Classical Item Analysis for Multiple-Choice Test Items

Description

Classicial Item Analysis for Multiple-Choice Test Items

Usage

ITEMAN1(data, key, options, ngroup = ncol(data) + 1, correction = TRUE)

Arguments

Details

To be added later.

Value

Author(s)

Cengiz Zopluoglu

See Also

ITEMAN2 for classical item analysis of polytomously scored items

Examples

require(ITEMAN)

data(dichotomous)
head(dichotomous)
str(dichotomous)

# Key response vector

key <- c("A","D","C","B","C","B","C","D","A","D","C","A","D","C","A",
          "B","D","B","A","C","A","A","C","B","C","B","D","A","A","A",
          "C","B","B","A","B","D","D","A","D","C","D","A","B","B","C",
          "D","B","C","C","B","D","A","C","B","A","D")

# Use ITEMAN1 function to run the item analysis

item.analysis <- ITEMAN1(data=dichotomous,
                         key=key,
                         options=c("A","B","C","D"),
                         ngroup=20,
                         correction=FALSE)

item.analysis$plots[[1]]   # Item Trace Line for the first item

# item.analysis$plots[[2]]   # Item Trace Line for the second item
# item.analysis$plots[[3]]   # Item Trace Line for the third item
# item.analysis$plots[[4]]   # Item Trace Line for the fourth item
# item.analysis$plots[[5]]   # Item Trace Line for the fifth item
# item.analysis$plots[[6]]   # Item Trace Line for the sixth item
# item.analysis$plots[[7]]   # Item Trace Line for the seventh item
# item.analysis$plots[[8]]   # Item Trace Line for the eigth item
# item.analysis$plots[[9]]   # Item Trace Line for the ninth item
# item.analysis$plots[[10]]  # Item Trace Line for the tenth item

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(ITEMAN)
Loading required package: ggplot2
Loading required package: polycor
Loading required package: mvtnorm
Loading required package: sfsmisc
Loading required package: car
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ITEMAN/ITEMAN1.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ITEMAN1
> ### Title: Classical Item Analysis for Multiple-Choice Test Items
> ### Aliases: ITEMAN1
> 
> ### ** Examples
> 
> 
> require(ITEMAN)
> 
> data(dichotomous)
> head(dichotomous)
  item1 item2 item3 item4 item5 item6 item7 item8 item9 item10 item11 item12
1     A     A     D     D     C     B     C     D     D      D      C      A
2     A     B     C     C     C     B     A     D     A      D      C      A
3     A     C     D     B     D     D     D     D     A      D      C      A
4     A     B     D     B     D     D     C     D     A      C      C      B
5     A     D     C     B     C     B     C     D     B      D      C      A
6     D     C     B     C     A     B     C     D     A      D      A      B
  item13 item14 item15 item16 item17 item18 item19 item20 item21 item22 item23
1      D      C      A      B      D      B      A      B      B      A      D
2      D      C      A      B      A      D      A      C      B      A      C
3      D      D      A      B      A      A      A      C      B      C      C
4      D      D      A      A      D      B      D      C      D      A      C
5      D      C      A      A      A      B      A      C      B      C      A
6      D      D      B      C      B   <NA>      D      B      B      A      C
  item24 item25 item26 item27 item28 item29 item30 item31 item32 item33 item34
1      B      C      B      A      C      A      C      A      B      B      A
2      B      D      B      C      A      D      B      C      A      B      A
3      B      B      B      B      D      D      A      A      B      B      C
4      B      C      B      A      D      A      B      D      A      B      C
5      B      C      B      B      C      A      C      D      B      D      B
6      A      C      A      C   <NA>   <NA>      C      B      A      C      B
  item35 item36 item37 item38 item39 item40 item41 item42 item43 item44 item45
1      B      D      C      A      D      C      D      A      B      C      C
2      D      B      D      B      C      C      A      D      B      C      A
3      C      D      B      A      C      C      D      D      B      D      A
4      B      B      A      C      A      C      A      D      C      A      B
5      B      D      B      A      A      C      D      A      C      B      C
6      D      B      C      B      A      C      A      B      C      B      A
  item46 item47 item48 item49 item50 item51 item52 item53 item54 item55 item56
1      C      D      B      D      D      D      D      C      A      D      D
2      B      A      D      A      D      D      C      C      B      A      C
3      D      B      D      C      B      D      A      C      C      A      D
4      D      D      C      B      A      D      C      B      A      D      A
5      B      B      D      B      B      D      C      D      B      D      D
6      D      A      C      B      A      B      A   <NA>      B      C      C
> str(dichotomous)
'data.frame':	6000 obs. of  56 variables:
 $ item1 : Factor w/ 4 levels "A","B","C","D": 1 1 1 1 1 4 1 1 1 2 ...
 $ item2 : Factor w/ 4 levels "A","B","C","D": 1 2 3 2 4 3 1 2 4 1 ...
 $ item3 : Factor w/ 4 levels "A","B","C","D": 4 3 4 4 3 2 3 3 3 3 ...
 $ item4 : Factor w/ 4 levels "A","B","C","D": 4 3 2 2 2 3 2 2 4 2 ...
 $ item5 : Factor w/ 4 levels "A","B","C","D": 3 3 4 4 3 1 3 3 4 3 ...
 $ item6 : Factor w/ 4 levels "A","B","C","D": 2 2 4 4 2 2 2 2 2 2 ...
 $ item7 : Factor w/ 4 levels "A","B","C","D": 3 1 4 3 3 3 4 3 4 2 ...
 $ item8 : Factor w/ 4 levels "A","B","C","D": 4 4 4 4 4 4 4 4 4 4 ...
 $ item9 : Factor w/ 4 levels "A","B","C","D": 4 1 1 1 2 1 4 4 1 4 ...
 $ item10: Factor w/ 4 levels "A","B","C","D": 4 4 4 3 4 4 4 4 4 4 ...
 $ item11: Factor w/ 4 levels "A","B","C","D": 3 3 3 3 3 1 3 3 3 3 ...
 $ item12: Factor w/ 4 levels "A","B","C","D": 1 1 1 2 1 2 1 2 1 1 ...
 $ item13: Factor w/ 4 levels "A","B","C","D": 4 4 4 4 4 4 2 3 3 2 ...
 $ item14: Factor w/ 4 levels "A","B","C","D": 3 3 4 4 3 4 2 4 1 1 ...
 $ item15: Factor w/ 4 levels "A","B","C","D": 1 1 1 1 1 2 3 1 4 4 ...
 $ item16: Factor w/ 4 levels "A","B","C","D": 2 2 2 1 1 3 2 4 1 1 ...
 $ item17: Factor w/ 4 levels "A","B","C","D": 4 1 1 4 1 2 4 3 2 2 ...
 $ item18: Factor w/ 4 levels "A","B","C","D": 2 4 1 2 2 NA 4 2 1 1 ...
 $ item19: Factor w/ 4 levels "A","B","C","D": 1 1 1 4 1 4 1 2 3 1 ...
 $ item20: Factor w/ 4 levels "A","B","C","D": 2 3 3 3 3 2 3 3 4 NA ...
 $ item21: Factor w/ 4 levels "A","B","C","D": 2 2 2 4 2 2 1 3 2 2 ...
 $ item22: Factor w/ 4 levels "A","B","C","D": 1 1 3 1 3 1 1 2 1 1 ...
 $ item23: Factor w/ 4 levels "A","B","C","D": 4 3 3 3 1 3 4 4 2 3 ...
 $ item24: Factor w/ 4 levels "A","B","C","D": 2 2 2 2 2 1 2 3 1 2 ...
 $ item25: Factor w/ 4 levels "A","B","C","D": 3 4 2 3 3 3 4 2 4 2 ...
 $ item26: Factor w/ 4 levels "A","B","C","D": 2 2 2 2 2 1 2 3 3 1 ...
 $ item27: Factor w/ 4 levels "A","B","C","D": 1 3 2 1 2 3 2 1 4 3 ...
 $ item28: Factor w/ 4 levels "A","B","C","D": 3 1 4 4 3 NA 4 3 1 2 ...
 $ item29: Factor w/ 4 levels "A","B","C","D": 1 4 4 1 1 NA 4 2 2 3 ...
 $ item30: Factor w/ 4 levels "A","B","C","D": 3 2 1 2 3 3 3 4 3 2 ...
 $ item31: Factor w/ 4 levels "A","B","C","D": 1 3 1 4 4 2 2 4 1 1 ...
 $ item32: Factor w/ 4 levels "A","B","C","D": 2 1 2 1 2 1 2 2 2 1 ...
 $ item33: Factor w/ 4 levels "A","B","C","D": 2 2 2 2 4 3 1 4 2 2 ...
 $ item34: Factor w/ 4 levels "A","B","C","D": 1 1 3 3 2 2 1 1 1 2 ...
 $ item35: Factor w/ 4 levels "A","B","C","D": 2 4 3 2 2 4 2 2 3 3 ...
 $ item36: Factor w/ 4 levels "A","B","C","D": 4 2 4 2 4 2 4 4 4 1 ...
 $ item37: Factor w/ 4 levels "A","B","C","D": 3 4 2 1 2 3 4 NA 1 1 ...
 $ item38: Factor w/ 4 levels "A","B","C","D": 1 2 1 3 1 2 1 1 3 1 ...
 $ item39: Factor w/ 4 levels "A","B","C","D": 4 3 3 1 1 1 1 4 2 4 ...
 $ item40: Factor w/ 4 levels "A","B","C","D": 3 3 3 3 3 3 2 3 4 3 ...
 $ item41: Factor w/ 4 levels "A","B","C","D": 4 1 4 1 4 1 2 2 2 4 ...
 $ item42: Factor w/ 4 levels "A","B","C","D": 1 4 4 4 1 2 1 1 1 4 ...
 $ item43: Factor w/ 4 levels "A","B","C","D": 2 2 2 3 3 3 2 4 4 4 ...
 $ item44: Factor w/ 4 levels "A","B","C","D": 3 3 4 1 2 2 1 2 3 3 ...
 $ item45: Factor w/ 4 levels "A","B","C","D": 3 1 1 2 3 1 3 4 1 3 ...
 $ item46: Factor w/ 4 levels "A","B","C","D": 3 2 4 4 2 4 4 1 4 2 ...
 $ item47: Factor w/ 4 levels "A","B","C","D": 4 1 2 4 2 1 4 3 1 1 ...
 $ item48: Factor w/ 4 levels "A","B","C","D": 2 4 4 3 4 3 3 2 4 1 ...
 $ item49: Factor w/ 4 levels "A","B","C","D": 4 1 3 2 2 2 4 3 2 4 ...
 $ item50: Factor w/ 4 levels "A","B","C","D": 4 4 2 1 2 1 2 4 1 3 ...
 $ item51: Factor w/ 4 levels "A","B","C","D": 4 4 4 4 4 2 4 2 4 3 ...
 $ item52: Factor w/ 4 levels "A","B","C","D": 4 3 1 3 3 1 1 4 2 1 ...
 $ item53: Factor w/ 4 levels "A","B","C","D": 3 3 3 2 4 NA 3 2 1 2 ...
 $ item54: Factor w/ 4 levels "A","B","C","D": 1 2 3 1 2 2 3 3 3 3 ...
 $ item55: Factor w/ 4 levels "A","B","C","D": 4 1 1 4 4 3 2 1 1 4 ...
 $ item56: Factor w/ 4 levels "A","B","C","D": 4 3 4 1 4 3 4 NA 4 3 ...
> 
> # Key response vector
> 
> key <- c("A","D","C","B","C","B","C","D","A","D","C","A","D","C","A",
+           "B","D","B","A","C","A","A","C","B","C","B","D","A","A","A",
+           "C","B","B","A","B","D","D","A","D","C","D","A","B","B","C",
+           "D","B","C","C","B","D","A","C","B","A","D")
> 
> # Use ITEMAN1 function to run the item analysis
> 
> item.analysis <- ITEMAN1(data=dichotomous,
+                          key=key,
+                          options=c("A","B","C","D"),
+                          ngroup=20,
+                          correction=FALSE)
************************************************************************ 
ITEMAN: An R routine for Classical Item Analysis 
 
Cengiz Zopluoglu 
 
University of Miami 
Department of Educational and Psychological Studies 
Research, Measurement, and Evaluation Program 
 
c.zopluoglu@miami.edu 
 
Please report any programming bug or problem you experience to improve the code. 
************************************************************************* 
Processing Date:  Mon Jul  4 19:15:21 2016 
                                   ITEM STATISTICS 
 
        Item Difficulty Item Threshold Point-Biserial Biserial
Item 1            0.709         -0.551          0.349    0.462
Item 2            0.530         -0.075          0.304    0.381
Item 3            0.812         -0.885          0.440    0.638
Item 4            0.574         -0.185          0.281    0.354
Item 5            0.653         -0.393          0.334    0.431
Item 6            0.733         -0.621          0.384    0.517
Item 7            0.460          0.101          0.361    0.453
Item 8            0.856         -1.060          0.442    0.684
Item 9            0.544         -0.110          0.361    0.453
Item 10           0.808         -0.872          0.490    0.707
Item 11           0.827         -0.941          0.477    0.705
Item 12           0.553         -0.132          0.372    0.468
Item 13           0.772         -0.745          0.505    0.701
Item 14           0.473          0.067          0.345    0.433
Item 15           0.640         -0.360          0.480    0.616
Item 16           0.447          0.133          0.343    0.431
Item 17           0.434          0.166          0.379    0.477
Item 18           0.488          0.030          0.341    0.427
Item 19           0.668         -0.434          0.559    0.725
Item 20           0.502         -0.005          0.377    0.473
Item 21           0.572         -0.181          0.445    0.561
Item 22           0.437          0.159          0.420    0.529
Item 23           0.370          0.331          0.353    0.451
Item 24           0.569         -0.175          0.543    0.684
Item 25           0.503         -0.009          0.461    0.578
Item 26           0.741         -0.647          0.467    0.632
Item 27           0.163          0.982          0.209    0.313
Item 28           0.394          0.270          0.298    0.378
Item 29           0.446          0.136          0.351    0.441
Item 30           0.422          0.196          0.347    0.438
Item 31           0.364          0.348          0.258    0.331
Item 32           0.324          0.456          0.225    0.293
Item 33           0.666         -0.428          0.431    0.559
Item 34           0.489          0.027          0.445    0.558
Item 35           0.648         -0.379          0.532    0.684
Item 36           0.604         -0.264          0.543    0.689
Item 37           0.527         -0.068          0.493    0.619
Item 38           0.406          0.237          0.318    0.402
Item 39           0.334          0.428          0.291    0.377
Item 40           0.602         -0.257          0.418    0.530
Item 41           0.623         -0.313          0.490    0.626
Item 42           0.509         -0.024          0.381    0.477
Item 43           0.627         -0.323          0.420    0.536
Item 44           0.370          0.332          0.374    0.478
Item 45           0.527         -0.067          0.499    0.626
Item 46           0.537         -0.092          0.538    0.676
Item 47           0.458          0.105          0.426    0.534
Item 48           0.473          0.068          0.448    0.561
Item 49           0.489          0.028          0.380    0.476
Item 50           0.622         -0.310          0.583    0.744
Item 51           0.642         -0.365          0.612    0.785
Item 52           0.495          0.013          0.483    0.605
Item 53           0.494          0.016          0.452    0.567
Item 54           0.380          0.306          0.283    0.360
Item 55           0.415          0.216          0.395    0.500
Item 56           0.629         -0.329          0.560    0.716
 
 
 
                  DISTRACTOR SELECTION PROPORTIONS 
 
            A     B     C     D
Item 1  0.709 0.077 0.082 0.126
Item 2  0.143 0.148 0.171 0.530
Item 3  0.046 0.060 0.812 0.074
Item 4  0.140 0.574 0.138 0.142
Item 5  0.076 0.115 0.653 0.147
Item 6  0.073 0.733 0.134 0.054
Item 7  0.190 0.181 0.460 0.162
Item 8  0.029 0.062 0.044 0.856
Item 9  0.544 0.163 0.092 0.186
Item 10 0.036 0.077 0.069 0.808
Item 11 0.058 0.074 0.827 0.034
Item 12 0.553 0.296 0.094 0.048
Item 13 0.059 0.077 0.080 0.772
Item 14 0.110 0.193 0.473 0.211
Item 15 0.640 0.095 0.123 0.128
Item 16 0.256 0.447 0.180 0.104
Item 17 0.389 0.092 0.067 0.434
Item 18 0.110 0.488 0.137 0.245
Item 19 0.668 0.092 0.080 0.139
Item 20 0.128 0.198 0.502 0.149
Item 21 0.572 0.230 0.119 0.060
Item 22 0.437 0.180 0.252 0.109
Item 23 0.177 0.274 0.370 0.154
Item 24 0.134 0.569 0.096 0.174
Item 25 0.124 0.221 0.503 0.126
Item 26 0.075 0.741 0.080 0.077
Item 27 0.313 0.247 0.248 0.163
Item 28 0.394 0.175 0.224 0.174
Item 29 0.446 0.126 0.313 0.085
Item 30 0.422 0.188 0.261 0.098
Item 31 0.191 0.203 0.364 0.212
Item 32 0.164 0.324 0.234 0.244
Item 33 0.136 0.666 0.105 0.063
Item 34 0.489 0.252 0.143 0.085
Item 35 0.136 0.648 0.084 0.101
Item 36 0.097 0.122 0.144 0.604
Item 37 0.138 0.179 0.121 0.527
Item 38 0.406 0.136 0.273 0.150
Item 39 0.181 0.263 0.186 0.334
Item 40 0.100 0.198 0.602 0.066
Item 41 0.150 0.137 0.056 0.623
Item 42 0.509 0.128 0.147 0.180
Item 43 0.082 0.627 0.171 0.083
Item 44 0.304 0.370 0.149 0.137
Item 45 0.173 0.173 0.527 0.087
Item 46 0.090 0.152 0.179 0.537
Item 47 0.134 0.458 0.144 0.223
Item 48 0.093 0.158 0.473 0.232
Item 49 0.170 0.161 0.489 0.132
Item 50 0.096 0.622 0.121 0.117
Item 51 0.125 0.112 0.076 0.642
Item 52 0.495 0.248 0.131 0.078
Item 53 0.135 0.181 0.494 0.138
Item 54 0.189 0.380 0.245 0.133
Item 55 0.415 0.145 0.128 0.257
Item 56 0.093 0.112 0.108 0.629
 
 
 
                         DISTRACTOR Point-Biserial 
 
             A      B      C      D
Item 1   0.349 -0.197 -0.255 -0.086
Item 2  -0.023 -0.139 -0.229  0.304
Item 3  -0.222 -0.233  0.440 -0.230
Item 4  -0.105  0.281 -0.093 -0.184
Item 5  -0.218 -0.147  0.334 -0.125
Item 6  -0.239  0.384 -0.148 -0.219
Item 7  -0.238 -0.086  0.361 -0.121
Item 8  -0.201 -0.258 -0.236  0.442
Item 9   0.361 -0.191 -0.223 -0.078
Item 10 -0.235 -0.283 -0.244  0.490
Item 11 -0.272 -0.278  0.477 -0.182
Item 12  0.372 -0.113 -0.260 -0.209
Item 13 -0.228 -0.257 -0.267  0.505
Item 14 -0.199 -0.136  0.345 -0.097
Item 15  0.480 -0.229 -0.231 -0.206
Item 16 -0.060  0.343 -0.196 -0.168
Item 17 -0.094 -0.249 -0.199  0.379
Item 18 -0.177  0.341 -0.225 -0.034
Item 19  0.559 -0.291 -0.254 -0.250
Item 20 -0.181 -0.140  0.377 -0.134
Item 21  0.445 -0.183 -0.228 -0.190
Item 22  0.420 -0.176 -0.148 -0.165
Item 23 -0.162 -0.136  0.353 -0.054
Item 24 -0.235  0.543 -0.260 -0.221
Item 25 -0.197 -0.250  0.461 -0.097
Item 26 -0.187  0.467 -0.284 -0.178
Item 27 -0.131 -0.051  0.081  0.209
Item 28  0.298 -0.106 -0.080 -0.108
Item 29  0.351 -0.252 -0.037 -0.149
Item 30  0.347 -0.166 -0.081 -0.135
Item 31 -0.087 -0.117  0.258 -0.030
Item 32 -0.145  0.225 -0.174  0.132
Item 33 -0.206  0.431 -0.156 -0.183
Item 34  0.445 -0.115 -0.245 -0.167
Item 35 -0.236  0.532 -0.232 -0.219
Item 36 -0.177 -0.260 -0.244  0.543
Item 37 -0.303 -0.103 -0.176  0.493
Item 38  0.318 -0.230 -0.025 -0.062
Item 39 -0.084  0.062 -0.222  0.291
Item 40 -0.190 -0.109  0.418 -0.237
Item 41 -0.253 -0.146 -0.224  0.490
Item 42  0.381 -0.250 -0.220  0.048
Item 43 -0.153  0.420 -0.144 -0.212
Item 44 -0.058  0.374 -0.152 -0.145
Item 45 -0.180 -0.235  0.499 -0.146
Item 46 -0.211 -0.288 -0.142  0.538
Item 47 -0.147  0.426 -0.225 -0.077
Item 48 -0.217 -0.206  0.448 -0.076
Item 49 -0.177 -0.112  0.380 -0.085
Item 50 -0.246  0.583 -0.256 -0.239
Item 51 -0.289 -0.277 -0.219  0.612
Item 52  0.483 -0.112 -0.259 -0.191
Item 53 -0.125 -0.210  0.452 -0.129
Item 54 -0.064  0.283 -0.047 -0.102
Item 55  0.395 -0.140 -0.136 -0.098
Item 56 -0.232 -0.245 -0.216  0.560
 
 
 
                               DISTRACTOR Biserial 
 
             A      B      C      D
Item 1   0.462 -0.365 -0.462 -0.138
Item 2  -0.036 -0.214 -0.340  0.381
Item 3  -0.484 -0.466  0.638 -0.428
Item 4  -0.163  0.354 -0.145 -0.286
Item 5  -0.404 -0.242  0.431 -0.192
Item 6  -0.448  0.517 -0.234 -0.451
Item 7  -0.344 -0.125  0.453 -0.182
Item 8  -0.511 -0.509 -0.518  0.684
Item 9   0.453 -0.286 -0.391 -0.113
Item 10 -0.553 -0.522 -0.467  0.707
Item 11 -0.548 -0.520  0.705 -0.437
Item 12  0.468 -0.149 -0.453 -0.447
Item 13 -0.457 -0.475 -0.488  0.701
Item 14 -0.331 -0.196  0.433 -0.137
Item 15  0.616 -0.397 -0.373 -0.328
Item 16 -0.082  0.431 -0.287 -0.284
Item 17 -0.119 -0.436 -0.383  0.477
Item 18 -0.294  0.427 -0.353 -0.047
Item 19  0.725 -0.509 -0.464 -0.390
Item 20 -0.288 -0.201  0.473 -0.205
Item 21  0.561 -0.254 -0.370 -0.378
Item 22  0.529 -0.257 -0.202 -0.275
Item 23 -0.238 -0.182  0.451 -0.082
Item 24 -0.371  0.684 -0.450 -0.326
Item 25 -0.317 -0.350  0.578 -0.155
Item 26 -0.348  0.632 -0.518 -0.329
Item 27 -0.171 -0.069  0.110  0.313
Item 28  0.378 -0.157 -0.111 -0.159
Item 29  0.441 -0.404 -0.048 -0.267
Item 30  0.438 -0.241 -0.110 -0.233
Item 31 -0.126 -0.166  0.331 -0.042
Item 32 -0.217  0.293 -0.241  0.181
Item 33 -0.323  0.559 -0.263 -0.360
Item 34  0.558 -0.156 -0.381 -0.298
Item 35 -0.371  0.684 -0.418 -0.373
Item 36 -0.306 -0.422 -0.378  0.689
Item 37 -0.475 -0.150 -0.286  0.619
Item 38  0.402 -0.362 -0.033 -0.096
Item 39 -0.123  0.083 -0.323  0.377
Item 40 -0.325 -0.157  0.530 -0.458
Item 41 -0.388 -0.229 -0.456  0.626
Item 42  0.477 -0.400 -0.339  0.070
Item 43 -0.278  0.536 -0.213 -0.382
Item 44 -0.076  0.478 -0.233 -0.228
Item 45 -0.266 -0.348  0.626 -0.260
Item 46 -0.372 -0.439 -0.208  0.676
Item 47 -0.231  0.534 -0.347 -0.108
Item 48 -0.380 -0.312  0.561 -0.105
Item 49 -0.263 -0.168  0.476 -0.134
Item 50 -0.427  0.744 -0.415 -0.391
Item 51 -0.464 -0.459 -0.405  0.785
Item 52  0.605 -0.153 -0.410 -0.350
Item 53 -0.196 -0.307  0.567 -0.202
Item 54 -0.092  0.360 -0.064 -0.161
Item 55  0.500 -0.217 -0.217 -0.132
Item 56 -0.406 -0.405 -0.361  0.716
 
 
 
> 
> item.analysis$plots[[1]]   # Item Trace Line for the first item
> 
> # item.analysis$plots[[2]]   # Item Trace Line for the second item
> # item.analysis$plots[[3]]   # Item Trace Line for the third item
> # item.analysis$plots[[4]]   # Item Trace Line for the fourth item
> # item.analysis$plots[[5]]   # Item Trace Line for the fifth item
> # item.analysis$plots[[6]]   # Item Trace Line for the sixth item
> # item.analysis$plots[[7]]   # Item Trace Line for the seventh item
> # item.analysis$plots[[8]]   # Item Trace Line for the eigth item
> # item.analysis$plots[[9]]   # Item Trace Line for the ninth item
> # item.analysis$plots[[10]]  # Item Trace Line for the tenth item
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>