| itemstats {mirt} | R Documentation |
Function to compute generic item summary statistics that do not require prior fitting of IRT models. Contains information about coefficient alpha (and alpha if an item is deleted), mean/SD and frequency of total scores, reduced item-total correlations, average/sd of the correlation between items, response frequencies, and conditional mean/sd information given the unweighted sum scores.
itemstats(
data,
group = NULL,
use_ts = TRUE,
proportions = TRUE,
ts.tables = FALSE
)
data |
An object of class |
group |
optional grouping variable to condition on when computing summary information |
use_ts |
logical; include information that is conditional on a meaningful total score? |
proportions |
logical; include response proportion information for each item? |
ts.tables |
logical; include mean/sd summary information pertaining to the unweighted total score? |
Returns a list containing the summary statistics
Phil Chalmers rphilip.chalmers@gmail.com
Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi:10.18637/jss.v048.i06
# dichotomous data example
LSAT7full <- expand.table(LSAT7)
head(LSAT7full)
## Item.1 Item.2 Item.3 Item.4 Item.5
## 1 0 0 0 0 0
## 2 0 0 0 0 0
## 3 0 0 0 0 0
## 4 0 0 0 0 0
## 5 0 0 0 0 0
## 6 0 0 0 0 0
itemstats(LSAT7full)
## $overall
## N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
## 1000 3.707 1.199 0.143 0.052 0.453 0.886
##
## $itemstats
## N mean sd total.r total.r_if_rm alpha_if_rm
## Item.1 1000 0.828 0.378 0.530 0.246 0.396
## Item.2 1000 0.658 0.475 0.600 0.247 0.394
## Item.3 1000 0.772 0.420 0.611 0.313 0.345
## Item.4 1000 0.606 0.489 0.592 0.223 0.415
## Item.5 1000 0.843 0.364 0.461 0.175 0.438
##
## $proportions
## 0 1
## Item.1 0.172 0.828
## Item.2 0.342 0.658
## Item.3 0.228 0.772
## Item.4 0.394 0.606
## Item.5 0.157 0.843
# behaviour with missing data
LSAT7full[1:5,1] <- NA
itemstats(LSAT7full)
## $overall
## N.complete N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
## 995 1000 3.726 1.172 0.137 0.052 0.426 0.888
##
## $itemstats
## N mean sd total.r total.r_if_rm alpha_if_rm
## Item.1 995 0.832 0.374 0.515 0.222 0.396
## Item.2 1000 0.658 0.475 0.595 0.232 0.364
## Item.3 1000 0.772 0.420 0.602 0.295 0.316
## Item.4 1000 0.606 0.489 0.589 0.209 0.384
## Item.5 1000 0.843 0.364 0.442 0.149 0.418
##
## $proportions
## 0 1 NA
## Item.1 0.167 0.828 0.005
## Item.2 0.342 0.658 NA
## Item.3 0.228 0.772 NA
## Item.4 0.394 0.606 NA
## Item.5 0.157 0.843 NA
# data with no meaningful total score
head(SAT12)
## Item.1 Item.2 Item.3 Item.4 Item.5 Item.6 Item.7 Item.8 Item.9 Item.10
## 1 1 4 5 2 3 1 2 1 3 1
## 2 3 4 2 NA 3 3 2 NA 3 1
## 3 1 4 5 4 3 2 2 3 3 2
## 4 2 4 4 2 3 3 2 4 3 2
## 5 2 4 5 2 3 2 2 1 1 2
## 6 1 4 3 1 3 2 2 3 3 1
## Item.11 Item.12 Item.13 Item.14 Item.15 Item.16 Item.17 Item.18 Item.19
## 1 2 4 2 1 5 3 4 4 1
## 2 2 NA 2 1 5 2 4 1 1
## 3 2 1 3 1 5 5 4 1 3
## 4 2 4 2 1 5 2 4 1 3
## 5 2 4 2 1 5 4 4 5 1
## 6 2 3 2 1 5 5 4 4 1
## Item.20 Item.21 Item.22 Item.23 Item.24 Item.25 Item.26 Item.27 Item.28
## 1 4 3 3 4 1 3 5 1 3
## 2 4 3 3 NA 1 NA 4 1 4
## 3 4 3 3 1 1 3 4 1 3
## 4 4 3 1 5 2 5 4 1 3
## 5 4 3 3 3 1 1 5 1 3
## 6 4 3 3 4 1 1 4 1 4
## Item.29 Item.30 Item.31 Item.32
## 1 1 5 4 5
## 2 5 NA 4 NA
## 3 4 4 4 1
## 4 4 2 4 2
## 5 1 2 4 1
## 6 2 3 4 3
itemstats(SAT12, use_ts=FALSE)
## $overall
## N.complete N
## 1 572 600
##
## $itemstats
## N mean sd
## Item.1 599 2.487 1.168
## Item.2 599 3.377 1.344
## Item.3 592 3.147 1.439
## Item.4 595 2.718 1.289
## Item.5 599 2.860 0.887
## Item.6 600 2.358 1.135
## Item.7 599 2.412 0.880
## Item.8 598 2.908 1.340
## Item.9 600 2.907 0.567
## Item.10 598 2.301 1.456
## Item.11 600 2.017 0.199
## Item.12 595 3.605 1.119
## Item.13 600 2.317 0.956
## Item.14 598 1.778 1.389
## Item.15 599 4.529 1.078
## Item.16 599 3.361 1.120
## Item.17 600 3.968 0.343
## Item.18 597 2.995 1.476
## Item.19 600 1.900 1.053
## Item.20 599 3.863 0.453
## Item.21 599 2.928 0.514
## Item.22 600 2.985 0.442
## Item.23 597 2.729 1.392
## Item.24 599 1.491 1.003
## Item.25 595 2.696 1.299
## Item.26 599 3.917 1.255
## Item.27 598 1.217 0.660
## Item.28 597 3.238 0.877
## Item.29 595 2.237 1.202
## Item.30 594 3.660 1.499
## Item.31 599 3.781 0.883
## Item.32 593 2.965 1.193
##
## $proportions
## 1 2 3 4 5 NA
## Item.1 0.283 0.203 0.267 0.232 0.013 0.002
## Item.2 0.212 0.022 0.070 0.568 0.127 0.002
## Item.3 0.165 0.183 0.260 0.098 0.280 0.013
## Item.4 0.165 0.378 0.148 0.172 0.128 0.008
## Item.5 0.093 0.143 0.620 0.093 0.048 0.002
## Item.6 0.160 0.582 0.107 0.043 0.108 NA
## Item.7 0.025 0.760 0.007 0.190 0.017 0.002
## Item.8 0.202 0.205 0.207 0.250 0.133 0.003
## Item.9 0.065 0.010 0.885 0.033 0.007 NA
## Item.10 0.422 0.215 0.165 0.028 0.167 0.003
## Item.11 0.003 0.983 0.008 0.003 0.002 NA
## Item.12 0.072 0.082 0.218 0.415 0.205 0.008
## Item.13 0.110 0.662 0.070 0.118 0.040 NA
## Item.14 0.723 0.027 0.108 0.022 0.117 0.003
## Item.15 0.035 0.062 0.060 0.025 0.817 0.002
## Item.16 0.070 0.105 0.413 0.215 0.195 0.002
## Item.17 0.008 0.005 0.010 0.963 0.013 NA
## Item.18 0.303 0.033 0.165 0.352 0.142 0.005
## Item.19 0.548 0.053 0.358 0.030 0.010 NA
## Item.20 0.012 0.002 0.105 0.873 0.007 0.002
## Item.21 0.050 0.008 0.915 0.013 0.012 0.002
## Item.22 0.028 0.005 0.935 0.017 0.015 NA
## Item.23 0.290 0.177 0.128 0.313 0.087 0.005
## Item.24 0.728 0.162 0.042 0.022 0.045 0.002
## Item.25 0.240 0.170 0.375 0.065 0.142 0.008
## Item.26 0.020 0.227 0.030 0.262 0.460 0.002
## Item.27 0.862 0.093 0.012 0.020 0.010 0.003
## Item.28 0.082 0.010 0.530 0.337 0.037 0.005
## Item.29 0.340 0.295 0.205 0.085 0.067 0.008
## Item.30 0.150 0.110 0.107 0.183 0.440 0.010
## Item.31 0.075 0.020 0.012 0.833 0.058 0.002
## Item.32 0.125 0.183 0.443 0.075 0.162 0.012
# extra total scores tables
dat <- key2binary(SAT12,
key = c(1,4,5,2,3,1,2,1,3,1,2,4,2,1,
5,3,4,4,1,4,3,3,4,1,3,5,1,3,1,5,4,5))
itemstats(dat, ts.tables=TRUE)
## $overall
## N.complete N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
## 572 600 18.367 4.93 0.107 0.075 0.787 2.275
##
## $itemstats
## N mean sd total.r total.r_if_rm alpha_if_rm
## Item.1 599 0.284 0.451 0.398 0.317 0.780
## Item.2 599 0.569 0.496 0.521 0.442 0.774
## Item.3 592 0.284 0.451 0.454 0.377 0.777
## Item.4 595 0.382 0.486 0.339 0.248 0.783
## Item.5 599 0.621 0.486 0.418 0.331 0.779
## Item.6 600 0.160 0.367 0.415 0.351 0.779
## Item.7 599 0.761 0.427 0.359 0.281 0.782
## Item.8 598 0.202 0.402 0.305 0.227 0.784
## Item.9 600 0.885 0.319 0.166 0.103 0.788
## Item.10 598 0.423 0.494 0.460 0.375 0.777
## Item.11 600 0.983 0.128 0.163 0.139 0.787
## Item.12 595 0.418 0.494 0.150 0.051 0.795
## Item.13 600 0.662 0.474 0.418 0.334 0.779
## Item.14 598 0.726 0.447 0.399 0.319 0.780
## Item.15 599 0.818 0.386 0.376 0.307 0.781
## Item.16 599 0.414 0.493 0.356 0.264 0.783
## Item.17 600 0.963 0.188 0.208 0.173 0.786
## Item.18 597 0.353 0.478 0.576 0.505 0.773
## Item.19 600 0.548 0.498 0.387 0.296 0.781
## Item.20 599 0.875 0.331 0.354 0.295 0.781
## Item.21 599 0.917 0.277 0.181 0.127 0.787
## Item.22 600 0.935 0.247 0.263 0.217 0.784
## Item.23 597 0.315 0.465 0.332 0.244 0.784
## Item.24 599 0.730 0.445 0.424 0.346 0.779
## Item.25 595 0.378 0.485 0.387 0.298 0.781
## Item.26 599 0.461 0.499 0.549 0.472 0.772
## Item.27 598 0.865 0.342 0.407 0.348 0.779
## Item.28 597 0.533 0.499 0.465 0.380 0.777
## Item.29 595 0.343 0.475 0.420 0.336 0.780
## Item.30 594 0.444 0.497 0.229 0.131 0.790
## Item.31 599 0.835 0.372 0.453 0.391 0.778
## Item.32 593 0.164 0.370 0.094 0.019 0.794
##
## $proportions
## 0 1 NA
## Item.1 0.715 0.283 0.002
## Item.2 0.430 0.568 0.002
## Item.3 0.707 0.280 0.013
## Item.4 0.613 0.378 0.008
## Item.5 0.378 0.620 0.002
## Item.6 0.840 0.160 NA
## Item.7 0.238 0.760 0.002
## Item.8 0.795 0.202 0.003
## Item.9 0.115 0.885 NA
## Item.10 0.575 0.422 0.003
## Item.11 0.017 0.983 NA
## Item.12 0.577 0.415 0.008
## Item.13 0.338 0.662 NA
## Item.14 0.273 0.723 0.003
## Item.15 0.182 0.817 0.002
## Item.16 0.585 0.413 0.002
## Item.17 0.037 0.963 NA
## Item.18 0.643 0.352 0.005
## Item.19 0.452 0.548 NA
## Item.20 0.125 0.873 0.002
## Item.21 0.083 0.915 0.002
## Item.22 0.065 0.935 NA
## Item.23 0.682 0.313 0.005
## Item.24 0.270 0.728 0.002
## Item.25 0.617 0.375 0.008
## Item.26 0.538 0.460 0.002
## Item.27 0.135 0.862 0.003
## Item.28 0.465 0.530 0.005
## Item.29 0.652 0.340 0.008
## Item.30 0.550 0.440 0.010
## Item.31 0.165 0.833 0.002
## Item.32 0.827 0.162 0.012
##
## $total.score_frequency
## 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
## Freq 1 1 1 5 7 10 11 16 33 51 44 39 44 49 43 43 20 34 30 17 15 18 19 7 7 3
## 31 32
## Freq 1 3
##
## $total.score_means
## 0 1
## Item.1 17.11794 21.44848
## Item.2 15.35000 20.54819
## Item.3 16.94853 21.89634
## Item.4 17.06197 20.50230
## Item.5 15.72685 19.96910
## Item.6 17.46555 23.01075
## Item.7 15.19853 19.35550
## Item.8 17.59292 21.28333
## Item.9 16.07692 18.66075
## Item.10 16.42727 21.01240
## Item.11 12.00000 18.46892
## Item.12 17.73795 19.23750
## Item.13 15.46073 19.82415
## Item.14 15.14194 19.56595
## Item.15 14.32323 19.21353
## Item.16 16.87009 20.42324
## Item.17 12.84211 18.55696
## Item.18 16.26287 22.19212
## Item.19 16.27413 20.09904
## Item.20 13.58209 19.00198
## Item.21 15.34783 18.63118
## Item.22 13.36111 18.70336
## Item.23 17.26904 20.79775
## Item.24 14.90850 19.63007
## Item.25 16.87288 20.79358
## Item.26 15.82895 21.24627
## Item.27 13.20000 19.14688
## Item.28 15.85769 20.45833
## Item.29 16.86096 21.21212
## Item.30 17.34395 19.61240
## Item.31 13.24176 19.33680
## Item.32 18.16109 19.41489
##
## $total.score_sds
## 0 1
## Item.1 4.300401 5.041784
## Item.2 3.600674 4.604027
## Item.3 4.144775 4.968143
## Item.4 4.256811 5.213164
## Item.5 4.077667 4.712782
## Item.6 4.286102 5.420361
## Item.7 4.111087 4.747872
## Item.8 4.402453 5.685280
## Item.9 4.583625 4.900119
## Item.10 4.107505 4.730480
## Item.11 3.535534 4.884467
## Item.12 4.716815 5.093873
## Item.13 4.070080 4.676148
## Item.14 3.816299 4.759716
## Item.15 3.872531 4.705621
## Item.16 4.145612 5.182836
## Item.17 4.349498 4.841408
## Item.18 3.794125 4.437413
## Item.19 4.148193 4.858884
## Item.20 3.614572 4.730641
## Item.21 4.761967 4.860423
## Item.22 3.448832 4.833650
## Item.23 4.402024 5.173116
## Item.24 3.773801 4.695427
## Item.25 4.224332 5.037057
## Item.26 3.586326 4.661479
## Item.27 3.579219 4.628601
## Item.28 4.131868 4.555996
## Item.29 4.087767 5.135272
## Item.30 4.640031 4.994643
## Item.31 3.081633 4.605576
## Item.32 4.744322 5.697405
# grouping information
group <- gl(2, 300, labels=c('G1', 'G2'))
itemstats(dat, group=group)
## $G1
## $G1$overall
## N.complete N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
## 287 300 18.167 4.924 0.105 0.09 0.784 2.286
##
## $G1$itemstats
## N mean sd total.r total.r_if_rm alpha_if_rm
## Item.1 300 0.290 0.455 0.427 0.346 0.776
## Item.2 300 0.573 0.495 0.516 0.437 0.771
## Item.3 297 0.293 0.456 0.451 0.372 0.774
## Item.4 298 0.356 0.480 0.344 0.254 0.781
## Item.5 300 0.630 0.484 0.469 0.387 0.774
## Item.6 300 0.130 0.337 0.407 0.347 0.777
## Item.7 299 0.729 0.445 0.371 0.289 0.780
## Item.8 299 0.214 0.411 0.351 0.274 0.779
## Item.9 300 0.897 0.305 0.171 0.111 0.785
## Item.10 299 0.405 0.492 0.423 0.336 0.776
## Item.11 300 0.993 0.082 0.062 0.050 0.785
## Item.12 297 0.418 0.494 0.116 0.016 0.793
## Item.13 300 0.647 0.479 0.427 0.343 0.776
## Item.14 300 0.727 0.446 0.402 0.322 0.777
## Item.15 300 0.793 0.406 0.380 0.308 0.778
## Item.16 299 0.378 0.486 0.329 0.236 0.782
## Item.17 300 0.957 0.204 0.198 0.159 0.783
## Item.18 299 0.361 0.481 0.561 0.489 0.769
## Item.19 300 0.537 0.499 0.418 0.329 0.777
## Item.20 299 0.866 0.341 0.332 0.270 0.779
## Item.21 300 0.910 0.287 0.192 0.135 0.784
## Item.22 300 0.927 0.261 0.224 0.174 0.783
## Item.23 298 0.262 0.440 0.330 0.247 0.781
## Item.24 299 0.709 0.455 0.433 0.354 0.776
## Item.25 297 0.374 0.485 0.410 0.324 0.777
## Item.26 299 0.475 0.500 0.525 0.445 0.771
## Item.27 298 0.862 0.345 0.457 0.400 0.775
## Item.28 298 0.540 0.499 0.428 0.340 0.776
## Item.29 298 0.346 0.476 0.399 0.313 0.778
## Item.30 296 0.446 0.498 0.223 0.123 0.789
## Item.31 299 0.813 0.391 0.493 0.430 0.773
## Item.32 295 0.183 0.387 0.020 -0.060 0.797
##
## $G1$proportions
## 0 1 NA
## Item.1 0.710 0.290 NA
## Item.2 0.427 0.573 NA
## Item.3 0.700 0.290 0.010
## Item.4 0.640 0.353 0.007
## Item.5 0.370 0.630 NA
## Item.6 0.870 0.130 NA
## Item.7 0.270 0.727 0.003
## Item.8 0.783 0.213 0.003
## Item.9 0.103 0.897 NA
## Item.10 0.593 0.403 0.003
## Item.11 0.007 0.993 NA
## Item.12 0.577 0.413 0.010
## Item.13 0.353 0.647 NA
## Item.14 0.273 0.727 NA
## Item.15 0.207 0.793 NA
## Item.16 0.620 0.377 0.003
## Item.17 0.043 0.957 NA
## Item.18 0.637 0.360 0.003
## Item.19 0.463 0.537 NA
## Item.20 0.133 0.863 0.003
## Item.21 0.090 0.910 NA
## Item.22 0.073 0.927 NA
## Item.23 0.733 0.260 0.007
## Item.24 0.290 0.707 0.003
## Item.25 0.620 0.370 0.010
## Item.26 0.523 0.473 0.003
## Item.27 0.137 0.857 0.007
## Item.28 0.457 0.537 0.007
## Item.29 0.650 0.343 0.007
## Item.30 0.547 0.440 0.013
## Item.31 0.187 0.810 0.003
## Item.32 0.803 0.180 0.017
##
##
## $G2
## $G2$overall
## N.complete N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
## 285 300 18.568 4.937 0.11 0.08 0.79 2.265
##
## $G2$itemstats
## N mean sd total.r total.r_if_rm alpha_if_rm
## Item.1 299 0.278 0.449 0.372 0.289 0.784
## Item.2 299 0.565 0.497 0.527 0.449 0.776
## Item.3 295 0.275 0.447 0.461 0.385 0.780
## Item.4 297 0.407 0.492 0.332 0.239 0.786
## Item.5 299 0.612 0.488 0.370 0.280 0.785
## Item.6 300 0.190 0.393 0.422 0.353 0.782
## Item.7 300 0.793 0.406 0.344 0.268 0.785
## Item.8 299 0.191 0.393 0.260 0.183 0.788
## Item.9 300 0.873 0.333 0.166 0.100 0.791
## Item.10 299 0.441 0.497 0.495 0.413 0.778
## Item.11 300 0.973 0.161 0.231 0.199 0.788
## Item.12 298 0.419 0.494 0.184 0.085 0.798
## Item.13 300 0.677 0.469 0.406 0.323 0.783
## Item.14 298 0.725 0.447 0.397 0.317 0.783
## Item.15 299 0.843 0.365 0.369 0.304 0.785
## Item.16 300 0.450 0.498 0.380 0.289 0.784
## Item.17 300 0.970 0.171 0.221 0.191 0.788
## Item.18 298 0.346 0.476 0.594 0.526 0.777
## Item.19 300 0.560 0.497 0.354 0.261 0.786
## Item.20 300 0.883 0.322 0.376 0.320 0.784
## Item.21 299 0.923 0.267 0.169 0.117 0.790
## Item.22 300 0.943 0.232 0.306 0.263 0.786
## Item.23 299 0.368 0.483 0.330 0.239 0.787
## Item.24 300 0.750 0.434 0.413 0.337 0.782
## Item.25 298 0.383 0.487 0.362 0.271 0.785
## Item.26 300 0.447 0.498 0.576 0.503 0.773
## Item.27 300 0.867 0.341 0.358 0.296 0.784
## Item.28 299 0.525 0.500 0.503 0.421 0.778
## Item.29 297 0.340 0.475 0.443 0.360 0.782
## Item.30 298 0.443 0.498 0.237 0.138 0.792
## Item.31 300 0.857 0.351 0.406 0.346 0.782
## Item.32 298 0.144 0.352 0.185 0.116 0.790
##
## $G2$proportions
## 0 1 NA
## Item.1 0.720 0.277 0.003
## Item.2 0.433 0.563 0.003
## Item.3 0.713 0.270 0.017
## Item.4 0.587 0.403 0.010
## Item.5 0.387 0.610 0.003
## Item.6 0.810 0.190 NA
## Item.7 0.207 0.793 NA
## Item.8 0.807 0.190 0.003
## Item.9 0.127 0.873 NA
## Item.10 0.557 0.440 0.003
## Item.11 0.027 0.973 NA
## Item.12 0.577 0.417 0.007
## Item.13 0.323 0.677 NA
## Item.14 0.273 0.720 0.007
## Item.15 0.157 0.840 0.003
## Item.16 0.550 0.450 NA
## Item.17 0.030 0.970 NA
## Item.18 0.650 0.343 0.007
## Item.19 0.440 0.560 NA
## Item.20 0.117 0.883 NA
## Item.21 0.077 0.920 0.003
## Item.22 0.057 0.943 NA
## Item.23 0.630 0.367 0.003
## Item.24 0.250 0.750 NA
## Item.25 0.613 0.380 0.007
## Item.26 0.553 0.447 NA
## Item.27 0.133 0.867 NA
## Item.28 0.473 0.523 0.003
## Item.29 0.653 0.337 0.010
## Item.30 0.553 0.440 0.007
## Item.31 0.143 0.857 NA
## Item.32 0.850 0.143 0.007
#####
# polytomous data example
itemstats(Science)
## $overall
## N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
## 392 11.668 2.003 0.275 0.098 0.598 1.27
##
## $itemstats
## N mean sd total.r total.r_if_rm alpha_if_rm
## Comfort 392 3.120 0.588 0.596 0.352 0.552
## Work 392 2.722 0.807 0.666 0.332 0.567
## Future 392 2.990 0.757 0.748 0.488 0.437
## Benefit 392 2.837 0.802 0.684 0.363 0.541
##
## $proportions
## 1 2 3 4
## Comfort 0.013 0.082 0.679 0.227
## Work 0.084 0.250 0.526 0.140
## Future 0.036 0.184 0.536 0.245
## Benefit 0.054 0.255 0.492 0.199
# polytomous data with missing
newScience <- Science
newScience[1:5,1] <- NA
itemstats(newScience)
## $overall
## N.complete N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
## 387 392 11.672 2.011 0.276 0.1 0.605 1.264
##
## $itemstats
## N mean sd total.r total.r_if_rm alpha_if_rm
## Comfort 387 3.119 0.590 0.596 0.352 0.552
## Work 392 2.722 0.807 0.666 0.335 0.576
## Future 392 2.990 0.757 0.749 0.491 0.449
## Benefit 392 2.837 0.802 0.695 0.382 0.538
##
## $proportions
## 1 2 3 4 NA
## Comfort 0.013 0.082 0.668 0.224 0.013
## Work 0.084 0.250 0.526 0.140 NA
## Future 0.036 0.184 0.536 0.245 NA
## Benefit 0.054 0.255 0.492 0.199 NA
# unequal categories
newScience[,1] <- ifelse(Science[,1] == 1, NA, Science[,1])
itemstats(newScience)
## $overall
## N.complete N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
## 387 392 11.731 1.917 0.26 0.092 0.572 1.254
##
## $itemstats
## N mean sd total.r total.r_if_rm alpha_if_rm
## Comfort 387 3.147 0.540 0.556 0.314 0.552
## Work 392 2.722 0.807 0.680 0.339 0.517
## Future 392 2.990 0.757 0.738 0.460 0.409
## Benefit 392 2.837 0.802 0.668 0.328 0.525
##
## $proportions
## 1 2 3 4 NA
## Comfort NA 0.082 0.679 0.227 0.013
## Work 0.084 0.250 0.526 0.140 NA
## Future 0.036 0.184 0.536 0.245 NA
## Benefit 0.054 0.255 0.492 0.199 NA
merged <- data.frame(LSAT7full[1:392,], Science)
itemstats(merged)
## $overall
## N.complete N mean_total.score sd_total.score ave.r sd.r alpha SEM.alpha
## 387 392 14.331 2.231 0.037 0.167 0.379 1.759
##
## $itemstats
## N mean sd total.r total.r_if_rm alpha_if_rm
## Item.1 387 0.568 0.496 0.193 -0.030 0.417
## Item.2 392 0.232 0.423 0.033 -0.156 0.443
## Item.3 392 0.605 0.490 0.216 -0.003 0.405
## Item.4 392 0.467 0.500 0.261 0.038 0.392
## Item.5 392 0.760 0.428 0.178 -0.011 0.402
## Comfort 392 3.120 0.588 0.527 0.295 0.286
## Work 392 2.722 0.807 0.620 0.314 0.251
## Future 392 2.990 0.757 0.680 0.421 0.185
## Benefit 392 2.837 0.802 0.608 0.299 0.261
##
## $proportions
## 0 1 2 3 4 NA
## Item.1 0.426 0.561 NA NA NA 0.013
## Item.2 0.768 0.232 NA NA NA NA
## Item.3 0.395 0.605 NA NA NA NA
## Item.4 0.533 0.467 NA NA NA NA
## Item.5 0.240 0.760 NA NA NA NA
## Comfort NA 0.013 0.082 0.679 0.227 NA
## Work NA 0.084 0.250 0.526 0.140 NA
## Future NA 0.036 0.184 0.536 0.245 NA
## Benefit NA 0.054 0.255 0.492 0.199 NA