 -0.011 -0.011
## 134 JS58 ~~ JS63 7.473 0.026 0.026 0.161 0.161
## 135 JS58 ~~ JS64 0.073 0.003 0.003 0.016 0.016
## 136 JS58 ~~ JS65 2.388 -0.014 -0.014 -0.096 -0.096
## 137 JS58 ~~ JS66 0.765 -0.009 -0.009 -0.052 -0.052
## 138 JS58 ~~ JS67 0.054 0.002 0.002 0.014 0.014
## 139 JS58 ~~ JS68 5.479 0.023 0.023 0.139 0.139
## 140 JS58 ~~ JS69 2.102 -0.014 -0.014 -0.089 -0.089
## 141 JS58 ~~ JS70 4.737 -0.023 -0.023 -0.127 -0.127
## 142 JS58 ~~ JS71 10.130 -0.036 -0.036 -0.183 -0.183
## 143 JS58 ~~ JS72 1.302 0.011 0.011 0.068 0.068
## 144 JS58 ~~ JS73 0.143 0.004 0.004 0.022 0.022
## 145 JS58 ~~ JS74 0.881 0.008 0.008 0.057 0.057
## 146 JS58 ~~ JS75 11.020 -0.030 -0.030 -0.206 -0.206
## 147 JS58 ~~ JS76 2.112 0.015 0.015 0.084 0.084
## 148 JS58 ~~ JS77 1.479 0.011 0.011 0.072 0.072
## 149 JS59 ~~ JS60 0.050 0.003 0.003 0.017 0.017
## 150 JS59 ~~ JS61 10.399 -0.039 -0.039 -0.206 -0.206
## 151 JS59 ~~ JS62 1.210 -0.012 -0.012 -0.065 -0.065
## 152 JS59 ~~ JS63 2.086 -0.014 -0.014 -0.086 -0.086
## 153 JS59 ~~ JS64 12.248 -0.039 -0.039 -0.207 -0.207
## 154 JS59 ~~ JS65 0.064 -0.002 -0.002 -0.016 -0.016
## 155 JS59 ~~ JS66 0.454 0.007 0.007 0.040 0.040
## 156 JS59 ~~ JS67 0.133 0.004 0.004 0.022 0.022
## 157 JS59 ~~ JS68 1.147 -0.011 -0.011 -0.064 -0.064
## 158 JS59 ~~ JS69 1.637 0.013 0.013 0.080 0.080
## 159 JS59 ~~ JS70 0.063 -0.003 -0.003 -0.015 -0.015
## 160 JS59 ~~ JS71 0.770 0.010 0.010 0.051 0.051
## 161 JS59 ~~ JS72 1.665 0.013 0.013 0.078 0.078
## 162 JS59 ~~ JS73 1.587 -0.014 -0.014 -0.074 -0.074
## 163 JS59 ~~ JS74 5.386 -0.021 -0.021 -0.143 -0.143
## 164 JS59 ~~ JS75 7.008 0.025 0.025 0.166 0.166
## 165 JS59 ~~ JS76 0.981 0.011 0.011 0.058 0.058
## 166 JS59 ~~ JS77 1.461 0.011 0.011 0.072 0.072
## 167 JS60 ~~ JS61 0.047 -0.003 -0.003 -0.014 -0.014
## 168 JS60 ~~ JS62 17.193 0.050 0.050 0.242 0.242
## 169 JS60 ~~ JS63 0.000 0.000 0.000 0.000 0.000
## 170 JS60 ~~ JS64 0.405 0.008 0.008 0.037 0.037
## 171 JS60 ~~ JS65 0.874 0.009 0.009 0.057 0.057
## 172 JS60 ~~ JS66 0.302 -0.006 -0.006 -0.032 -0.032
## 173 JS60 ~~ JS67 4.942 -0.025 -0.025 -0.130 -0.130
## 174 JS60 ~~ JS68 2.592 -0.017 -0.017 -0.095 -0.095
## 175 JS60 ~~ JS69 0.004 0.001 0.001 0.004 0.004
## 176 JS60 ~~ JS70 0.040 0.002 0.002 0.012 0.012
## 177 JS60 ~~ JS71 0.191 0.006 0.006 0.025 0.025
## 178 JS60 ~~ JS72 0.052 0.002 0.002 0.013 0.013
## 179 JS60 ~~ JS73 0.601 0.009 0.009 0.045 0.045
## 180 JS60 ~~ JS74 0.004 0.001 0.001 0.004 0.004
## 181 JS60 ~~ JS75 0.001 0.000 0.000 0.002 0.002
## 182 JS60 ~~ JS76 2.977 -0.021 -0.021 -0.099 -0.099
## 183 JS60 ~~ JS77 1.281 -0.012 -0.012 -0.066 -0.066
## 184 JS61 ~~ JS62 5.157 0.031 0.031 0.124 0.124
## 185 JS61 ~~ JS63 6.184 0.031 0.031 0.136 0.136
## 186 JS61 ~~ JS64 18.054 0.060 0.060 0.231 0.231
## 187 JS61 ~~ JS65 3.101 -0.020 -0.020 -0.101 -0.101
## 188 JS61 ~~ JS66 0.994 -0.013 -0.013 -0.055 -0.055
## 189 JS61 ~~ JS67 1.145 -0.014 -0.014 -0.058 -0.058
## 190 JS61 ~~ JS68 13.868 0.047 0.047 0.205 0.205
## 191 JS61 ~~ JS69 1.253 -0.014 -0.014 -0.064 -0.064
## 192 JS61 ~~ JS70 0.279 0.007 0.007 0.029 0.029
## 193 JS61 ~~ JS71 0.379 -0.009 -0.009 -0.033 -0.033
## 194 JS61 ~~ JS72 1.671 -0.016 -0.016 -0.072 -0.072
## 195 JS61 ~~ JS73 0.251 0.007 0.007 0.027 0.027
## 196 JS61 ~~ JS74 0.991 0.011 0.011 0.056 0.056
## 197 JS61 ~~ JS75 0.662 -0.010 -0.010 -0.047 -0.047
## 198 JS61 ~~ JS76 2.455 -0.022 -0.022 -0.084 -0.084
## 199 JS61 ~~ JS77 0.183 0.005 0.005 0.023 0.023
## 200 JS62 ~~ JS63 2.045 0.018 0.018 0.079 0.079
## 201 JS62 ~~ JS64 7.165 0.037 0.037 0.147 0.147
## 202 JS62 ~~ JS65 0.429 -0.008 -0.008 -0.039 -0.039
## 203 JS62 ~~ JS66 0.733 -0.011 -0.011 -0.048 -0.048
## 204 JS62 ~~ JS67 0.904 -0.012 -0.012 -0.053 -0.053
## 205 JS62 ~~ JS68 0.098 -0.004 -0.004 -0.017 -0.017
## 206 JS62 ~~ JS69 0.394 -0.008 -0.008 -0.036 -0.036
## 207 JS62 ~~ JS70 0.627 -0.011 -0.011 -0.043 -0.043
## 208 JS62 ~~ JS71 0.190 -0.006 -0.006 -0.023 -0.023
## 209 JS62 ~~ JS72 0.363 0.007 0.007 0.033 0.033
## 210 JS62 ~~ JS73 0.288 0.007 0.007 0.029 0.029
## 211 JS62 ~~ JS74 0.102 0.003 0.003 0.018 0.018
## 212 JS62 ~~ JS75 6.580 -0.029 -0.029 -0.148 -0.148
## 213 JS62 ~~ JS76 0.312 0.008 0.008 0.030 0.030
## 214 JS62 ~~ JS77 7.355 -0.031 -0.031 -0.148 -0.148
## 215 JS63 ~~ JS64 3.320 0.023 0.023 0.101 0.101
## 216 JS63 ~~ JS65 0.657 0.008 0.008 0.049 0.049
## 217 JS63 ~~ JS66 5.984 -0.029 -0.029 -0.138 -0.138
## 218 JS63 ~~ JS67 3.678 -0.022 -0.022 -0.106 -0.106
## 219 JS63 ~~ JS68 9.620 0.034 0.034 0.172 0.172
## 220 JS63 ~~ JS69 4.642 -0.024 -0.024 -0.124 -0.124
## 221 JS63 ~~ JS70 2.248 -0.018 -0.018 -0.081 -0.081
## 222 JS63 ~~ JS71 7.080 -0.034 -0.034 -0.143 -0.143
## 223 JS63 ~~ JS72 2.600 0.017 0.017 0.089 0.089
## 224 JS63 ~~ JS73 0.114 0.004 0.004 0.018 0.018
## 225 JS63 ~~ JS74 0.554 -0.007 -0.007 -0.042 -0.042
## 226 JS63 ~~ JS75 1.221 -0.011 -0.011 -0.064 -0.064
## 227 JS63 ~~ JS76 1.347 -0.014 -0.014 -0.062 -0.062
## 228 JS63 ~~ JS77 0.793 0.009 0.009 0.049 0.049
## 229 JS64 ~~ JS65 0.107 0.004 0.004 0.019 0.019
## 230 JS64 ~~ JS66 7.003 -0.036 -0.036 -0.148 -0.148
## 231 JS64 ~~ JS67 4.708 -0.028 -0.028 -0.119 -0.119
## 232 JS64 ~~ JS68 0.409 0.008 0.008 0.035 0.035
## 233 JS64 ~~ JS69 2.227 0.019 0.019 0.085 0.085
## 234 JS64 ~~ JS70 0.554 -0.010 -0.010 -0.040 -0.040
## 235 JS64 ~~ JS71 0.012 0.002 0.002 0.006 0.006
## 236 JS64 ~~ JS72 0.100 0.004 0.004 0.017 0.017
## 237 JS64 ~~ JS73 0.087 -0.004 -0.004 -0.016 -0.016
## 238 JS64 ~~ JS74 2.976 0.019 0.019 0.097 0.097
## 239 JS64 ~~ JS75 6.742 -0.030 -0.030 -0.149 -0.149
## 240 JS64 ~~ JS76 2.136 -0.020 -0.020 -0.078 -0.078
## 241 JS64 ~~ JS77 0.038 0.002 0.002 0.011 0.011
## 242 JS65 ~~ JS66 0.120 0.004 0.004 0.021 0.021
## 243 JS65 ~~ JS67 0.121 -0.004 -0.004 -0.021 -0.021
## 244 JS65 ~~ JS68 2.248 -0.015 -0.015 -0.088 -0.088
## 245 JS65 ~~ JS69 0.655 0.008 0.008 0.050 0.050
## 246 JS65 ~~ JS70 0.169 0.005 0.005 0.024 0.024
## 247 JS65 ~~ JS71 0.043 0.002 0.002 0.012 0.012
## 248 JS65 ~~ JS72 1.837 -0.013 -0.013 -0.079 -0.079
## 249 JS65 ~~ JS73 0.432 -0.007 -0.007 -0.037 -0.037
## 250 JS65 ~~ JS74 0.866 0.008 0.008 0.056 0.056
## 251 JS65 ~~ JS75 12.769 0.034 0.034 0.218 0.218
## 252 JS65 ~~ JS76 0.295 -0.006 -0.006 -0.031 -0.031
## 253 JS65 ~~ JS77 2.151 -0.014 -0.014 -0.085 -0.085
## 254 JS66 ~~ JS67 20.397 0.056 0.056 0.254 0.254
## 255 JS66 ~~ JS68 0.071 -0.003 -0.003 -0.015 -0.015
## 256 JS66 ~~ JS69 0.005 -0.001 -0.001 -0.004 -0.004
## 257 JS66 ~~ JS70 0.386 0.008 0.008 0.034 0.034
## 258 JS66 ~~ JS71 8.109 0.040 0.040 0.154 0.154
## 259 JS66 ~~ JS72 0.001 0.000 0.000 0.002 0.002
## 260 JS66 ~~ JS73 0.001 0.000 0.000 0.001 0.001
## 261 JS66 ~~ JS74 0.070 0.003 0.003 0.015 0.015
## 262 JS66 ~~ JS75 0.230 0.005 0.005 0.028 0.028
## 263 JS66 ~~ JS76 0.296 -0.007 -0.007 -0.030 -0.030
## 264 JS66 ~~ JS77 0.023 -0.002 -0.002 -0.008 -0.008
## 265 JS67 ~~ JS68 1.619 0.015 0.015 0.070 0.070
## 266 JS67 ~~ JS69 1.622 0.015 0.015 0.073 0.073
## 267 JS67 ~~ JS70 0.042 -0.003 -0.003 -0.011 -0.011
## 268 JS67 ~~ JS71 1.754 -0.018 -0.018 -0.071 -0.071
## 269 JS67 ~~ JS72 2.885 0.019 0.019 0.094 0.094
## 270 JS67 ~~ JS73 3.508 -0.023 -0.023 -0.101 -0.101
## 271 JS67 ~~ JS74 0.517 0.007 0.007 0.041 0.041
## 272 JS67 ~~ JS75 1.422 0.013 0.013 0.069 0.069
## 273 JS67 ~~ JS76 0.061 -0.003 -0.003 -0.013 -0.013
## 274 JS67 ~~ JS77 1.694 -0.014 -0.014 -0.071 -0.071
## 275 JS68 ~~ JS69 2.538 -0.021 -0.021 -0.110 -0.110
## 276 JS68 ~~ JS70 0.500 -0.009 -0.009 -0.041 -0.041
## 277 JS68 ~~ JS71 9.590 -0.042 -0.042 -0.172 -0.172
## 278 JS68 ~~ JS72 0.064 0.003 0.003 0.014 0.014
## 279 JS68 ~~ JS73 2.344 0.018 0.018 0.083 0.083
## 280 JS68 ~~ JS74 3.516 -0.018 -0.018 -0.108 -0.108
## 281 JS68 ~~ JS75 0.108 -0.003 -0.003 -0.019 -0.019
## 282 JS68 ~~ JS76 0.023 -0.002 -0.002 -0.008 -0.008
## 283 JS68 ~~ JS77 0.753 0.009 0.009 0.048 0.048
## 284 JS69 ~~ JS70 0.555 0.010 0.010 0.046 0.046
## 285 JS69 ~~ JS71 0.162 0.006 0.006 0.024 0.024
## 286 JS69 ~~ JS72 0.004 0.001 0.001 0.004 0.004
## 287 JS69 ~~ JS73 0.972 0.012 0.012 0.055 0.055
## 288 JS69 ~~ JS74 1.973 -0.014 -0.014 -0.084 -0.084
## 289 JS69 ~~ JS75 1.230 0.012 0.012 0.068 0.068
## 290 JS69 ~~ JS76 0.611 -0.010 -0.010 -0.044 -0.044
## 291 JS69 ~~ JS77 0.462 0.007 0.007 0.039 0.039
## 292 JS70 ~~ JS71 35.053 0.086 0.086 0.319 0.319
## 293 JS70 ~~ JS72 4.477 0.025 0.025 0.116 0.116
## 294 JS70 ~~ JS73 5.146 0.030 0.030 0.121 0.121
## 295 JS70 ~~ JS74 1.660 -0.014 -0.014 -0.072 -0.072
## 296 JS70 ~~ JS75 0.847 -0.010 -0.010 -0.053 -0.053
## 297 JS70 ~~ JS76 0.010 0.001 0.001 0.005 0.005
## 298 JS70 ~~ JS77 2.671 -0.019 -0.019 -0.089 -0.089
## 299 JS71 ~~ JS72 12.076 0.045 0.045 0.188 0.188
## 300 JS71 ~~ JS73 0.026 -0.002 -0.002 -0.009 -0.009
## 301 JS71 ~~ JS74 0.277 -0.006 -0.006 -0.029 -0.029
## 302 JS71 ~~ JS75 0.001 0.000 0.000 -0.002 -0.002
## 303 JS71 ~~ JS76 1.061 -0.015 -0.015 -0.054 -0.054
## 304 JS71 ~~ JS77 0.930 -0.012 -0.012 -0.052 -0.052
## 305 JS72 ~~ JS73 0.688 0.010 0.010 0.046 0.046
## 306 JS72 ~~ JS74 7.678 -0.028 -0.028 -0.167 -0.167
## 307 JS72 ~~ JS75 10.089 -0.034 -0.034 -0.197 -0.197
## 308 JS72 ~~ JS76 1.180 -0.013 -0.013 -0.060 -0.060
## 309 JS72 ~~ JS77 1.596 -0.013 -0.013 -0.072 -0.072
## 310 JS73 ~~ JS74 0.928 -0.011 -0.011 -0.055 -0.055
## 311 JS73 ~~ JS75 0.324 0.007 0.007 0.033 0.033
## 312 JS73 ~~ JS76 2.626 -0.022 -0.022 -0.087 -0.087
## 313 JS73 ~~ JS77 3.335 -0.021 -0.021 -0.100 -0.100
## 314 JS74 ~~ JS75 11.361 0.034 0.034 0.220 0.220
## 315 JS74 ~~ JS76 2.219 0.017 0.017 0.085 0.085
## 316 JS74 ~~ JS77 0.565 0.007 0.007 0.044 0.044
## 317 JS75 ~~ JS76 0.190 -0.005 -0.005 -0.025 -0.025
## 318 JS75 ~~ JS77 0.005 -0.001 -0.001 -0.004 -0.004
## 319 JS76 ~~ JS77 47.007 0.080 0.080 0.375 0.375
## 324 Direction ~~ Cultivation 0.246 0.003 0.084 0.084 0.084
## 325 Direction ~~ Organization 1.414 -0.007 -0.267 -0.267 -0.267
## 326 Direction ~~ Tutor 0.464 0.004 0.081 0.081 0.081
## 327 Cultivation ~~ Organization 0.464 0.005 0.383 0.383 0.383
## 328 Cultivation ~~ Tutor 1.415 -0.008 -0.351 -0.351 -0.351
## 329 Organization ~~ Tutor 0.246 0.003 0.182 0.182 0.182# Print out the path diagram
library("lavaanPlot")
lavaanPlot(model=fit,node_options=list(shape="box",fontname="Helvetica"),edge_options=list(color="blue"),coefs=TRUE, covs=TRUE, stars=c("regress"),stand = FALSE)Two-level CFA with “SchoolID” as cluster
Prepare a function to calculate the between and with-in covariate retrived from: http://faculty.missouri.edu/huangf/data/mcfa/MCFA%20in%20R%20HUANG.pdf
mcfa.input<-function(gp,dat){
dat1<-dat[complete.cases(dat),]
g<-dat1[,gp] #grouping
freq<-data.frame(table(g))
gn<-grep(gp,names(dat1)) #which column number is the grouping var
dat2<-dat1[,-gn] #raw only
G<-length(table(g))
n<-nrow(dat2)
k<-ncol(dat2)
scaling<-(n^2-sum(freq$Freq^2)) / (n*(G-1))
varn<-names(dat1[,-gn])
ms<-matrix(0,n,k)
for (i in 1:k){
ms[,i]<-ave(dat2[,i],g)
}
cs<-dat2-ms #deviation matrix, centered scores
colnames(ms)<-colnames(cs)<-varn
b.cov<-(cov(ms) * (n - 1))/(G-1) #group level cov matrix
w.cov<-(cov(cs) * (n - 1))/(n-G) #individual level cov matrix
pb.cov<-(b.cov-w.cov)/scaling #estimate of pure/adjusted between cov matrix
w.cor<-cov2cor(w.cov) #individual level cor matrix
b.cor<-cov2cor(b.cov) #group level cor matrix
pb.cor<-cov2cor(pb.cov) #estimate of pure between cor matrix
icc<-round(diag(pb.cov)/(diag(w.cov)+diag(pb.cov)),3) #iccs
return(list(b.cov=b.cov,pw.cov=w.cov,ab.cov=pb.cov,pw.cor=w.cor,
b.cor=b.cor,ab.cor=pb.cor,
n=n,G=G,c.=scaling,sqc=sqrt(scaling),
icc=icc,dfw=n-G,dfb=G) )
}
alpha<-function(dat){
covar<-dat[lower.tri(dat)] #get unique covariances
n<-ncol(dat) #number of items in the scale
al<-((sum(covar)/length(covar))*n^2/sum(dat))
cat("alpha:",return(al),"\n")
}Prepare the dataset
# Load the data with 2-level information
TL_ML <- read_excel("Teacher_Leadership_ML.xlsx")
# Prepare the data set
TL_ML <- as.data.frame(TL_ML)
TL_ML_data <- mcfa.input("SchoolID",TL_ML)
combined.cov <- list(within = TL_ML_data$pw.cov, between = TL_ML_data$b.cov)
combined.n <- list(within = TL_ML_data$n - TL_ML_data$G, between = TL_ML_data$G)
TL_ML_data$icc #view intraclass correlation (ICCs) of the 20 variables## JS58 JS59 JS60 JS61 JS62 JS63 JS64 JS65 JS66 JS67 JS68 JS69 JS70
## 0.197 0.195 0.180 0.212 0.228 0.208 0.202 0.212 0.167 0.229 0.238 0.196 0.177
## JS71 JS72 JS73 JS74 JS75 JS76 JS77
## 0.160 0.197 0.221 0.204 0.203 0.178 0.170Specify the model
# Specify the model
twolevelmodel <- '
level: 1
TL=~Direction+Cultivation+Organization+Tutor
Direction=~JS58+JS59+JS60+JS61
Cultivation=~JS62+JS63+JS64+JS65+JS66+JS67
Organization=~JS68+JS69+JS70+JS71
Tutor=~JS72+JS73+JS74+JS75+JS76+JS77
level: 2
School =~JS58+JS59+JS60+JS61+JS62+JS63+JS64+JS65+JS66+JS67+JS68+JS69+JS70+JS71+JS72+JS73+JS74+JS75+JS76+JS77
'
# Run a two-level CFA
ML.fit <- cfa(twolevelmodel,data=TL_ML,cluster="SchoolID")## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS58" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 31 40 42 46 55
## 58 64 67 68 70 77## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS59" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 9 11 16 24 29 31 42
## 46 58 64 68 70 77## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS60" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 29 31 40 42 46
## 58 64 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS61" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 9 16 31 42 46 58 64
## 67 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS62" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 31 42 58 64 68
## 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS63" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 29 31 42 46 58
## 64 67 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS64" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 16 31 42 58 64 68 70
## 77## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS65" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 31 42 46 58 64
## 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS66" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 31 42 58 64 68
## 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS67" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 9 11 16 29 31 42 58
## 64 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS68" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 29 31 42 46 58
## 64 67 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS69" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 29 31 42 46 58
## 64 68 70 77## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS70" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 29 31 58 64 68
## 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS71" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 29 31 42 58 64 68
## 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS72" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 9 11 16 29 31 40 42
## 49 58 64 67 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS73" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 31 42 46 58 64 67
## 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS74" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 29 31 42 58 64
## 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS75" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 31 42 46 58 64 67
## 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS76" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 11 16 29 31 42 46 58
## 64 67 68 70## Warning in lav_data_full(data = data, group = group, cluster = cluster, : lavaan WARNING:
## Level-1 variable "JS77" has no variance within some clusters. The
## cluster ids with zero within variance are: 3 9 11 16 29 31 35 42
## 46 49 58 64 68 70## Warning in lav_model_estimate(lavmodel = lavmodel, lavpartable = lavpartable, :
## lavaan WARNING: the optimizer warns that a solution has NOT been found!## Warning in lav_model_estimate(lavmodel = lavmodel, lavpartable = lavpartable, :
## lavaan WARNING: the optimizer warns that a solution has NOT been found!## Warning in lav_model_estimate(lavmodel = lavmodel, lavpartable = lavpartable, :
## lavaan WARNING: the optimizer warns that a solution has NOT been found!## Warning in lav_model_estimate(lavmodel = lavmodel, lavpartable = lavpartable, :
## lavaan WARNING: the optimizer warns that a solution has NOT been found!# Check the summary
summary(ML.fit, fit.measures = T, standardized = T)## lavaan 0.6-7 did NOT end normally after 190 iterations
## ** WARNING ** Estimates below are most likely unreliable
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 104
##
## Number of observations 958
## Number of clusters [SchoolID] 89
##
## Model Test User Model:
##
## Test statistic NA
## Degrees of freedom NA## Warning in .local(object, ...): lavaan WARNING: fit measures not available if model did not converge##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
##
## Level 1 [within]:
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## TL =~
## Direction 1.000 0.955 0.955
## Cultivation 1.176 NA 0.989 0.989
## Organization 1.045 NA 0.994 0.994
## Tutor 1.184 NA 0.984 0.984
## Direction =~
## JS58 1.000 0.543 0.901
## JS59 1.204 NA 0.654 0.939
## JS60 1.253 NA 0.680 0.933
## JS61 1.071 NA 0.582 0.876
## Cultivation =~
## JS62 1.000 0.617 0.890
## JS63 0.934 NA 0.576 0.895
## JS64 1.054 NA 0.650 0.892
## JS65 1.123 NA 0.693 0.938
## JS66 1.161 NA 0.716 0.918
## JS67 1.001 NA 0.617 0.901
## Organization =~
## JS68 1.000 0.546 0.885
## JS69 1.241 NA 0.677 0.881
## JS70 1.063 NA 0.580 0.883
## JS71 1.084 NA 0.591 0.873
## Tutor =~
## JS72 1.000 0.625 0.914
## JS73 0.901 NA 0.563 0.870
## JS74 1.049 NA 0.655 0.933
## JS75 1.127 NA 0.704 0.937
## JS76 0.959 NA 0.599 0.853
## JS77 0.977 NA 0.610 0.915
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .JS58 0.000 0.000 0.000
## .JS59 0.000 0.000 0.000
## .JS60 0.000 0.000 0.000
## .JS61 0.000 0.000 0.000
## .JS62 0.000 0.000 0.000
## .JS63 0.000 0.000 0.000
## .JS64 0.000 0.000 0.000
## .JS65 0.000 0.000 0.000
## .JS66 0.000 0.000 0.000
## .JS67 0.000 0.000 0.000
## .JS68 0.000 0.000 0.000
## .JS69 0.000 0.000 0.000
## .JS70 0.000 0.000 0.000
## .JS71 0.000 0.000 0.000
## .JS72 0.000 0.000 0.000
## .JS73 0.000 0.000 0.000
## .JS74 0.000 0.000 0.000
## .JS75 0.000 0.000 0.000
## .JS76 0.000 0.000 0.000
## .JS77 0.000 0.000 0.000
## TL 0.000 0.000 0.000
## .Direction 0.000 0.000 0.000
## .Cultivation 0.000 0.000 0.000
## .Organization 0.000 0.000 0.000
## .Tutor 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .JS58 0.068 NA 0.068 0.187
## .JS59 0.057 NA 0.057 0.118
## .JS60 0.069 NA 0.069 0.130
## .JS61 0.103 NA 0.103 0.233
## .JS62 0.099 NA 0.099 0.207
## .JS63 0.083 NA 0.083 0.200
## .JS64 0.108 NA 0.108 0.204
## .JS65 0.066 NA 0.066 0.120
## .JS66 0.096 NA 0.096 0.157
## .JS67 0.089 NA 0.089 0.189
## .JS68 0.082 NA 0.082 0.216
## .JS69 0.133 NA 0.133 0.224
## .JS70 0.095 NA 0.095 0.221
## .JS71 0.110 NA 0.110 0.239
## .JS72 0.077 NA 0.077 0.165
## .JS73 0.102 NA 0.102 0.244
## .JS74 0.064 NA 0.064 0.130
## .JS75 0.069 NA 0.069 0.122
## .JS76 0.135 NA 0.135 0.273
## .JS77 0.072 NA 0.072 0.163
## TL 0.269 NA 1.000 1.000
## .Direction 0.026 NA 0.088 0.088
## .Cultivation 0.008 NA 0.022 0.022
## .Organization 0.004 NA 0.013 0.013
## .Tutor 0.013 NA 0.033 0.033
##
##
## Level 2 [SchoolID]:
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## School =~
## JS58 1.000 1.702 0.974
## JS59 1.123 NA 1.912 0.999
## JS60 1.122 NA 1.910 1.000
## JS61 1.128 NA 1.920 0.999
## JS62 1.122 NA 1.909 0.994
## JS63 1.139 NA 1.939 1.000
## JS64 1.116 NA 1.899 1.000
## JS65 1.122 NA 1.909 1.000
## JS66 1.111 NA 1.891 0.999
## JS67 1.119 NA 1.905 0.999
## JS68 1.145 NA 1.949 0.997
## JS69 1.125 NA 1.915 1.000
## JS70 1.129 NA 1.922 0.999
## JS71 1.116 NA 1.899 0.990
## JS72 1.137 NA 1.935 0.998
## JS73 1.138 NA 1.937 0.999
## JS74 1.124 NA 1.914 1.000
## JS75 1.128 NA 1.921 1.000
## JS76 1.128 NA 1.921 0.995
## JS77 1.135 NA 1.931 0.996
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .JS58 0.445 NA 0.445 0.255
## .JS59 0.124 NA 0.124 0.065
## .JS60 0.115 NA 0.115 0.060
## .JS61 0.126 NA 0.126 0.066
## .JS62 0.094 NA 0.094 0.049
## .JS63 0.129 NA 0.129 0.066
## .JS64 0.106 NA 0.106 0.056
## .JS65 0.101 NA 0.101 0.053
## .JS66 0.112 NA 0.112 0.059
## .JS67 0.113 NA 0.113 0.059
## .JS68 0.120 NA 0.120 0.061
## .JS69 0.109 NA 0.109 0.057
## .JS70 0.131 NA 0.131 0.068
## .JS71 0.137 NA 0.137 0.071
## .JS72 0.124 NA 0.124 0.064
## .JS73 0.127 NA 0.127 0.066
## .JS74 0.116 NA 0.116 0.061
## .JS75 0.110 NA 0.110 0.057
## .JS76 0.136 NA 0.136 0.071
## .JS77 0.146 NA 0.146 0.075
## School 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .JS58 0.154 NA 0.154 0.050
## .JS59 0.004 NA 0.004 0.001
## .JS60 0.001 NA 0.001 0.000
## .JS61 0.008 NA 0.008 0.002
## .JS62 0.042 NA 0.042 0.011
## .JS63 0.001 NA 0.001 0.000
## .JS64 0.001 NA 0.001 0.000
## .JS65 0.001 NA 0.001 0.000
## .JS66 0.006 NA 0.006 0.002
## .JS67 0.005 NA 0.005 0.001
## .JS68 0.026 NA 0.026 0.007
## .JS69 -0.003 NA -0.003 -0.001
## .JS70 0.005 NA 0.005 0.001
## .JS71 0.071 NA 0.071 0.019
## .JS72 0.012 NA 0.012 0.003
## .JS73 0.011 NA 0.011 0.003
## .JS74 -0.001 NA -0.001 -0.000
## .JS75 -0.000 NA -0.000 -0.000
## .JS76 0.040 NA 0.040 0.011
## .JS77 0.033 NA 0.033 0.009
## School 2.897 NA 1.000 1.000Two Level model using “TeachYear” as the cluster
Prepare the dataset
# Load the data with 2-level information
TL_MLTY <- read_excel("Teacher_Leadership_MLTY.xlsx")
# Prepare the data set
TL_MLTY <- as.data.frame(TL_MLTY)
TL_MLTY_data <- mcfa.input("TeachYear",TL_MLTY)
combined.cov <- list(within = TL_MLTY_data$pw.cov, between = TL_MLTY_data$b.cov)
combined.n <- list(within = TL_MLTY_data$n - TL_MLTY_data$G, between = TL_MLTY_data$G)
TL_MLTY_data$icc #view intraclass correlation (ICCs) of the 20 variables## JS58 JS59 JS60 JS61 JS62 JS63 JS64 JS65 JS66 JS67 JS68 JS69 JS70
## 0.032 0.028 0.023 0.042 0.018 0.020 0.037 0.033 0.037 0.033 0.035 0.035 0.019
## JS71 JS72 JS73 JS74 JS75 JS76 JS77
## 0.016 0.021 0.035 0.027 0.026 0.016 0.023Specify the model
# Specify the model
twolevelmodel <- '
level: 1
TL=~Direction+Cultivation+Organization+Tutor
Direction=~JS58+JS59+JS60+JS61
Cultivation=~JS62+JS63+JS64+JS65+JS66+JS67
Organization=~JS68+JS69+JS70+JS71
Tutor=~JS72+JS73+JS74+JS75+JS76+JS77
level: 2
TY =~JS58+JS59+JS60+JS61+JS62+JS63+JS64+JS65+JS66+JS67+JS68+JS69+JS70+JS71+JS72+JS73+JS74+JS75+JS76+JS77
'
# Run a two-level CFA
MLTY.fit <- cfa(twolevelmodel,data=TL_MLTY,cluster="TeachYear")## Warning in lav_model_estimate(lavmodel = lavmodel, lavpartable = lavpartable, :
## lavaan WARNING: the optimizer warns that a solution has NOT been found!## Warning in lav_model_estimate(lavmodel = lavmodel, lavpartable = lavpartable, :
## lavaan WARNING: the optimizer warns that a solution has NOT been found!## Warning in lav_model_estimate(lavmodel = lavmodel, lavpartable = lavpartable, :
## lavaan WARNING: the optimizer warns that a solution has NOT been found!## Warning in lav_model_estimate(lavmodel = lavmodel, lavpartable = lavpartable, :
## lavaan WARNING: the optimizer warns that a solution has NOT been found!# Check the summary
summary(ML.fit, fit.measures = T, standardized = T)## lavaan 0.6-7 did NOT end normally after 190 iterations
## ** WARNING ** Estimates below are most likely unreliable
##
## Estimator ML
## Optimization method NLMINB
## Number of free parameters 104
##
## Number of observations 958
## Number of clusters [SchoolID] 89
##
## Model Test User Model:
##
## Test statistic NA
## Degrees of freedom NA## Warning in .local(object, ...): lavaan WARNING: fit measures not available if model did not converge##
## Parameter Estimates:
##
## Standard errors Standard
## Information Observed
## Observed information based on Hessian
##
##
## Level 1 [within]:
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## TL =~
## Direction 1.000 0.955 0.955
## Cultivation 1.176 NA 0.989 0.989
## Organization 1.045 NA 0.994 0.994
## Tutor 1.184 NA 0.984 0.984
## Direction =~
## JS58 1.000 0.543 0.901
## JS59 1.204 NA 0.654 0.939
## JS60 1.253 NA 0.680 0.933
## JS61 1.071 NA 0.582 0.876
## Cultivation =~
## JS62 1.000 0.617 0.890
## JS63 0.934 NA 0.576 0.895
## JS64 1.054 NA 0.650 0.892
## JS65 1.123 NA 0.693 0.938
## JS66 1.161 NA 0.716 0.918
## JS67 1.001 NA 0.617 0.901
## Organization =~
## JS68 1.000 0.546 0.885
## JS69 1.241 NA 0.677 0.881
## JS70 1.063 NA 0.580 0.883
## JS71 1.084 NA 0.591 0.873
## Tutor =~
## JS72 1.000 0.625 0.914
## JS73 0.901 NA 0.563 0.870
## JS74 1.049 NA 0.655 0.933
## JS75 1.127 NA 0.704 0.937
## JS76 0.959 NA 0.599 0.853
## JS77 0.977 NA 0.610 0.915
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .JS58 0.000 0.000 0.000
## .JS59 0.000 0.000 0.000
## .JS60 0.000 0.000 0.000
## .JS61 0.000 0.000 0.000
## .JS62 0.000 0.000 0.000
## .JS63 0.000 0.000 0.000
## .JS64 0.000 0.000 0.000
## .JS65 0.000 0.000 0.000
## .JS66 0.000 0.000 0.000
## .JS67 0.000 0.000 0.000
## .JS68 0.000 0.000 0.000
## .JS69 0.000 0.000 0.000
## .JS70 0.000 0.000 0.000
## .JS71 0.000 0.000 0.000
## .JS72 0.000 0.000 0.000
## .JS73 0.000 0.000 0.000
## .JS74 0.000 0.000 0.000
## .JS75 0.000 0.000 0.000
## .JS76 0.000 0.000 0.000
## .JS77 0.000 0.000 0.000
## TL 0.000 0.000 0.000
## .Direction 0.000 0.000 0.000
## .Cultivation 0.000 0.000 0.000
## .Organization 0.000 0.000 0.000
## .Tutor 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .JS58 0.068 NA 0.068 0.187
## .JS59 0.057 NA 0.057 0.118
## .JS60 0.069 NA 0.069 0.130
## .JS61 0.103 NA 0.103 0.233
## .JS62 0.099 NA 0.099 0.207
## .JS63 0.083 NA 0.083 0.200
## .JS64 0.108 NA 0.108 0.204
## .JS65 0.066 NA 0.066 0.120
## .JS66 0.096 NA 0.096 0.157
## .JS67 0.089 NA 0.089 0.189
## .JS68 0.082 NA 0.082 0.216
## .JS69 0.133 NA 0.133 0.224
## .JS70 0.095 NA 0.095 0.221
## .JS71 0.110 NA 0.110 0.239
## .JS72 0.077 NA 0.077 0.165
## .JS73 0.102 NA 0.102 0.244
## .JS74 0.064 NA 0.064 0.130
## .JS75 0.069 NA 0.069 0.122
## .JS76 0.135 NA 0.135 0.273
## .JS77 0.072 NA 0.072 0.163
## TL 0.269 NA 1.000 1.000
## .Direction 0.026 NA 0.088 0.088
## .Cultivation 0.008 NA 0.022 0.022
## .Organization 0.004 NA 0.013 0.013
## .Tutor 0.013 NA 0.033 0.033
##
##
## Level 2 [SchoolID]:
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## School =~
## JS58 1.000 1.702 0.974
## JS59 1.123 NA 1.912 0.999
## JS60 1.122 NA 1.910 1.000
## JS61 1.128 NA 1.920 0.999
## JS62 1.122 NA 1.909 0.994
## JS63 1.139 NA 1.939 1.000
## JS64 1.116 NA 1.899 1.000
## JS65 1.122 NA 1.909 1.000
## JS66 1.111 NA 1.891 0.999
## JS67 1.119 NA 1.905 0.999
## JS68 1.145 NA 1.949 0.997
## JS69 1.125 NA 1.915 1.000
## JS70 1.129 NA 1.922 0.999
## JS71 1.116 NA 1.899 0.990
## JS72 1.137 NA 1.935 0.998
## JS73 1.138 NA 1.937 0.999
## JS74 1.124 NA 1.914 1.000
## JS75 1.128 NA 1.921 1.000
## JS76 1.128 NA 1.921 0.995
## JS77 1.135 NA 1.931 0.996
##
## Intercepts:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .JS58 0.445 NA 0.445 0.255
## .JS59 0.124 NA 0.124 0.065
## .JS60 0.115 NA 0.115 0.060
## .JS61 0.126 NA 0.126 0.066
## .JS62 0.094 NA 0.094 0.049
## .JS63 0.129 NA 0.129 0.066
## .JS64 0.106 NA 0.106 0.056
## .JS65 0.101 NA 0.101 0.053
## .JS66 0.112 NA 0.112 0.059
## .JS67 0.113 NA 0.113 0.059
## .JS68 0.120 NA 0.120 0.061
## .JS69 0.109 NA 0.109 0.057
## .JS70 0.131 NA 0.131 0.068
## .JS71 0.137 NA 0.137 0.071
## .JS72 0.124 NA 0.124 0.064
## .JS73 0.127 NA 0.127 0.066
## .JS74 0.116 NA 0.116 0.061
## .JS75 0.110 NA 0.110 0.057
## .JS76 0.136 NA 0.136 0.071
## .JS77 0.146 NA 0.146 0.075
## School 0.000 0.000 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .JS58 0.154 NA 0.154 0.050
## .JS59 0.004 NA 0.004 0.001
## .JS60 0.001 NA 0.001 0.000
## .JS61 0.008 NA 0.008 0.002
## .JS62 0.042 NA 0.042 0.011
## .JS63 0.001 NA 0.001 0.000
## .JS64 0.001 NA 0.001 0.000
## .JS65 0.001 NA 0.001 0.000
## .JS66 0.006 NA 0.006 0.002
## .JS67 0.005 NA 0.005 0.001
## .JS68 0.026 NA 0.026 0.007
## .JS69 -0.003 NA -0.003 -0.001
## .JS70 0.005 NA 0.005 0.001
## .JS71 0.071 NA 0.071 0.019
## .JS72 0.012 NA 0.012 0.003
## .JS73 0.011 NA 0.011 0.003
## .JS74 -0.001 NA -0.001 -0.000
## .JS75 -0.000 NA -0.000 -0.000
## .JS76 0.040 NA 0.040 0.011
## .JS77 0.033 NA 0.033 0.009
## School 2.897 NA 1.000 1.000Rasch Partial Credit Model
Prepare the data and Rasch package
# Load the package
library(eRm) # For running the Partial Credit Model##
## Attaching package: 'eRm'## The following object is masked from 'package:psych':
##
## sim.raschlibrary(plyr) # For plot the Item characteristic curves## ------------------------------------------------------------------------------## You have loaded plyr after dplyr - this is likely to cause problems.
## If you need functions from both plyr and dplyr, please load plyr first, then dplyr:
## library(plyr); library(dplyr)## ------------------------------------------------------------------------------##
## Attaching package: 'plyr'## The following objects are masked from 'package:Hmisc':
##
## is.discrete, summarize## The following objects are masked from 'package:dplyr':
##
## arrange, count, desc, failwith, id, mutate, rename, summarise,
## summarizelibrary(WrightMap)# For plot the variable map# Prepare the data set
# Add ID column for test takers
ID <- 1:400
TL_data_PC <- TL_data_clean
# Centering the 1st category to zero
TL_data_PC <- TL_data_PC-1Run the Partial Credit Model
# Run the Partial Credit Model
PC_model <- PCM(TL_data_PC)Wright Map & Expected Response Curves & Item characteristic curves
# Plot the Variable Map
plotPImap(PC_model)
# Item characteristic curves
plotICC(PC_model, ask = FALSE)
Item diffculty and threshold SEs values
### Examine item difficulty values:
item.estimates <- thresholds(PC_model)
item.estimates##
## Design Matrix Block 1:
## Location Threshold 1 Threshold 2 Threshold 3 Threshold 4
## JS58 1.05545 -2.55718 -0.81711 1.44190 6.15418
## JS59 1.41391 -2.65551 -0.56301 2.38926 6.48490
## JS60 1.70196 -1.98769 -0.15166 2.50850 6.43867
## JS61 1.25229 -2.52934 -0.95668 2.07988 6.41529
## JS62 1.92700 -1.72172 0.00020 2.71062 6.71889
## JS63 1.07802 -2.09298 -0.84131 1.30473 5.94165
## JS64 1.96685 -1.68359 -0.12443 2.76831 6.90712
## JS65 2.04552 -1.30568 0.40245 2.52477 6.56053
## JS66 2.29663 -0.44035 -0.15212 2.92185 6.85715
## JS67 1.73945 -1.87000 -0.50004 2.31879 7.00906
## JS68 1.11465 -1.66877 -0.90562 1.26604 5.76695
## JS69 1.95906 -1.34455 0.56312 2.31322 6.30446
## JS70 0.87945 -3.68046 -1.19429 2.05693 6.33563
## JS71 1.06357 -3.61954 -1.43881 2.50048 6.81213
## JS72 1.12981 -2.64131 -0.55995 1.71158 6.00893
## JS73 0.82503 -2.93897 -1.32214 1.42626 6.13499
## JS74 1.44720 -2.23008 -0.50893 1.92552 6.60228
## JS75 1.89120 -0.28924 -0.34319 1.91743 6.27979
## JS76 1.01031 -3.04737 -0.98335 1.62394 6.44802
## JS77 0.68383 -3.70702 -1.03204 1.25714 6.21724item_difficulty <- item.estimates[["threshtable"]][["1"]]
item_difficulty## Location Threshold 1 Threshold 2 Threshold 3 Threshold 4
## JS58 1.0554478 -2.5571806 -0.8171135906 1.441900 6.154185
## JS59 1.4139109 -2.6555053 -0.5630094536 2.389255 6.484903
## JS60 1.7019580 -1.9876855 -0.1516574773 2.508501 6.438674
## JS61 1.2522884 -2.5293438 -0.9566759662 2.079881 6.415292
## JS62 1.9269980 -1.7217166 0.0001990053 2.710619 6.718891
## JS63 1.0780226 -2.0929791 -0.8413090851 1.304728 5.941650
## JS64 1.9668504 -1.6835900 -0.1244345775 2.768309 6.907117
## JS65 2.0455165 -1.3056838 0.4024507844 2.524769 6.560530
## JS66 2.2966322 -0.4403544 -0.1521217280 2.921851 6.857154
## JS67 1.7394504 -1.8700011 -0.5000446160 2.318790 7.009057
## JS68 1.1146486 -1.6687717 -0.9056239758 1.266036 5.766954
## JS69 1.9590630 -1.3445536 0.5631210427 2.313221 6.304464
## JS70 0.8794525 -3.6804552 -1.1942904661 2.056928 6.335628
## JS71 1.0635680 -3.6195353 -1.4388093463 2.500482 6.812135
## JS72 1.1298124 -2.6413078 -0.5599507307 1.711581 6.008927
## JS73 0.8250348 -2.9389744 -1.3221378016 1.426259 6.134992
## JS74 1.4471967 -2.2300793 -0.5089307783 1.925519 6.602278
## JS75 1.8911974 -0.2892407 -0.3431857955 1.917427 6.279789
## JS76 1.0103092 -3.0473747 -0.9833522188 1.623940 6.448024
## JS77 0.6838298 -3.7070178 -1.0320390803 1.257137 6.217239## Get threshold SEs values:
item.se <- item.estimates$se.thresh
item.se## thresh beta JS58.c1 thresh beta JS58.c2 thresh beta JS58.c3 thresh beta JS58.c4
## 0.7105940 0.4272366 0.2505792 0.2058739
## thresh beta JS59.c1 thresh beta JS59.c2 thresh beta JS59.c3 thresh beta JS59.c4
## 0.6921224 0.3779087 0.2263486 0.2093885
## thresh beta JS60.c1 thresh beta JS60.c2 thresh beta JS60.c3 thresh beta JS60.c4
## 0.5888828 0.3567879 0.2258522 0.2094243
## thresh beta JS61.c1 thresh beta JS61.c2 thresh beta JS61.c3 thresh beta JS61.c4
## 0.7133381 0.4156044 0.2318184 0.2083352
## thresh beta JS62.c1 thresh beta JS62.c2 thresh beta JS62.c3 thresh beta JS62.c4
## 0.5536302 0.3460460 0.2216311 0.2116334
## thresh beta JS63.c1 thresh beta JS63.c2 thresh beta JS63.c3 thresh beta JS63.c4
## 0.6684335 0.4417097 0.2561634 0.2047071
## thresh beta JS64.c1 thresh beta JS64.c2 thresh beta JS64.c3 thresh beta JS64.c4
## 0.5585551 0.3517377 0.2195241 0.2131580
## thresh beta JS65.c1 thresh beta JS65.c2 thresh beta JS65.c3 thresh beta JS65.c4
## 0.4986452 0.3363189 0.2277316 0.2101568
## thresh beta JS66.c1 thresh beta JS66.c2 thresh beta JS66.c3 thresh beta JS66.c4
## 0.4866415 0.3702693 0.2175698 0.2131761
## thresh beta JS67.c1 thresh beta JS67.c2 thresh beta JS67.c3 thresh beta JS67.c4
## 0.6061771 0.3840687 0.2262721 0.2130732
## thresh beta JS68.c1 thresh beta JS68.c2 thresh beta JS68.c3 thresh beta JS68.c4
## 0.6418214 0.4570733 0.2584437 0.2040227
## thresh beta JS69.c1 thresh beta JS69.c2 thresh beta JS69.c3 thresh beta JS69.c4
## 0.4945152 0.3357909 0.2345873 0.2082582
## thresh beta JS70.c1 thresh beta JS70.c2 thresh beta JS70.c3 thresh beta JS70.c4
## 0.9071985 0.4246875 0.2318510 0.2078606
## thresh beta JS71.c1 thresh beta JS71.c2 thresh beta JS71.c3 thresh beta JS71.c4
## 0.9191702 0.4349985 0.2208528 0.2118203
## thresh beta JS72.c1 thresh beta JS72.c2 thresh beta JS72.c3 thresh beta JS72.c4
## 0.6955601 0.3990968 0.2446384 0.2056566
## thresh beta JS73.c1 thresh beta JS73.c2 thresh beta JS73.c3 thresh beta JS73.c4
## 0.8062478 0.4633878 0.2486557 0.2057670
## thresh beta JS74.c1 thresh beta JS74.c2 thresh beta JS74.c3 thresh beta JS74.c4
## 0.6441966 0.3924884 0.2366390 0.2092235
## thresh beta JS75.c1 thresh beta JS75.c2 thresh beta JS75.c3 thresh beta JS75.c4
## 0.5131458 0.4218403 0.2405229 0.2072646
## thresh beta JS76.c1 thresh beta JS76.c2 thresh beta JS76.c3 thresh beta JS76.c4
## 0.7857460 0.4269439 0.2430146 0.2077586
## thresh beta JS77.c1 thresh beta JS77.c2 thresh beta JS77.c3 thresh beta JS77.c4
## 0.9034792 0.4393580 0.2549441 0.2059627Examine Person locations (theta) and SEs
# Standard errors for theta estimates:
person.locations.estimate <- person.parameter(PC_model)
summary(person.locations.estimate)##
## Estimation of Ability Parameters
##
## Collapsed log-likelihood: -762.6404
## Number of iterations: 23
## Number of parameters: 53
##
## ML estimated ability parameters (without spline interpolated values):
## Estimate Std. Err. 2.5 % 97.5 %
## theta P1 2.9099027 0.4367822 2.05382538 3.7659801
## theta P2 5.0236046 0.4846435 4.07372078 5.9734884
## theta P3 8.1973121 0.6286678 6.96514595 9.4294783
## theta P4 5.2526704 0.4725217 4.32654483 6.1787960
## theta P5 6.8621323 0.4550666 5.97021818 7.7540463
## theta P6 7.0751057 0.4688874 6.15610319 7.9941081
## theta P7 4.2768355 0.5064941 3.28412525 5.2695457
## theta P8 7.5566277 0.5182094 6.54095584 8.5722995
## theta P9 0.2271127 0.3364313 -0.43228053 0.8865059
## theta P10 6.0759531 0.4408006 5.21199976 6.9399064
## theta P11 5.6789698 0.4519690 4.79312687 6.5648127
## theta P12 7.5566277 0.5182094 6.54095584 8.5722995
## theta P13 1.6203574 0.3765068 0.88241770 2.3582971
## theta P14 8.6629875 0.7477750 7.19737548 10.1285994
## theta P15 1.3430238 0.3684305 0.62091334 2.0651343
## theta P16 1.3430238 0.3684305 0.62091334 2.0651343
## theta P17 -0.4226323 0.3237518 -1.05717415 0.2119095
## theta P18 4.7830281 0.4959376 3.81100829 5.7550479
## theta P19 7.3039033 0.4890592 6.34536497 8.2624417
## theta P20 7.0751057 0.4688874 6.15610319 7.9941081
## theta P21 9.4135838 1.0281352 7.39847585 11.4286917
## theta P22 4.0218528 0.5023461 3.03727263 5.0064330
## theta P23 9.4135838 1.0281352 7.39847585 11.4286917
## theta P24 8.6629875 0.7477750 7.19737548 10.1285994
## theta P25 5.8799611 0.4450514 5.00767636 6.7522458
## theta P26 5.2526704 0.4725217 4.32654483 6.1787960
## theta P27 0.6978842 0.3500391 0.01182012 1.3839482
## theta P28 7.5566277 0.5182094 6.54095584 8.5722995
## theta P29 6.6594599 0.4460877 5.78514403 7.5337757
## theta P30 7.5566277 0.5182094 6.54095584 8.5722995
## theta P31 7.0751057 0.4688874 6.15610319 7.9941081
## theta P32 6.4629882 0.4410467 5.59855263 7.3274238
## theta P33 6.6594599 0.4460877 5.78514403 7.5337757
## theta P34 6.2694295 0.4393957 5.40822980 7.1306293
## theta P35 5.6789698 0.4519690 4.79312687 6.5648127
## theta P36 6.0759531 0.4408006 5.21199976 6.9399064
## theta P37 6.8621323 0.4550666 5.97021818 7.7540463
## theta P38 6.2694295 0.4393957 5.40822980 7.1306293
## theta P39 6.4629882 0.4410467 5.59855263 7.3274238
## theta P40 8.6629875 0.7477750 7.19737548 10.1285994
## theta P41 5.0236046 0.4846435 4.07372078 5.9734884
## theta P42 6.0759531 0.4408006 5.21199976 6.9399064
## theta P43 5.4705942 0.4612957 4.56647127 6.3747171
## theta P44 4.7830281 0.4959376 3.81100829 5.7550479
## theta P45 4.0218528 0.5023461 3.03727263 5.0064330
## theta P46 1.4801882 0.3723398 0.75041560 2.2099607
## theta P47 5.0236046 0.4846435 4.07372078 5.9734884
## theta P48 5.2526704 0.4725217 4.32654483 6.1787960
## theta P49 4.5326604 0.5040050 3.54482884 5.5204920
## theta P50 4.5326604 0.5040050 3.54482884 5.5204920
## theta P51 4.5326604 0.5040050 3.54482884 5.5204920
## theta P52 7.3039033 0.4890592 6.34536497 8.2624417
## theta P53 7.3039033 0.4890592 6.34536497 8.2624417
## theta P54 7.5566277 0.5182094 6.54095584 8.5722995
## theta P55 8.1973121 0.6286678 6.96514595 9.4294783
## theta P56 1.9108742 0.3860809 1.15416949 2.6675790
## theta P57 1.3430238 0.3684305 0.62091334 2.0651343
## theta P58 3.7740540 0.4924670 2.80883632 4.7392716
## theta P59 4.7830281 0.4959376 3.81100829 5.7550479
## theta P60 4.2768355 0.5064941 3.28412525 5.2695457
## theta P61 7.5566277 0.5182094 6.54095584 8.5722995
## theta P62 4.0218528 0.5023461 3.03727263 5.0064330
## theta P63 4.0218528 0.5023461 3.03727263 5.0064330
## theta P64 8.1973121 0.6286678 6.96514595 9.4294783
## theta P65 4.7830281 0.4959376 3.81100829 5.7550479
## theta P66 4.0218528 0.5023461 3.03727263 5.0064330
## theta P67 3.7740540 0.4924670 2.80883632 4.7392716
## theta P68 -0.2113842 0.3265752 -0.85145990 0.4286914
## theta P69 6.2694295 0.4393957 5.40822980 7.1306293
## theta P70 6.6594599 0.4460877 5.78514403 7.5337757
## theta P71 6.4629882 0.4410467 5.59855263 7.3274238
## theta P72 3.7740540 0.4924670 2.80883632 4.7392716
## theta P73 4.5326604 0.5040050 3.54482884 5.5204920
## theta P74 5.6789698 0.4519690 4.79312687 6.5648127
## theta P75 6.6594599 0.4460877 5.78514403 7.5337757
## theta P76 6.0759531 0.4408006 5.21199976 6.9399064
## theta P77 6.6594599 0.4460877 5.78514403 7.5337757
## theta P78 3.1063982 0.4500073 2.22440009 3.9883964
## theta P79 4.5326604 0.5040050 3.54482884 5.5204920
## theta P80 6.6594599 0.4460877 5.78514403 7.5337757
## theta P81 5.4705942 0.4612957 4.56647127 6.3747171
## theta P82 9.4135838 1.0281352 7.39847585 11.4286917
## theta P83 5.0236046 0.4846435 4.07372078 5.9734884
## theta P84 5.2526704 0.4725217 4.32654483 6.1787960
## theta P85 7.3039033 0.4890592 6.34536497 8.2624417
## theta P86 6.4629882 0.4410467 5.59855263 7.3274238
## theta P87 3.5379049 0.4790624 2.59895986 4.4768499
## theta P88 4.7830281 0.4959376 3.81100829 5.7550479
## theta P89 0.3413646 0.3396065 -0.32425190 1.0069812
## theta P90 2.9099027 0.4367822 2.05382538 3.7659801
## theta P91 3.3153595 0.4643819 2.40518772 4.2255313
## theta P92 2.5481046 0.4148064 1.73509901 3.3611102
## theta P93 6.6594599 0.4460877 5.78514403 7.5337757
## theta P94 8.1973121 0.6286678 6.96514595 9.4294783
## theta P95 6.2694295 0.4393957 5.40822980 7.1306293
## theta P96 3.5379049 0.4790624 2.59895986 4.4768499
## theta P97 6.8621323 0.4550666 5.97021818 7.7540463
## theta P98 4.0218528 0.5023461 3.03727263 5.0064330
## theta P99 4.0218528 0.5023461 3.03727263 5.0064330
## theta P100 3.1063982 0.4500073 2.22440009 3.9883964
## theta P101 2.2181227 0.3983694 1.43733296 2.9989124
## theta P102 5.6789698 0.4519690 4.79312687 6.5648127
## theta P103 -1.4814798 0.3342466 -2.13659122 -0.8263684
## theta P104 6.0759531 0.4408006 5.21199976 6.9399064
## theta P105 9.4135838 1.0281352 7.39847585 11.4286917
## theta P106 7.3039033 0.4890592 6.34536497 8.2624417
## theta P107 4.7830281 0.4959376 3.81100829 5.7550479
## theta P108 4.0218528 0.5023461 3.03727263 5.0064330
## theta P109 2.5481046 0.4148064 1.73509901 3.3611102
## theta P110 4.7830281 0.4959376 3.81100829 5.7550479
## theta P111 4.0218528 0.5023461 3.03727263 5.0064330
## theta P112 0.3413646 0.3396065 -0.32425190 1.0069812
## theta P113 4.0218528 0.5023461 3.03727263 5.0064330
## theta P114 5.4705942 0.4612957 4.56647127 6.3747171
## theta P115 2.9099027 0.4367822 2.05382538 3.7659801
## theta P116 5.4705942 0.4612957 4.56647127 6.3747171
## theta P117 5.6789698 0.4519690 4.79312687 6.5648127
## theta P118 3.3153595 0.4643819 2.40518772 4.2255313
## theta P119 7.0751057 0.4688874 6.15610319 7.9941081
## theta P120 9.4135838 1.0281352 7.39847585 11.4286917
## theta P121 6.8621323 0.4550666 5.97021818 7.7540463
## theta P122 3.5379049 0.4790624 2.59895986 4.4768499
## theta P123 7.8463966 0.5612629 6.74634163 8.9464516
## theta P124 6.4629882 0.4410467 5.59855263 7.3274238
## theta P125 6.0759531 0.4408006 5.21199976 6.9399064
## theta P126 3.7740540 0.4924670 2.80883632 4.7392716
## theta P127 5.6789698 0.4519690 4.79312687 6.5648127
## theta P128 7.8463966 0.5612629 6.74634163 8.9464516
## theta P129 3.3153595 0.4643819 2.40518772 4.2255313
## theta P130 4.0218528 0.5023461 3.03727263 5.0064330
## theta P131 8.6629875 0.7477750 7.19737548 10.1285994
## theta P132 4.0218528 0.5023461 3.03727263 5.0064330
## theta P133 9.4135838 1.0281352 7.39847585 11.4286917
## theta P134 6.6594599 0.4460877 5.78514403 7.5337757
## theta P135 8.6629875 0.7477750 7.19737548 10.1285994
## theta P136 -1.3708219 0.3311289 -2.01982257 -0.7218211
## theta P137 7.5566277 0.5182094 6.54095584 8.5722995
## theta P138 3.1063982 0.4500073 2.22440009 3.9883964
## theta P139 4.7830281 0.4959376 3.81100829 5.7550479
## theta P140 4.0218528 0.5023461 3.03727263 5.0064330
## theta P141 6.8621323 0.4550666 5.97021818 7.7540463
## theta P142 5.6789698 0.4519690 4.79312687 6.5648127
## theta P143 2.9099027 0.4367822 2.05382538 3.7659801
## theta P144 1.9108742 0.3860809 1.15416949 2.6675790
## theta P145 4.7830281 0.4959376 3.81100829 5.7550479
## theta P146 -0.4226323 0.3237518 -1.05717415 0.2119095
## theta P147 1.3430238 0.3684305 0.62091334 2.0651343
## theta P148 3.7740540 0.4924670 2.80883632 4.7392716
## theta P149 8.6629875 0.7477750 7.19737548 10.1285994
## theta P150 7.8463966 0.5612629 6.74634163 8.9464516
## theta P151 7.5566277 0.5182094 6.54095584 8.5722995
## theta P152 8.1973121 0.6286678 6.96514595 9.4294783
## theta P153 8.6629875 0.7477750 7.19737548 10.1285994
## theta P154 5.2526704 0.4725217 4.32654483 6.1787960
## theta P155 5.2526704 0.4725217 4.32654483 6.1787960
## theta P156 3.1063982 0.4500073 2.22440009 3.9883964
## theta P157 -0.3174889 0.3249684 -0.95441529 0.3194376
## theta P158 0.9480847 0.3573081 0.24777370 1.6483957
## theta P159 4.2768355 0.5064941 3.28412525 5.2695457
## theta P160 6.0759531 0.4408006 5.21199976 6.9399064
## theta P161 5.6789698 0.4519690 4.79312687 6.5648127
## theta P162 6.0759531 0.4408006 5.21199976 6.9399064
## theta P163 6.4629882 0.4410467 5.59855263 7.3274238
## theta P164 3.7740540 0.4924670 2.80883632 4.7392716
## theta P165 7.5566277 0.5182094 6.54095584 8.5722995
## theta P166 2.7243315 0.4250374 1.89127353 3.5573895
## theta P167 4.0218528 0.5023461 3.03727263 5.0064330
## theta P168 3.7740540 0.4924670 2.80883632 4.7392716
## theta P169 2.9099027 0.4367822 2.05382538 3.7659801
## theta P170 4.7830281 0.4959376 3.81100829 5.7550479
## theta P171 6.4629882 0.4410467 5.59855263 7.3274238
## theta P172 5.0236046 0.4846435 4.07372078 5.9734884
## theta P173 4.7830281 0.4959376 3.81100829 5.7550479
## theta P174 8.6629875 0.7477750 7.19737548 10.1285994
## theta P175 2.9099027 0.4367822 2.05382538 3.7659801
## theta P176 2.9099027 0.4367822 2.05382538 3.7659801
## theta P177 5.4705942 0.4612957 4.56647127 6.3747171
## theta P178 7.5566277 0.5182094 6.54095584 8.5722995
## theta P179 6.8621323 0.4550666 5.97021818 7.7540463
## theta P180 2.5481046 0.4148064 1.73509901 3.3611102
## theta P181 6.6594599 0.4460877 5.78514403 7.5337757
## theta P182 8.6629875 0.7477750 7.19737548 10.1285994
## theta P183 5.8799611 0.4450514 5.00767636 6.7522458
## theta P184 4.5326604 0.5040050 3.54482884 5.5204920
## theta P185 7.8463966 0.5612629 6.74634163 8.9464516
## theta P186 1.2086875 0.3646656 0.49395594 1.9234190
## theta P187 2.2181227 0.3983694 1.43733296 2.9989124
## theta P188 1.3430238 0.3684305 0.62091334 2.0651343
## theta P189 6.0759531 0.4408006 5.21199976 6.9399064
## theta P190 6.6594599 0.4460877 5.78514403 7.5337757
## theta P191 1.3430238 0.3684305 0.62091334 2.0651343
## theta P192 5.0236046 0.4846435 4.07372078 5.9734884
## theta P193 6.8621323 0.4550666 5.97021818 7.7540463
## theta P194 6.2694295 0.4393957 5.40822980 7.1306293
## theta P195 0.6978842 0.3500391 0.01182012 1.3839482
## theta P196 6.8621323 0.4550666 5.97021818 7.7540463
## theta P197 9.4135838 1.0281352 7.39847585 11.4286917
## theta P198 3.1063982 0.4500073 2.22440009 3.9883964
## theta P199 4.0218528 0.5023461 3.03727263 5.0064330
## theta P200 4.5326604 0.5040050 3.54482884 5.5204920
## theta P201 0.6978842 0.3500391 0.01182012 1.3839482
## theta P202 3.1063982 0.4500073 2.22440009 3.9883964
## theta P203 5.0236046 0.4846435 4.07372078 5.9734884
## theta P204 5.2526704 0.4725217 4.32654483 6.1787960
## theta P205 7.0751057 0.4688874 6.15610319 7.9941081
## theta P206 3.5379049 0.4790624 2.59895986 4.4768499
## theta P207 3.7740540 0.4924670 2.80883632 4.7392716
## theta P208 2.7243315 0.4250374 1.89127353 3.5573895
## theta P209 2.9099027 0.4367822 2.05382538 3.7659801
## theta P210 5.2526704 0.4725217 4.32654483 6.1787960
## theta P211 6.4629882 0.4410467 5.59855263 7.3274238
## theta P212 1.9108742 0.3860809 1.15416949 2.6675790
## theta P213 9.4135838 1.0281352 7.39847585 11.4286917
## theta P214 4.2768355 0.5064941 3.28412525 5.2695457
## theta P215 2.9099027 0.4367822 2.05382538 3.7659801
## theta P216 9.4135838 1.0281352 7.39847585 11.4286917
## theta P217 6.0759531 0.4408006 5.21199976 6.9399064
## theta P218 4.7830281 0.4959376 3.81100829 5.7550479
## theta P219 7.5566277 0.5182094 6.54095584 8.5722995
## theta P220 6.4629882 0.4410467 5.59855263 7.3274238
## theta P221 4.5326604 0.5040050 3.54482884 5.5204920
## theta P222 4.0218528 0.5023461 3.03727263 5.0064330
## theta P223 -1.4814798 0.3342466 -2.13659122 -0.8263684
## theta P224 9.4135838 1.0281352 7.39847585 11.4286917
## theta P225 3.3153595 0.4643819 2.40518772 4.2255313
## theta P226 7.5566277 0.5182094 6.54095584 8.5722995
## theta P227 4.5326604 0.5040050 3.54482884 5.5204920
## theta P228 8.1973121 0.6286678 6.96514595 9.4294783
## theta P229 5.4705942 0.4612957 4.56647127 6.3747171
## theta P230 5.0236046 0.4846435 4.07372078 5.9734884
## theta P231 6.0759531 0.4408006 5.21199976 6.9399064
## theta P232 4.5326604 0.5040050 3.54482884 5.5204920
## theta P233 5.0236046 0.4846435 4.07372078 5.9734884
## theta P234 1.9108742 0.3860809 1.15416949 2.6675790
## theta P235 3.3153595 0.4643819 2.40518772 4.2255313
## theta P236 5.8799611 0.4450514 5.00767636 6.7522458
## theta P237 4.0218528 0.5023461 3.03727263 5.0064330
## theta P238 7.5566277 0.5182094 6.54095584 8.5722995
## theta P239 2.7243315 0.4250374 1.89127353 3.5573895
## theta P240 7.8463966 0.5612629 6.74634163 8.9464516
## theta P241 8.6629875 0.7477750 7.19737548 10.1285994
## theta P242 7.3039033 0.4890592 6.34536497 8.2624417
## theta P243 0.9480847 0.3573081 0.24777370 1.6483957
## theta P244 8.6629875 0.7477750 7.19737548 10.1285994
## theta P245 1.2086875 0.3646656 0.49395594 1.9234190
## theta P246 5.2526704 0.4725217 4.32654483 6.1787960
## theta P247 5.2526704 0.4725217 4.32654483 6.1787960
## theta P248 4.2768355 0.5064941 3.28412525 5.2695457
## theta P249 5.6789698 0.4519690 4.79312687 6.5648127
## theta P250 6.8621323 0.4550666 5.97021818 7.7540463
## theta P251 -0.7352463 0.3224480 -1.36723281 -0.1032598
## theta P252 2.3797817 0.4059717 1.58409187 3.1754715
## theta P253 8.6629875 0.7477750 7.19737548 10.1285994
## theta P254 1.0770654 0.3609751 0.36956719 1.7845637
## theta P255 5.6789698 0.4519690 4.79312687 6.5648127
## theta P256 -2.4947796 0.3870839 -3.25345020 -1.7361091
## theta P257 -2.0784858 0.3598280 -2.78373563 -1.3732359
## theta P258 -1.4814798 0.3342466 -2.13659122 -0.8263684
## theta P259 5.2526704 0.4725217 4.32654483 6.1787960
## theta P260 2.0620978 0.3917998 1.29418432 2.8300112
## theta P261 7.5566277 0.5182094 6.54095584 8.5722995
## theta P262 1.9108742 0.3860809 1.15416949 2.6675790
## theta P263 6.2694295 0.4393957 5.40822980 7.1306293
## theta P264 3.1063982 0.4500073 2.22440009 3.9883964
## theta P265 4.0218528 0.5023461 3.03727263 5.0064330
## theta P266 2.3797817 0.4059717 1.58409187 3.1754715
## theta P267 3.3153595 0.4643819 2.40518772 4.2255313
## theta P268 2.2181227 0.3983694 1.43733296 2.9989124
## theta P269 1.9108742 0.3860809 1.15416949 2.6675790
## theta P270 6.8621323 0.4550666 5.97021818 7.7540463
## theta P271 5.6789698 0.4519690 4.79312687 6.5648127
## theta P272 8.6629875 0.7477750 7.19737548 10.1285994
## theta P273 -0.4226323 0.3237518 -1.05717415 0.2119095
## theta P274 4.5326604 0.5040050 3.54482884 5.5204920
## theta P275 5.8799611 0.4450514 5.00767636 6.7522458
## theta P276 5.6789698 0.4519690 4.79312687 6.5648127
## theta P277 4.2768355 0.5064941 3.28412525 5.2695457
## theta P278 7.0751057 0.4688874 6.15610319 7.9941081
## theta P279 0.2271127 0.3364313 -0.43228053 0.8865059
## theta P280 2.9099027 0.4367822 2.05382538 3.7659801
## theta P281 7.8463966 0.5612629 6.74634163 8.9464516
## theta P282 4.0218528 0.5023461 3.03727263 5.0064330
## theta P283 7.3039033 0.4890592 6.34536497 8.2624417
## theta P284 8.1973121 0.6286678 6.96514595 9.4294783
## theta P285 7.3039033 0.4890592 6.34536497 8.2624417
## theta P286 7.0751057 0.4688874 6.15610319 7.9941081
## theta P287 8.6629875 0.7477750 7.19737548 10.1285994
## theta P288 3.3153595 0.4643819 2.40518772 4.2255313
## theta P289 3.5379049 0.4790624 2.59895986 4.4768499
## theta P290 5.6789698 0.4519690 4.79312687 6.5648127
## theta P291 6.0759531 0.4408006 5.21199976 6.9399064
## theta P292 7.5566277 0.5182094 6.54095584 8.5722995
## theta P293 7.8463966 0.5612629 6.74634163 8.9464516
## theta P294 6.2694295 0.4393957 5.40822980 7.1306293
## theta P295 8.1973121 0.6286678 6.96514595 9.4294783
## theta P296 6.0759531 0.4408006 5.21199976 6.9399064
## theta P297 3.3153595 0.4643819 2.40518772 4.2255313
## theta P298 3.7740540 0.4924670 2.80883632 4.7392716
## theta P299 5.4705942 0.4612957 4.56647127 6.3747171
## theta P300 5.8799611 0.4450514 5.00767636 6.7522458
## theta P301 5.8799611 0.4450514 5.00767636 6.7522458
## theta P302 8.1973121 0.6286678 6.96514595 9.4294783
## theta P303 7.3039033 0.4890592 6.34536497 8.2624417
## theta P304 5.6789698 0.4519690 4.79312687 6.5648127
## theta P305 6.8621323 0.4550666 5.97021818 7.7540463
## theta P306 3.7740540 0.4924670 2.80883632 4.7392716
## theta P307 5.6789698 0.4519690 4.79312687 6.5648127
## theta P308 3.3153595 0.4643819 2.40518772 4.2255313
## theta P309 -4.7648089 0.7535721 -6.24178309 -3.2878347
## theta P310 5.2526704 0.4725217 4.32654483 6.1787960
## theta P311 4.0218528 0.5023461 3.03727263 5.0064330
## theta P312 6.8621323 0.4550666 5.97021818 7.7540463
## theta P313 7.8463966 0.5612629 6.74634163 8.9464516
## theta P314 8.1973121 0.6286678 6.96514595 9.4294783
## theta P315 3.1063982 0.4500073 2.22440009 3.9883964
## theta P316 6.6594599 0.4460877 5.78514403 7.5337757
## theta P317 9.4135838 1.0281352 7.39847585 11.4286917
## theta P318 3.3153595 0.4643819 2.40518772 4.2255313
## theta P319 6.8621323 0.4550666 5.97021818 7.7540463
## theta P320 5.0236046 0.4846435 4.07372078 5.9734884
## theta P321 6.8621323 0.4550666 5.97021818 7.7540463
## theta P322 8.6629875 0.7477750 7.19737548 10.1285994
## theta P323 0.6978842 0.3500391 0.01182012 1.3839482
## theta P324 4.5326604 0.5040050 3.54482884 5.5204920
## theta P325 -0.3174889 0.3249684 -0.95441529 0.3194376
## theta P326 4.5326604 0.5040050 3.54482884 5.5204920
## theta P327 7.5566277 0.5182094 6.54095584 8.5722995
## theta P328 6.4629882 0.4410467 5.59855263 7.3274238
## theta P329 9.4135838 1.0281352 7.39847585 11.4286917
## theta P330 8.1973121 0.6286678 6.96514595 9.4294783
## theta P331 7.3039033 0.4890592 6.34536497 8.2624417
## theta P332 9.4135838 1.0281352 7.39847585 11.4286917
## theta P333 4.7830281 0.4959376 3.81100829 5.7550479
## theta P334 7.3039033 0.4890592 6.34536497 8.2624417
## theta P335 4.7830281 0.4959376 3.81100829 5.7550479
## theta P336 4.0218528 0.5023461 3.03727263 5.0064330
## theta P337 4.5326604 0.5040050 3.54482884 5.5204920
## theta P338 8.6629875 0.7477750 7.19737548 10.1285994
## theta P339 0.4578098 0.3429687 -0.21439649 1.1300162
## theta P340 5.8799611 0.4450514 5.00767636 6.7522458
## theta P341 8.1973121 0.6286678 6.96514595 9.4294783
## theta P342 3.7740540 0.4924670 2.80883632 4.7392716
## theta P343 8.1973121 0.6286678 6.96514595 9.4294783
## theta P344 9.4135838 1.0281352 7.39847585 11.4286917
## theta P345 8.6629875 0.7477750 7.19737548 10.1285994
## theta P346 3.5379049 0.4790624 2.59895986 4.4768499
## theta P347 5.6789698 0.4519690 4.79312687 6.5648127
## theta P348 6.8621323 0.4550666 5.97021818 7.7540463
## theta P349 5.6789698 0.4519690 4.79312687 6.5648127
## theta P350 3.3153595 0.4643819 2.40518772 4.2255313
## theta P351 2.0620978 0.3917998 1.29418432 2.8300112
## theta P352 6.6594599 0.4460877 5.78514403 7.5337757
## theta P353 9.4135838 1.0281352 7.39847585 11.4286917
## theta P354 7.3039033 0.4890592 6.34536497 8.2624417
## theta P355 2.2181227 0.3983694 1.43733296 2.9989124
## theta P356 8.6629875 0.7477750 7.19737548 10.1285994
## theta P357 6.8621323 0.4550666 5.97021818 7.7540463
## theta P358 5.6789698 0.4519690 4.79312687 6.5648127
## theta P359 4.5326604 0.5040050 3.54482884 5.5204920
## theta P360 1.2086875 0.3646656 0.49395594 1.9234190
## theta P361 -3.1878458 0.4525445 -4.07481679 -2.3008749
## theta P362 4.5326604 0.5040050 3.54482884 5.5204920
## theta P363 -0.7352463 0.3224480 -1.36723281 -0.1032598
## theta P364 1.9108742 0.3860809 1.15416949 2.6675790
## theta P365 5.8799611 0.4450514 5.00767636 6.7522458
## theta P366 -3.1878458 0.4525445 -4.07481679 -2.3008749
## theta P367 6.2694295 0.4393957 5.40822980 7.1306293
## theta P368 5.8799611 0.4450514 5.00767636 6.7522458
## theta P369 5.6789698 0.4519690 4.79312687 6.5648127
## theta P370 6.8621323 0.4550666 5.97021818 7.7540463
## theta P371 6.6594599 0.4460877 5.78514403 7.5337757
## theta P372 8.6629875 0.7477750 7.19737548 10.1285994
## theta P373 2.0620978 0.3917998 1.29418432 2.8300112
## theta P374 1.3430238 0.3684305 0.62091334 2.0651343
## theta P375 7.8463966 0.5612629 6.74634163 8.9464516
## theta P376 4.5326604 0.5040050 3.54482884 5.5204920
## theta P377 1.4801882 0.3723398 0.75041560 2.2099607
## theta P378 9.4135838 1.0281352 7.39847585 11.4286917
## theta P379 7.3039033 0.4890592 6.34536497 8.2624417
## theta P380 1.9108742 0.3860809 1.15416949 2.6675790
## theta P381 8.1973121 0.6286678 6.96514595 9.4294783
## theta P382 2.7243315 0.4250374 1.89127353 3.5573895
## theta P383 4.5326604 0.5040050 3.54482884 5.5204920
## theta P384 2.5481046 0.4148064 1.73509901 3.3611102
## theta P385 4.7830281 0.4959376 3.81100829 5.7550479
## theta P386 7.0751057 0.4688874 6.15610319 7.9941081
## theta P387 3.5379049 0.4790624 2.59895986 4.4768499
## theta P388 3.3153595 0.4643819 2.40518772 4.2255313
## theta P389 6.4629882 0.4410467 5.59855263 7.3274238
## theta P390 3.3153595 0.4643819 2.40518772 4.2255313
## theta P391 5.6789698 0.4519690 4.79312687 6.5648127
## theta P392 5.6789698 0.4519690 4.79312687 6.5648127
## theta P393 5.4705942 0.4612957 4.56647127 6.3747171
## theta P394 4.7830281 0.4959376 3.81100829 5.7550479
## theta P395 9.4135838 1.0281352 7.39847585 11.4286917
## theta P396 8.6629875 0.7477750 7.19737548 10.1285994
## theta P397 -0.3174889 0.3249684 -0.95441529 0.3194376
## theta P398 1.7637954 0.3810392 1.01697222 2.5106186
## theta P399 5.0236046 0.4846435 4.07372078 5.9734884
## theta P400 4.0218528 0.5023461 3.03727263 5.0064330# Build a table for person locations
person_theta <- person.locations.estimate$theta.table
person_theta## Person Parameter NAgroup Interpolated
## P1 2.9099027 1 FALSE
## P2 5.0236046 1 FALSE
## P3 8.1973121 1 FALSE
## P4 5.2526704 1 FALSE
## P5 6.8621323 1 FALSE
## P6 7.0751057 1 FALSE
## P7 4.2768355 1 FALSE
## P8 7.5566277 1 FALSE
## P9 0.2271127 1 FALSE
## P10 6.0759531 1 FALSE
## P11 5.6789698 1 FALSE
## P12 7.5566277 1 FALSE
## P13 1.6203574 1 FALSE
## P14 8.6629875 1 FALSE
## P15 1.3430238 1 FALSE
## P16 1.3430238 1 FALSE
## P17 -0.4226323 1 FALSE
## P18 4.7830281 1 FALSE
## P19 7.3039033 1 FALSE
## P20 7.0751057 1 FALSE
## P21 9.4135838 1 FALSE
## P22 4.0218528 1 FALSE
## P23 9.4135838 1 FALSE
## P24 8.6629875 1 FALSE
## P25 5.8799611 1 FALSE
## P26 5.2526704 1 FALSE
## P27 0.6978842 1 FALSE
## P28 7.5566277 1 FALSE
## P29 6.6594599 1 FALSE
## P30 7.5566277 1 FALSE
## P31 7.0751057 1 FALSE
## P32 6.4629882 1 FALSE
## P33 6.6594599 1 FALSE
## P34 6.2694295 1 FALSE
## P35 5.6789698 1 FALSE
## P36 6.0759531 1 FALSE
## P37 6.8621323 1 FALSE
## P38 6.2694295 1 FALSE
## P39 6.4629882 1 FALSE
## P40 8.6629875 1 FALSE
## P41 5.0236046 1 FALSE
## P42 6.0759531 1 FALSE
## P43 5.4705942 1 FALSE
## P44 4.7830281 1 FALSE
## P45 4.0218528 1 FALSE
## P46 1.4801882 1 FALSE
## P47 5.0236046 1 FALSE
## P48 5.2526704 1 FALSE
## P49 4.5326604 1 FALSE
## P50 4.5326604 1 FALSE
## P51 4.5326604 1 FALSE
## P52 7.3039033 1 FALSE
## P53 7.3039033 1 FALSE
## P54 7.5566277 1 FALSE
## P55 8.1973121 1 FALSE
## P56 1.9108742 1 FALSE
## P57 1.3430238 1 FALSE
## P58 3.7740540 1 FALSE
## P59 4.7830281 1 FALSE
## P60 4.2768355 1 FALSE
## P61 7.5566277 1 FALSE
## P62 4.0218528 1 FALSE
## P63 4.0218528 1 FALSE
## P64 8.1973121 1 FALSE
## P65 4.7830281 1 FALSE
## P66 4.0218528 1 FALSE
## P67 3.7740540 1 FALSE
## P68 -0.2113842 1 FALSE
## P69 6.2694295 1 FALSE
## P70 6.6594599 1 FALSE
## P71 6.4629882 1 FALSE
## P72 3.7740540 1 FALSE
## P73 4.5326604 1 FALSE
## P74 5.6789698 1 FALSE
## P75 6.6594599 1 FALSE
## P76 6.0759531 1 FALSE
## P77 6.6594599 1 FALSE
## P78 3.1063982 1 FALSE
## P79 4.5326604 1 FALSE
## P80 6.6594599 1 FALSE
## P81 5.4705942 1 FALSE
## P82 9.4135838 1 FALSE
## P83 5.0236046 1 FALSE
## P84 5.2526704 1 FALSE
## P85 7.3039033 1 FALSE
## P86 6.4629882 1 FALSE
## P87 3.5379049 1 FALSE
## P88 4.7830281 1 FALSE
## P89 0.3413646 1 FALSE
## P90 2.9099027 1 FALSE
## P91 3.3153595 1 FALSE
## P92 2.5481046 1 FALSE
## P93 6.6594599 1 FALSE
## P94 8.1973121 1 FALSE
## P95 6.2694295 1 FALSE
## P96 3.5379049 1 FALSE
## P97 6.8621323 1 FALSE
## P98 4.0218528 1 FALSE
## P99 4.0218528 1 FALSE
## P100 3.1063982 1 FALSE
## P101 2.2181227 1 FALSE
## P102 5.6789698 1 FALSE
## P103 -1.4814798 1 FALSE
## P104 6.0759531 1 FALSE
## P105 9.4135838 1 FALSE
## P106 7.3039033 1 FALSE
## P107 4.7830281 1 FALSE
## P108 4.0218528 1 FALSE
## P109 2.5481046 1 FALSE
## P110 4.7830281 1 FALSE
## P111 4.0218528 1 FALSE
## P112 0.3413646 1 FALSE
## P113 4.0218528 1 FALSE
## P114 5.4705942 1 FALSE
## P115 2.9099027 1 FALSE
## P116 5.4705942 1 FALSE
## P117 5.6789698 1 FALSE
## P118 3.3153595 1 FALSE
## P119 7.0751057 1 FALSE
## P120 9.4135838 1 FALSE
## P121 6.8621323 1 FALSE
## P122 3.5379049 1 FALSE
## P123 7.8463966 1 FALSE
## P124 6.4629882 1 FALSE
## P125 6.0759531 1 FALSE
## P126 3.7740540 1 FALSE
## P127 5.6789698 1 FALSE
## P128 7.8463966 1 FALSE
## P129 3.3153595 1 FALSE
## P130 4.0218528 1 FALSE
## P131 8.6629875 1 FALSE
## P132 4.0218528 1 FALSE
## P133 9.4135838 1 FALSE
## P134 6.6594599 1 FALSE
## P135 8.6629875 1 FALSE
## P136 -1.3708219 1 FALSE
## P137 7.5566277 1 FALSE
## P138 3.1063982 1 FALSE
## P139 4.7830281 1 FALSE
## P140 4.0218528 1 FALSE
## P141 6.8621323 1 FALSE
## P142 5.6789698 1 FALSE
## P143 2.9099027 1 FALSE
## P144 1.9108742 1 FALSE
## P145 4.7830281 1 FALSE
## P146 -0.4226323 1 FALSE
## P147 1.3430238 1 FALSE
## P148 3.7740540 1 FALSE
## P149 8.6629875 1 FALSE
## P150 7.8463966 1 FALSE
## P151 7.5566277 1 FALSE
## P152 8.1973121 1 FALSE
## P153 8.6629875 1 FALSE
## P154 5.2526704 1 FALSE
## P155 5.2526704 1 FALSE
## P156 3.1063982 1 FALSE
## P157 -0.3174889 1 FALSE
## P158 0.9480847 1 FALSE
## P159 4.2768355 1 FALSE
## P160 6.0759531 1 FALSE
## P161 5.6789698 1 FALSE
## P162 6.0759531 1 FALSE
## P163 6.4629882 1 FALSE
## P164 3.7740540 1 FALSE
## P165 7.5566277 1 FALSE
## P166 2.7243315 1 FALSE
## P167 4.0218528 1 FALSE
## P168 3.7740540 1 FALSE
## P169 2.9099027 1 FALSE
## P170 4.7830281 1 FALSE
## P171 6.4629882 1 FALSE
## P172 5.0236046 1 FALSE
## P173 4.7830281 1 FALSE
## P174 8.6629875 1 FALSE
## P175 2.9099027 1 FALSE
## P176 2.9099027 1 FALSE
## P177 5.4705942 1 FALSE
## P178 7.5566277 1 FALSE
## P179 6.8621323 1 FALSE
## P180 2.5481046 1 FALSE
## P181 6.6594599 1 FALSE
## P182 8.6629875 1 FALSE
## P183 5.8799611 1 FALSE
## P184 4.5326604 1 FALSE
## P185 7.8463966 1 FALSE
## P186 1.2086875 1 FALSE
## P187 2.2181227 1 FALSE
## P188 1.3430238 1 FALSE
## P189 6.0759531 1 FALSE
## P190 6.6594599 1 FALSE
## P191 1.3430238 1 FALSE
## P192 5.0236046 1 FALSE
## P193 6.8621323 1 FALSE
## P194 6.2694295 1 FALSE
## P195 0.6978842 1 FALSE
## P196 6.8621323 1 FALSE
## P197 9.4135838 1 FALSE
## P198 3.1063982 1 FALSE
## P199 4.0218528 1 FALSE
## P200 4.5326604 1 FALSE
## P201 0.6978842 1 FALSE
## P202 3.1063982 1 FALSE
## P203 5.0236046 1 FALSE
## P204 5.2526704 1 FALSE
## P205 7.0751057 1 FALSE
## P206 3.5379049 1 FALSE
## P207 3.7740540 1 FALSE
## P208 2.7243315 1 FALSE
## P209 2.9099027 1 FALSE
## P210 5.2526704 1 FALSE
## P211 6.4629882 1 FALSE
## P212 1.9108742 1 FALSE
## P213 9.4135838 1 FALSE
## P214 4.2768355 1 FALSE
## P215 2.9099027 1 FALSE
## P216 9.4135838 1 FALSE
## P217 6.0759531 1 FALSE
## P218 4.7830281 1 FALSE
## P219 7.5566277 1 FALSE
## P220 6.4629882 1 FALSE
## P221 4.5326604 1 FALSE
## P222 4.0218528 1 FALSE
## P223 -1.4814798 1 FALSE
## P224 9.4135838 1 FALSE
## P225 3.3153595 1 FALSE
## P226 7.5566277 1 FALSE
## P227 4.5326604 1 FALSE
## P228 8.1973121 1 FALSE
## P229 5.4705942 1 FALSE
## P230 5.0236046 1 FALSE
## P231 6.0759531 1 FALSE
## P232 4.5326604 1 FALSE
## P233 5.0236046 1 FALSE
## P234 1.9108742 1 FALSE
## P235 3.3153595 1 FALSE
## P236 5.8799611 1 FALSE
## P237 4.0218528 1 FALSE
## P238 7.5566277 1 FALSE
## P239 2.7243315 1 FALSE
## P240 7.8463966 1 FALSE
## P241 8.6629875 1 FALSE
## P242 7.3039033 1 FALSE
## P243 0.9480847 1 FALSE
## P244 8.6629875 1 FALSE
## P245 1.2086875 1 FALSE
## P246 5.2526704 1 FALSE
## P247 5.2526704 1 FALSE
## P248 4.2768355 1 FALSE
## P249 5.6789698 1 FALSE
## P250 6.8621323 1 FALSE
## P251 -0.7352463 1 FALSE
## P252 2.3797817 1 FALSE
## P253 8.6629875 1 FALSE
## P254 1.0770654 1 FALSE
## P255 5.6789698 1 FALSE
## P256 -2.4947796 1 FALSE
## P257 -2.0784858 1 FALSE
## P258 -1.4814798 1 FALSE
## P259 5.2526704 1 FALSE
## P260 2.0620978 1 FALSE
## P261 7.5566277 1 FALSE
## P262 1.9108742 1 FALSE
## P263 6.2694295 1 FALSE
## P264 3.1063982 1 FALSE
## P265 4.0218528 1 FALSE
## P266 2.3797817 1 FALSE
## P267 3.3153595 1 FALSE
## P268 2.2181227 1 FALSE
## P269 1.9108742 1 FALSE
## P270 6.8621323 1 FALSE
## P271 5.6789698 1 FALSE
## P272 8.6629875 1 FALSE
## P273 -0.4226323 1 FALSE
## P274 4.5326604 1 FALSE
## P275 5.8799611 1 FALSE
## P276 5.6789698 1 FALSE
## P277 4.2768355 1 FALSE
## P278 7.0751057 1 FALSE
## P279 0.2271127 1 FALSE
## P280 2.9099027 1 FALSE
## P281 7.8463966 1 FALSE
## P282 4.0218528 1 FALSE
## P283 7.3039033 1 FALSE
## P284 8.1973121 1 FALSE
## P285 7.3039033 1 FALSE
## P286 7.0751057 1 FALSE
## P287 8.6629875 1 FALSE
## P288 3.3153595 1 FALSE
## P289 3.5379049 1 FALSE
## P290 5.6789698 1 FALSE
## P291 6.0759531 1 FALSE
## P292 7.5566277 1 FALSE
## P293 7.8463966 1 FALSE
## P294 6.2694295 1 FALSE
## P295 8.1973121 1 FALSE
## P296 6.0759531 1 FALSE
## P297 3.3153595 1 FALSE
## P298 3.7740540 1 FALSE
## P299 5.4705942 1 FALSE
## P300 5.8799611 1 FALSE
## P301 5.8799611 1 FALSE
## P302 8.1973121 1 FALSE
## P303 7.3039033 1 FALSE
## P304 5.6789698 1 FALSE
## P305 6.8621323 1 FALSE
## P306 3.7740540 1 FALSE
## P307 5.6789698 1 FALSE
## P308 3.3153595 1 FALSE
## P309 -4.7648089 1 FALSE
## P310 5.2526704 1 FALSE
## P311 4.0218528 1 FALSE
## P312 6.8621323 1 FALSE
## P313 7.8463966 1 FALSE
## P314 8.1973121 1 FALSE
## P315 3.1063982 1 FALSE
## P316 6.6594599 1 FALSE
## P317 9.4135838 1 FALSE
## P318 3.3153595 1 FALSE
## P319 6.8621323 1 FALSE
## P320 5.0236046 1 FALSE
## P321 6.8621323 1 FALSE
## P322 8.6629875 1 FALSE
## P323 0.6978842 1 FALSE
## P324 4.5326604 1 FALSE
## P325 -0.3174889 1 FALSE
## P326 4.5326604 1 FALSE
## P327 7.5566277 1 FALSE
## P328 6.4629882 1 FALSE
## P329 9.4135838 1 FALSE
## P330 8.1973121 1 FALSE
## P331 7.3039033 1 FALSE
## P332 9.4135838 1 FALSE
## P333 4.7830281 1 FALSE
## P334 7.3039033 1 FALSE
## P335 4.7830281 1 FALSE
## P336 4.0218528 1 FALSE
## P337 4.5326604 1 FALSE
## P338 8.6629875 1 FALSE
## P339 0.4578098 1 FALSE
## P340 5.8799611 1 FALSE
## P341 8.1973121 1 FALSE
## P342 3.7740540 1 FALSE
## P343 8.1973121 1 FALSE
## P344 9.4135838 1 FALSE
## P345 8.6629875 1 FALSE
## P346 3.5379049 1 FALSE
## P347 5.6789698 1 FALSE
## P348 6.8621323 1 FALSE
## P349 5.6789698 1 FALSE
## P350 3.3153595 1 FALSE
## P351 2.0620978 1 FALSE
## P352 6.6594599 1 FALSE
## P353 9.4135838 1 FALSE
## P354 7.3039033 1 FALSE
## P355 2.2181227 1 FALSE
## P356 8.6629875 1 FALSE
## P357 6.8621323 1 FALSE
## P358 5.6789698 1 FALSE
## P359 4.5326604 1 FALSE
## P360 1.2086875 1 FALSE
## P361 -3.1878458 1 FALSE
## P362 4.5326604 1 FALSE
## P363 -0.7352463 1 FALSE
## P364 1.9108742 1 FALSE
## P365 5.8799611 1 FALSE
## P366 -3.1878458 1 FALSE
## P367 6.2694295 1 FALSE
## P368 5.8799611 1 FALSE
## P369 5.6789698 1 FALSE
## P370 6.8621323 1 FALSE
## P371 6.6594599 1 FALSE
## P372 8.6629875 1 FALSE
## P373 2.0620978 1 FALSE
## P374 1.3430238 1 FALSE
## P375 7.8463966 1 FALSE
## P376 4.5326604 1 FALSE
## P377 1.4801882 1 FALSE
## P378 9.4135838 1 FALSE
## P379 7.3039033 1 FALSE
## P380 1.9108742 1 FALSE
## P381 8.1973121 1 FALSE
## P382 2.7243315 1 FALSE
## P383 4.5326604 1 FALSE
## P384 2.5481046 1 FALSE
## P385 4.7830281 1 FALSE
## P386 7.0751057 1 FALSE
## P387 3.5379049 1 FALSE
## P388 3.3153595 1 FALSE
## P389 6.4629882 1 FALSE
## P390 3.3153595 1 FALSE
## P391 5.6789698 1 FALSE
## P392 5.6789698 1 FALSE
## P393 5.4705942 1 FALSE
## P394 4.7830281 1 FALSE
## P395 9.4135838 1 FALSE
## P396 8.6629875 1 FALSE
## P397 -0.3174889 1 FALSE
## P398 1.7637954 1 FALSE
## P399 5.0236046 1 FALSE
## P400 4.0218528 1 FALSEExam the item and person fit statistics
item.fit <- itemfit(person.locations.estimate)
item.fit##
## Itemfit Statistics:
## Chisq df p-value Outfit MSQ Infit MSQ Outfit t Infit t Discrim
## JS58 356.646 399 0.937 0.892 0.919 -1.120 -1.059 0.818
## JS59 342.431 399 0.981 0.856 0.897 -1.736 -1.441 0.828
## JS60 387.176 399 0.655 0.968 0.936 -0.344 -0.869 0.826
## JS61 468.573 399 0.009 1.171 1.150 1.864 1.968 0.760
## JS62 386.249 399 0.667 0.966 0.965 -0.397 -0.463 0.818
## JS63 360.234 399 0.919 0.901 0.896 -0.954 -1.351 0.824
## JS64 430.890 399 0.131 1.077 1.032 0.969 0.463 0.801
## JS65 252.026 399 1.000 0.630 0.677 -4.934 -4.816 0.885
## JS66 341.759 399 0.982 0.854 0.881 -1.799 -1.632 0.841
## JS67 368.033 399 0.865 0.920 0.952 -0.966 -0.636 0.804
## JS68 303.646 399 1.000 0.759 0.867 -2.353 -1.722 0.833
## JS69 300.188 399 1.000 0.750 0.768 -2.943 -3.259 0.870
## JS70 462.627 399 0.015 1.157 1.093 1.694 1.271 0.762
## JS71 549.288 399 0.000 1.373 1.330 4.175 4.255 0.692
## JS72 295.329 399 1.000 0.738 0.792 -2.856 -2.934 0.851
## JS73 533.389 399 0.000 1.333 1.213 3.127 2.687 0.746
## JS74 309.713 399 1.000 0.774 0.766 -2.761 -3.356 0.854
## JS75 293.563 399 1.000 0.734 0.775 -2.962 -2.998 0.870
## JS76 517.127 399 0.000 1.293 1.293 2.972 3.622 0.721
## JS77 348.297 399 0.968 0.871 0.947 -1.357 -0.689 0.801pfit <- personfit(person.locations.estimate)
pfit##
## Personfit Statistics:
## Chisq df p-value Outfit MSQ Infit MSQ Outfit t Infit t
## P1 12.771 19 0.850 0.639 0.692 -1.07 -0.93
## P2 21.505 19 0.310 1.075 1.038 0.32 0.22
## P3 21.922 19 0.288 1.096 1.045 0.35 0.25
## P4 17.250 19 0.573 0.862 0.807 -0.31 -0.51
## P5 16.418 19 0.629 0.821 0.823 -1.04 -1.07
## P6 19.550 19 0.422 0.977 0.972 -0.04 -0.08
## P7 8.401 19 0.982 0.420 0.436 -1.49 -1.44
## P8 19.442 19 0.429 0.972 1.002 0.01 0.10
## P9 30.536 19 0.045 1.527 1.395 1.51 1.22
## P10 16.429 19 0.628 0.821 0.826 -0.93 -0.91
## P11 13.489 19 0.813 0.674 0.686 -1.34 -1.32
## P12 19.741 19 0.410 0.987 1.008 0.06 0.12
## P13 20.858 19 0.345 1.043 0.994 0.24 0.09
## P14 24.096 19 0.192 1.205 1.029 0.51 0.25
## P15 7.877 19 0.988 0.394 0.387 -2.41 -2.41
## P16 6.863 19 0.995 0.343 0.331 -2.72 -2.75
## P17 35.349 19 0.013 1.767 1.589 2.22 1.83
## P18 10.307 19 0.945 0.515 0.500 -1.29 -1.36
## P19 18.932 19 0.461 0.947 0.946 -0.14 -0.16
## P20 20.346 19 0.374 1.017 1.013 0.15 0.13
## P21 13.169 19 0.830 0.658 0.954 -0.07 0.26
## P22 3.572 19 1.000 0.179 0.210 -2.70 -2.55
## P23 27.520 19 0.093 1.376 1.037 0.67 0.35
## P24 20.310 19 0.376 1.015 1.019 0.24 0.23
## P25 23.971 19 0.197 1.199 1.205 0.91 0.95
## P26 11.715 19 0.897 0.586 0.614 -1.33 -1.24
## P27 24.191 19 0.189 1.210 1.141 0.70 0.52
## P28 19.472 19 0.427 0.974 0.970 0.01 -0.02
## P29 23.030 19 0.236 1.152 1.132 0.97 0.87
## P30 23.534 19 0.215 1.177 1.053 0.66 0.28
## P31 22.137 19 0.277 1.107 1.084 0.58 0.49
## P32 18.331 19 0.500 0.917 0.918 -0.50 -0.48
## P33 19.679 19 0.414 0.984 0.966 -0.05 -0.17
## P34 19.278 19 0.439 0.964 0.966 -0.16 -0.15
## P35 14.526 19 0.752 0.726 0.735 -1.09 -1.08
## P36 17.780 19 0.537 0.889 0.892 -0.54 -0.53
## P37 21.212 19 0.325 1.061 1.048 0.40 0.34
## P38 19.831 19 0.405 0.992 0.992 0.01 0.01
## P39 18.443 19 0.493 0.922 0.919 -0.46 -0.48
## P40 17.086 19 0.584 0.854 0.966 -0.03 0.14
## P41 12.796 19 0.849 0.640 0.607 -0.97 -1.10
## P42 18.275 19 0.504 0.914 0.916 -0.40 -0.40
## P43 12.510 19 0.863 0.626 0.648 -1.36 -1.29
## P44 48.168 19 0.000 2.408 2.375 2.59 2.57
## P45 147.548 19 0.000 7.377 6.679 6.33 6.03
## P46 17.842 19 0.533 0.892 0.847 -0.25 -0.40
## P47 12.769 19 0.850 0.638 0.654 -0.97 -0.93
## P48 16.349 19 0.634 0.817 0.793 -0.46 -0.56
## P49 5.331 19 0.999 0.267 0.234 -2.26 -2.46
## P50 5.217 19 0.999 0.261 0.289 -2.29 -2.15
## P51 5.273 19 0.999 0.264 0.262 -2.28 -2.30
## P52 25.131 19 0.156 1.257 1.147 1.05 0.69
## P53 16.169 19 0.646 0.808 0.849 -0.76 -0.62
## P54 19.473 19 0.427 0.974 0.934 0.01 -0.15
## P55 20.411 19 0.370 1.021 0.995 0.20 0.14
## P56 41.412 19 0.002 2.071 2.111 2.87 2.90
## P57 28.085 19 0.082 1.404 1.458 1.23 1.35
## P58 7.660 19 0.990 0.383 0.413 -1.68 -1.63
## P59 9.510 19 0.964 0.476 0.429 -1.44 -1.65
## P60 16.430 19 0.628 0.822 0.873 -0.26 -0.14
## P61 19.973 19 0.396 0.999 1.014 0.10 0.14
## P62 3.572 19 1.000 0.179 0.210 -2.70 -2.55
## P63 15.614 19 0.683 0.781 0.737 -0.36 -0.49
## P64 21.545 19 0.308 1.077 1.026 0.32 0.21
## P65 9.510 19 0.964 0.476 0.429 -1.44 -1.65
## P66 7.428 19 0.992 0.371 0.319 -1.68 -1.96
## P67 9.891 19 0.956 0.495 0.487 -1.25 -1.33
## P68 13.549 19 0.809 0.677 0.637 -1.09 -1.32
## P69 25.531 19 0.144 1.277 1.272 1.57 1.55
## P70 17.953 19 0.526 0.898 0.902 -0.62 -0.60
## P71 21.004 19 0.337 1.050 1.040 0.37 0.31
## P72 9.384 19 0.967 0.469 0.441 -1.34 -1.51
## P73 6.205 19 0.997 0.310 0.328 -2.04 -1.96
## P74 33.407 19 0.022 1.670 1.595 2.25 2.08
## P75 18.369 19 0.498 0.918 0.922 -0.48 -0.46
## P76 19.926 19 0.399 0.996 1.002 0.04 0.07
## P77 20.659 19 0.356 1.033 1.029 0.26 0.24
## P78 61.038 19 0.000 3.052 3.015 3.73 3.89
## P79 3.750 19 1.000 0.188 0.198 -2.74 -2.69
## P80 21.345 19 0.318 1.067 1.068 0.47 0.48
## P81 15.857 19 0.667 0.793 0.799 -0.65 -0.65
## P82 27.520 19 0.093 1.376 1.037 0.67 0.35
## P83 21.079 19 0.332 1.054 1.084 0.27 0.34
## P84 18.328 19 0.501 0.916 0.932 -0.14 -0.10
## P85 21.513 19 0.309 1.076 1.075 0.38 0.40
## P86 17.914 19 0.528 0.896 0.896 -0.64 -0.63
## P87 24.627 19 0.173 1.231 1.288 0.65 0.79
## P88 18.176 19 0.511 0.909 0.931 -0.09 -0.03
## P89 10.146 19 0.949 0.507 0.383 -1.74 -2.43
## P90 20.962 19 0.339 1.048 1.013 0.25 0.15
## P91 10.177 19 0.948 0.509 0.559 -1.37 -1.27
## P92 38.928 19 0.005 1.946 1.852 2.48 2.33
## P93 19.759 19 0.409 0.988 0.995 -0.02 0.02
## P94 15.604 19 0.684 0.780 0.923 -0.34 -0.03
## P95 74.640 19 0.000 3.732 3.771 9.88 9.98
## P96 12.538 19 0.861 0.627 0.621 -0.87 -0.95
## P97 17.507 19 0.556 0.875 0.883 -0.69 -0.67
## P98 4.196 19 1.000 0.210 0.246 -2.49 -2.33
## P99 4.484 19 1.000 0.224 0.237 -2.41 -2.39
## P100 14.460 19 0.756 0.723 0.736 -0.70 -0.71
## P101 13.705 19 0.801 0.685 0.668 -1.10 -1.16
## P102 15.211 19 0.709 0.761 0.781 -0.93 -0.85
## P103 5.521 19 0.999 0.276 0.249 -3.52 -3.82
## P104 35.068 19 0.014 1.753 1.713 3.29 3.17
## P105 13.169 19 0.830 0.658 0.954 -0.07 0.26
## P106 18.465 19 0.492 0.923 0.945 -0.24 -0.17
## P107 27.305 19 0.098 1.365 1.272 0.93 0.74
## P108 21.711 19 0.299 1.086 1.055 0.33 0.27
## P109 14.286 19 0.767 0.714 0.706 -0.91 -0.97
## P110 7.114 19 0.994 0.356 0.364 -1.96 -1.94
## P111 3.677 19 1.000 0.184 0.220 -2.66 -2.49
## P112 39.041 19 0.004 1.952 1.843 2.39 2.21
## P113 4.484 19 1.000 0.224 0.237 -2.41 -2.39
## P114 18.003 19 0.522 0.900 0.912 -0.25 -0.22
## P115 16.955 19 0.593 0.848 0.797 -0.34 -0.55
## P116 23.746 19 0.206 1.187 1.186 0.69 0.70
## P117 17.621 19 0.548 0.881 0.870 -0.39 -0.45
## P118 12.851 19 0.846 0.643 0.666 -0.89 -0.88
## P119 35.587 19 0.012 1.779 1.868 3.20 3.67
## P120 12.000 19 0.886 0.600 0.939 -0.15 0.24
## P121 16.161 19 0.647 0.808 0.828 -1.13 -1.04
## P122 15.070 19 0.718 0.753 0.632 -0.49 -0.91
## P123 21.424 19 0.314 1.071 1.015 0.31 0.16
## P124 19.521 19 0.424 0.976 0.967 -0.10 -0.16
## P125 18.703 19 0.476 0.935 0.936 -0.28 -0.28
## P126 10.777 19 0.931 0.539 0.502 -1.10 -1.28
## P127 16.677 19 0.612 0.834 0.852 -0.60 -0.53
## P128 18.458 19 0.492 0.923 0.956 -0.09 -0.01
## P129 28.573 19 0.073 1.429 1.431 1.08 1.13
## P130 3.168 19 1.000 0.158 0.196 -2.84 -2.64
## P131 26.819 19 0.109 1.341 1.072 0.70 0.32
## P132 3.572 19 1.000 0.179 0.210 -2.70 -2.55
## P133 17.589 19 0.550 0.879 0.994 0.20 0.30
## P134 28.492 19 0.074 1.425 1.447 2.44 2.57
## P135 17.086 19 0.584 0.854 0.966 -0.03 0.14
## P136 10.130 19 0.950 0.507 0.496 -2.04 -2.12
## P137 19.472 19 0.427 0.974 0.991 0.01 0.06
## P138 9.793 19 0.958 0.490 0.550 -1.57 -1.41
## P139 8.457 19 0.981 0.423 0.419 -1.66 -1.69
## P140 3.572 19 1.000 0.179 0.210 -2.70 -2.55
## P141 23.166 19 0.230 1.158 1.140 0.93 0.85
## P142 17.051 19 0.586 0.853 0.844 -0.51 -0.57
## P143 13.983 19 0.785 0.699 0.705 -0.85 -0.88
## P144 12.449 19 0.866 0.622 0.584 -1.38 -1.53
## P145 17.929 19 0.527 0.896 0.908 -0.12 -0.09
## P146 18.018 19 0.521 0.901 0.741 -0.25 -0.89
## P147 12.274 19 0.874 0.614 0.665 -1.31 -1.07
## P148 27.338 19 0.097 1.367 1.289 0.88 0.76
## P149 31.441 19 0.036 1.572 2.052 0.98 1.56
## P150 19.482 19 0.426 0.974 0.974 0.06 0.04
## P151 20.490 19 0.366 1.024 1.035 0.18 0.22
## P152 15.816 19 0.670 0.791 0.924 -0.31 -0.03
## P153 19.225 19 0.442 0.961 1.005 0.15 0.21
## P154 13.472 19 0.814 0.674 0.686 -0.98 -0.95
## P155 11.777 19 0.895 0.589 0.605 -1.32 -1.28
## P156 12.369 19 0.869 0.618 0.682 -1.06 -0.90
## P157 6.541 19 0.996 0.327 0.348 -3.01 -2.95
## P158 3.578 19 1.000 0.179 0.174 -3.84 -3.86
## P159 9.801 19 0.958 0.490 0.530 -1.23 -1.11
## P160 18.744 19 0.473 0.937 0.932 -0.27 -0.30
## P161 15.760 19 0.673 0.788 0.800 -0.80 -0.76
## P162 17.530 19 0.554 0.877 0.884 -0.61 -0.57
## P163 21.096 19 0.332 1.055 1.055 0.40 0.40
## P164 9.122 19 0.971 0.456 0.446 -1.39 -1.49
## P165 22.235 19 0.273 1.112 1.066 0.46 0.32
## P166 10.912 19 0.927 0.546 0.591 -1.56 -1.42
## P167 5.103 19 0.999 0.255 0.244 -2.23 -2.35
## P168 6.206 19 0.997 0.310 0.379 -2.01 -1.77
## P169 12.976 19 0.840 0.649 0.687 -1.03 -0.95
## P170 8.221 19 0.984 0.411 0.445 -1.71 -1.58
## P171 43.696 19 0.001 2.185 2.142 5.78 5.60
## P172 22.970 19 0.239 1.148 1.055 0.50 0.27
## P173 18.495 19 0.490 0.925 0.861 -0.05 -0.22
## P174 13.931 19 0.788 0.697 0.921 -0.32 0.06
## P175 73.628 19 0.000 3.681 3.549 4.78 4.85
## P176 19.850 19 0.404 0.993 0.977 0.10 0.04
## P177 14.814 19 0.734 0.741 0.745 -0.86 -0.87
## P178 19.921 19 0.399 0.996 0.990 0.09 0.06
## P179 18.493 19 0.490 0.925 0.929 -0.39 -0.38
## P180 14.510 19 0.753 0.725 0.731 -0.87 -0.87
## P181 19.133 19 0.448 0.957 0.941 -0.23 -0.34
## P182 22.734 19 0.249 1.137 1.042 0.42 0.27
## P183 17.145 19 0.580 0.857 0.862 -0.60 -0.59
## P184 4.937 19 0.999 0.247 0.231 -2.37 -2.48
## P185 21.468 19 0.312 1.073 1.054 0.32 0.27
## P186 11.472 19 0.907 0.574 0.559 -1.46 -1.50
## P187 13.744 19 0.798 0.687 0.665 -1.09 -1.18
## P188 9.609 19 0.962 0.480 0.506 -1.93 -1.78
## P189 18.469 19 0.491 0.923 0.917 -0.35 -0.39
## P190 17.197 19 0.577 0.860 0.867 -0.88 -0.84
## P191 8.472 19 0.981 0.424 0.415 -2.24 -2.25
## P192 12.114 19 0.881 0.606 0.584 -1.09 -1.19
## P193 18.947 19 0.460 0.947 0.954 -0.25 -0.22
## P194 17.920 19 0.528 0.896 0.900 -0.58 -0.56
## P195 28.695 19 0.071 1.435 1.245 1.26 0.79
## P196 35.898 19 0.011 1.795 1.764 3.79 3.77
## P197 22.667 19 0.252 1.133 1.021 0.46 0.33
## P198 27.543 19 0.093 1.377 1.328 1.03 0.96
## P199 4.620 19 1.000 0.231 0.254 -2.37 -2.29
## P200 6.349 19 0.997 0.317 0.307 -2.00 -2.06
## P201 19.689 19 0.413 0.984 1.078 0.06 0.34
## P202 35.866 19 0.011 1.793 2.179 1.85 2.63
## P203 13.608 19 0.806 0.680 0.670 -0.82 -0.87
## P204 14.690 19 0.742 0.735 0.710 -0.75 -0.86
## P205 18.547 19 0.486 0.927 0.937 -0.30 -0.27
## P206 12.538 19 0.861 0.627 0.621 -0.87 -0.95
## P207 58.313 19 0.000 2.916 2.886 3.02 3.08
## P208 17.866 19 0.531 0.893 0.850 -0.23 -0.39
## P209 17.431 19 0.561 0.872 0.834 -0.27 -0.42
## P210 14.276 19 0.767 0.714 0.733 -0.83 -0.77
## P211 18.978 19 0.458 0.949 0.953 -0.28 -0.25
## P212 14.141 19 0.775 0.707 0.692 -1.00 -1.04
## P213 14.409 19 0.759 0.720 0.968 0.01 0.27
## P214 33.534 19 0.021 1.677 1.715 1.38 1.45
## P215 32.498 19 0.027 1.625 1.533 1.62 1.49
## P216 13.786 19 0.796 0.689 0.962 -0.03 0.26
## P217 66.473 19 0.000 3.324 3.293 7.78 7.78
## P218 16.882 19 0.598 0.844 0.861 -0.26 -0.22
## P219 23.334 19 0.223 1.167 1.073 0.63 0.35
## P220 18.790 19 0.470 0.940 0.939 -0.34 -0.34
## P221 62.376 19 0.000 3.119 3.166 3.27 3.33
## P222 3.168 19 1.000 0.158 0.196 -2.84 -2.64
## P223 8.518 19 0.981 0.426 0.385 -2.47 -2.78
## P224 15.714 19 0.676 0.786 0.980 0.09 0.29
## P225 16.657 19 0.613 0.833 0.774 -0.31 -0.52
## P226 18.590 19 0.483 0.930 0.949 -0.14 -0.09
## P227 4.937 19 0.999 0.247 0.231 -2.37 -2.48
## P228 22.396 19 0.265 1.120 1.056 0.40 0.27
## P229 36.924 19 0.008 1.846 1.783 2.38 2.29
## P230 11.971 19 0.887 0.599 0.577 -1.11 -1.22
## P231 18.155 19 0.512 0.908 0.902 -0.43 -0.47
## P232 17.538 19 0.553 0.877 0.831 -0.14 -0.26
## P233 19.746 19 0.410 0.987 1.025 0.09 0.19
## P234 14.499 19 0.754 0.725 0.711 -0.93 -0.97
## P235 14.531 19 0.752 0.727 0.738 -0.62 -0.64
## P236 18.786 19 0.471 0.939 0.939 -0.20 -0.21
## P237 4.062 19 1.000 0.203 0.239 -2.54 -2.38
## P238 27.420 19 0.095 1.371 1.503 1.21 1.65
## P239 39.237 19 0.004 1.962 2.073 2.40 2.71
## P240 33.037 19 0.024 1.652 1.638 1.58 1.66
## P241 17.326 19 0.568 0.866 0.959 -0.01 0.13
## P242 17.281 19 0.571 0.864 0.879 -0.50 -0.47
## P243 4.406 19 1.000 0.220 0.201 -3.47 -3.61
## P244 18.976 19 0.458 0.949 1.003 0.13 0.20
## P245 52.006 19 0.000 2.600 2.801 3.58 3.85
## P246 12.164 19 0.879 0.608 0.633 -1.24 -1.16
## P247 11.133 19 0.919 0.557 0.591 -1.45 -1.34
## P248 29.898 19 0.053 1.495 1.413 1.09 0.96
## P249 13.913 19 0.789 0.696 0.706 -1.24 -1.22
## P250 43.044 19 0.001 2.152 2.204 5.10 5.43
## P251 7.304 19 0.992 0.365 0.345 -2.92 -3.09
## P252 14.833 19 0.733 0.742 0.751 -0.84 -0.81
## P253 18.480 19 0.491 0.924 0.987 0.09 0.18
## P254 13.406 19 0.817 0.670 0.760 -1.03 -0.68
## P255 25.885 19 0.133 1.294 1.243 1.13 0.98
## P256 34.539 19 0.016 1.727 1.961 1.73 2.46
## P257 27.386 19 0.096 1.369 1.350 1.12 1.15
## P258 25.273 19 0.152 1.264 1.281 0.94 1.00
## P259 50.799 19 0.000 2.540 2.586 3.33 3.47
## P260 20.750 19 0.351 1.038 1.018 0.22 0.16
## P261 21.371 19 0.317 1.069 1.031 0.32 0.20
## P262 14.104 19 0.778 0.705 0.696 -1.01 -1.03
## P263 18.385 19 0.497 0.919 0.923 -0.44 -0.42
## P264 13.746 19 0.798 0.687 0.704 -0.82 -0.82
## P265 5.605 19 0.999 0.280 0.277 -2.10 -2.17
## P266 13.916 19 0.789 0.696 0.675 -1.03 -1.12
## P267 15.116 19 0.715 0.756 0.754 -0.53 -0.59
## P268 16.240 19 0.641 0.812 0.764 -0.58 -0.76
## P269 15.164 19 0.712 0.758 0.724 -0.79 -0.91
## P270 31.433 19 0.036 1.572 1.527 2.87 2.76
## P271 21.686 19 0.300 1.084 1.109 0.40 0.50
## P272 18.480 19 0.491 0.924 0.987 0.09 0.18
## P273 8.045 19 0.986 0.402 0.460 -2.56 -2.28
## P274 3.750 19 1.000 0.188 0.198 -2.74 -2.69
## P275 17.902 19 0.529 0.895 0.874 -0.42 -0.53
## P276 13.315 19 0.822 0.666 0.686 -1.39 -1.32
## P277 19.916 19 0.400 0.996 0.975 0.14 0.10
## P278 22.071 19 0.281 1.104 1.098 0.56 0.56
## P279 12.128 19 0.880 0.606 0.607 -1.31 -1.34
## P280 13.793 19 0.796 0.690 0.698 -0.88 -0.91
## P281 17.901 19 0.529 0.895 0.944 -0.17 -0.05
## P282 3.677 19 1.000 0.184 0.220 -2.66 -2.49
## P283 18.676 19 0.478 0.934 0.957 -0.19 -0.12
## P284 16.935 19 0.594 0.847 0.941 -0.18 0.01
## P285 16.903 19 0.596 0.845 0.885 -0.59 -0.45
## P286 16.796 19 0.604 0.840 0.856 -0.77 -0.72
## P287 24.810 19 0.167 1.241 1.058 0.56 0.29
## P288 9.952 19 0.954 0.498 0.566 -1.42 -1.24
## P289 7.473 19 0.991 0.374 0.440 -1.82 -1.63
## P290 17.289 19 0.570 0.864 0.875 -0.46 -0.43
## P291 18.125 19 0.514 0.906 0.908 -0.44 -0.44
## P292 16.404 19 0.630 0.820 0.898 -0.54 -0.29
## P293 18.039 19 0.520 0.902 0.965 -0.15 0.01
## P294 14.906 19 0.729 0.745 0.747 -1.61 -1.59
## P295 22.143 19 0.277 1.107 1.052 0.38 0.26
## P296 18.254 19 0.506 0.913 0.905 -0.41 -0.45
## P297 13.341 19 0.821 0.667 0.684 -0.81 -0.82
## P298 7.660 19 0.990 0.383 0.413 -1.68 -1.63
## P299 15.433 19 0.695 0.772 0.774 -0.73 -0.74
## P300 15.569 19 0.686 0.778 0.793 -1.01 -0.95
## P301 39.938 19 0.003 1.997 1.977 3.57 3.58
## P302 16.905 19 0.596 0.845 0.945 -0.18 0.02
## P303 18.905 19 0.463 0.945 0.958 -0.15 -0.11
## P304 15.447 19 0.694 0.772 0.779 -0.87 -0.86
## P305 19.771 19 0.408 0.989 0.971 -0.01 -0.12
## P306 13.532 19 0.810 0.677 0.827 -0.67 -0.28
## P307 16.483 19 0.625 0.824 0.826 -0.64 -0.65
## P308 8.443 19 0.982 0.422 0.509 -1.73 -1.47
## P309 27.702 19 0.089 1.385 2.122 0.68 1.55
## P310 13.081 19 0.834 0.654 0.681 -1.05 -0.97
## P311 4.062 19 1.000 0.203 0.239 -2.54 -2.38
## P312 20.845 19 0.345 1.042 1.032 0.30 0.25
## P313 18.760 19 0.472 0.938 0.939 -0.04 -0.06
## P314 30.273 19 0.048 1.514 1.753 1.09 1.54
## P315 11.511 19 0.905 0.576 0.629 -1.22 -1.10
## P316 32.361 19 0.028 1.618 1.649 3.37 3.54
## P317 20.512 19 0.364 1.026 1.011 0.35 0.32
## P318 11.552 19 0.904 0.578 0.648 -1.12 -0.94
## P319 18.799 19 0.470 0.940 0.924 -0.30 -0.41
## P320 11.337 19 0.912 0.567 0.564 -1.23 -1.27
## P321 18.894 19 0.464 0.945 0.941 -0.27 -0.30
## P322 42.735 19 0.001 2.137 2.136 1.56 1.65
## P323 5.864 19 0.998 0.293 0.248 -2.90 -3.23
## P324 5.922 19 0.998 0.296 0.336 -2.11 -1.92
## P325 16.215 19 0.643 0.811 0.774 -0.58 -0.74
## P326 15.962 19 0.660 0.798 0.758 -0.34 -0.45
## P327 20.961 19 0.339 1.048 1.033 0.26 0.21
## P328 19.937 19 0.398 0.997 0.993 0.03 0.00
## P329 27.520 19 0.093 1.376 1.037 0.67 0.35
## P330 16.253 19 0.640 0.813 0.935 -0.26 0.00
## P331 18.527 19 0.488 0.926 0.963 -0.23 -0.09
## P332 14.409 19 0.759 0.720 0.968 0.01 0.27
## P333 8.895 19 0.975 0.445 0.435 -1.57 -1.62
## P334 15.980 19 0.659 0.799 0.851 -0.80 -0.61
## P335 61.080 19 0.000 3.054 3.046 3.39 3.40
## P336 3.572 19 1.000 0.179 0.210 -2.70 -2.55
## P337 6.322 19 0.997 0.316 0.273 -2.01 -2.24
## P338 17.403 19 0.563 0.870 0.976 0.00 0.16
## P339 24.544 19 0.176 1.227 1.165 0.75 0.59
## P340 26.042 19 0.129 1.302 1.259 1.32 1.17
## P341 19.870 19 0.402 0.993 1.007 0.15 0.16
## P342 7.769 19 0.989 0.388 0.422 -1.66 -1.59
## P343 21.529 19 0.308 1.076 1.008 0.32 0.17
## P344 13.169 19 0.830 0.658 0.954 -0.07 0.26
## P345 17.690 19 0.543 0.885 0.980 0.03 0.16
## P346 9.003 19 0.973 0.450 0.498 -1.50 -1.39
## P347 18.676 19 0.478 0.934 0.906 -0.18 -0.30
## P348 25.359 19 0.149 1.268 1.307 1.48 1.72
## P349 14.709 19 0.741 0.735 0.754 -1.04 -0.98
## P350 14.649 19 0.745 0.732 0.720 -0.60 -0.70
## P351 101.657 19 0.000 5.083 4.877 7.40 7.07
## P352 20.945 19 0.340 1.047 1.045 0.35 0.34
## P353 21.004 19 0.337 1.050 1.014 0.38 0.32
## P354 21.355 19 0.318 1.068 1.050 0.35 0.29
## P355 16.714 19 0.609 0.836 0.809 -0.49 -0.59
## P356 26.636 19 0.113 1.332 1.063 0.68 0.30
## P357 34.119 19 0.018 1.706 1.738 3.43 3.67
## P358 32.760 19 0.026 1.638 1.630 2.16 2.18
## P359 4.937 19 0.999 0.247 0.231 -2.37 -2.48
## P360 8.641 19 0.979 0.432 0.354 -2.15 -2.56
## P361 21.760 19 0.296 1.088 1.560 0.34 1.43
## P362 6.027 19 0.998 0.301 0.256 -2.08 -2.33
## P363 32.528 19 0.027 1.626 1.606 1.95 1.91
## P364 17.395 19 0.563 0.870 0.821 -0.36 -0.53
## P365 17.992 19 0.523 0.900 0.897 -0.39 -0.41
## P366 30.373 19 0.047 1.519 2.212 1.09 2.60
## P367 18.346 19 0.499 0.917 0.914 -0.45 -0.47
## P368 19.571 19 0.421 0.979 0.978 -0.02 -0.03
## P369 18.017 19 0.521 0.901 0.895 -0.31 -0.35
## P370 24.836 19 0.166 1.242 1.208 1.35 1.22
## P371 19.587 19 0.420 0.979 0.972 -0.08 -0.13
## P372 21.985 19 0.285 1.099 1.035 0.36 0.26
## P373 12.540 19 0.861 0.627 0.621 -1.36 -1.37
## P374 9.369 19 0.967 0.468 0.439 -2.00 -2.11
## P375 19.040 19 0.454 0.952 0.983 -0.01 0.07
## P376 6.027 19 0.998 0.301 0.256 -2.08 -2.33
## P377 13.346 19 0.820 0.667 0.633 -1.10 -1.23
## P378 27.520 19 0.093 1.376 1.037 0.67 0.35
## P379 18.673 19 0.478 0.934 0.962 -0.20 -0.09
## P380 29.488 19 0.059 1.474 1.433 1.49 1.36
## P381 18.384 19 0.497 0.919 0.968 -0.01 0.07
## P382 15.631 19 0.682 0.782 0.752 -0.61 -0.75
## P383 12.358 19 0.870 0.618 0.675 -0.86 -0.69
## P384 16.925 19 0.595 0.846 0.811 -0.41 -0.56
## P385 8.941 19 0.974 0.447 0.450 -1.56 -1.56
## P386 16.017 19 0.656 0.801 0.835 -0.99 -0.84
## P387 31.874 19 0.032 1.594 1.550 1.32 1.30
## P388 12.086 19 0.882 0.604 0.662 -1.02 -0.89
## P389 20.980 19 0.338 1.049 1.049 0.36 0.36
## P390 17.125 19 0.581 0.856 0.800 -0.24 -0.44
## P391 17.907 19 0.529 0.895 0.905 -0.33 -0.31
## P392 16.126 19 0.649 0.806 0.806 -0.72 -0.74
## P393 13.975 19 0.785 0.699 0.702 -1.03 -1.05
## P394 26.217 19 0.124 1.311 1.298 0.82 0.80
## P395 14.409 19 0.759 0.720 0.968 0.01 0.27
## P396 18.480 19 0.491 0.924 0.987 0.09 0.18
## P397 17.144 19 0.580 0.857 0.797 -0.40 -0.65
## P398 9.845 19 0.957 0.492 0.494 -1.99 -1.95
## P399 18.364 19 0.498 0.918 0.922 -0.09 -0.09
## P400 4.484 19 1.000 0.224 0.237 -2.41 -2.39Calculate the Item/Person Separation Reliability
# compute item separation reliability
# Get Item scores
ItemScores <- colSums(TL_data_PC)
# Get Item SD
ItemSD <- apply(TL_data_PC,2,sd)
# Calculate the se of the Item
ItemSE <- ItemSD/sqrt(length(ItemSD))
# compute the Observed Variance (also known as Total Person Variability or Squared Standard Deviation)
SSD.ItemScores <- var(ItemScores)
# compute the Mean Square Measurement error (also known as Model Error variance)
Item.MSE <- sum((ItemSE)^2) / length(ItemSE)
# compute the Item Separation Reliability
item.separation.reliability <- (SSD.ItemScores-Item.MSE) / SSD.ItemScores
item.separation.reliability## [1] 0.9999725# compute person separation reliability
# Get Person scores
PersonScores <- rowSums(TL_data_PC)
# Get Person SD
PersonSD <- apply(TL_data_PC,1,sd)
# Calculate the se of the Person
PersonSE <- PersonSD/sqrt(length(PersonSD))
# compute the Observed Variance (also known as Total Person Variability or Squared Standard Deviation)
SSD.PersonScores <- var(PersonScores)
# compute the Mean Square Measurement error (also known as Model Error variance)
Person.MSE <- sum((PersonSE)^2) / length(PersonSE)
# compute the Person Separation Reliability
person.separation.reliability <- (SSD.PersonScores-Person.MSE) / SSD.PersonScores
person.separation.reliability## [1] 0.9999967